Sun May 17
7:00 AM - 6:00 PM
Registration Hours
Session Type: General Meeting
8:00 AM - 12:00 PM
Applied Generative AI for HEOR: Introduction
Session Type: Short Course
Topics: Methodological & Statistical Research
Level: Introductory
Separate registration required.
The rapid advancement in generative artificial intelligence (GenAI) presents an opportunity for transformative potential in the field of health economics and outcomes research (HEOR). This course provides an introductory understanding of generative AI models with a particular focus on large language models (LLMs), which are transforming the field of HEOR. Participants will be provided with an overview of the most appropriate ways to access LLMs, going beyond the use of chatbots. Further, they will be given insights into how to use prompt engineering, retrieval-augmented generation (RAG) and agents to conduct scientific research and gain an understanding on issues pertaining to privacy and security when using GenAI for HEOR. Participants will further explore specific applications of these models for conducting robust scientific HEOR research in, for example, systematic literature reviews (SLR) and economic evaluation. The course aims to equip participants with the knowledge to begin to use generative AI techniques for specific HEOR contexts and to appreciate how these innovative approaches can enhance HEOR activities. Practical exercises using Python and relevant AI frameworks will be incorporated for participants to follow along.
PREREQUISITES: Students should have a general understanding of common HEOR concepts such as SLRs and cost-effectiveness models. Knowledge of Python or similar programming languages such as R is considered a benefit but not required.
Speakers
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William Rawlinson
Estima Scientific, London, United Kingdom
Will is a senior health economist at Estima Scientific holding a degree in Physics and Philosophy from the University of Oxford. Will has 4 years’ experience developing cost-utility models and has specialized in applications of generative AI to health economic modelling. Will has published on the automation of R modelling using large language models (LLMs), and more recently has focused on applications of LLMs to Excel modelling and model reporting.
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Tim Reason, MSc
Estima Scientific, South Ruislip, United Kingdom
Tim Reason is co-founder of Estima Scientific and specializes in AI and evidence synthesis, having spent 15 years in the field of HEOR and technology. Tim is managing director of Estima, driving business activities, innovation and strategy for the company. Tim’s specializes in the intersection of HEOR, software development and AI to drive better outcomes for patients. Tim is the lead author on 2 seminal papers in AI for HEOR, showing that AI can be used to automate health economic modelling and NMA.
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Sven L Klijn, MSc
Bristol Myers Squibb, Utrecht, Netherlands
Sven Klijn is director at Bristol Myers Squibb in the Global HEOR Economic & Predictive Modeling group, where he leads the innovative modeling agenda in hematology and cell therapy. In addition, Sven has an active role in providing modeling education and masterclasses at international congresses. He has widely published on innovative methods, especially in the field of survival extrapolation and Generative AI. Sven has training in public health and health economics and previously had various roles in CROs related to health economic modeling.
Prompt Engineering for HEOR: Practical Skills and Use Cases for HEOR Professionals
Session Type: Short Course
Topics: Methodological & Statistical Research
Level: Introductory
Separate registration required.
Prompt engineering—the art and science of designing effective inputs for generative AI—has become a critical skill for health economists and outcomes researchers. Mastery of prompt engineering can significantly enhance productivity, accuracy, and innovation in HEOR, unlocking the full potential of large language models (LLMs) and other AI tools. This course delivers a comprehensive introduction to prompt engineering, tailored specifically for the HEOR context. Participants will gain hands-on experience with practical prompt strategies for systematic literature reviews (SLRs), economic modeling, real-world evidence generation, and more. The curriculum also addresses current best practices and common pitfalls, equipping attendees to confidently apply prompt engineering in regulated and high-stakes settings.
PREREQUISITE: Basic knowledge of systematic literature reviews and economic modeling will be helpful. No prior knowledge or use of AI is required.
Speakers
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Rachael Fleurence, MSc, PhD
Apodeixis Strategies, LLC, Boston, MA, United States
Rachael L. Fleurence, PhD, MSc, is the head of Evidence and AI Solutions, at Value Analytics Lab, a life sciences consultancy. A health economist by training, she previously served as senior advisor to Dr. Francis Collins at the National Institutes of Health, where she led a national initiative to eliminate Hepatitis C in the US. She also served as an advisor to the National Institute of Biomedical Imaging and Bioengineering (NIBIB), focusing on artificial intelligence and machine learning. Previously, Dr. Fleurence was a senior health policy advisor in the Biden-Harris White House and Senior Advisor to the NIH Director. She played a key role in the federal COVID-19 response, leading the “Say Yes! COVID Test” program and serving on White House pandemic policy groups. Prior to her federal service, she led the National Evaluation System for health Technology Coordinating Center (NESTcc) and PCORnet at PCORI and spent several years in the private sector in health economics and outcomes research (HEOR) consulting. Dr. Fleurence has received multiple NIH Director’s Awards, the HHS Secretary’s Award for Distinguished Service, and the National Champion for Global Hepatitis Elimination award. She co-led the ISPOR Task Force on EHR Data for Health Technology Assessment, serves on the ISPOR Working Group on Generative AI, and is an associate editor for Value in Health. She also sits on the boards of CTTI (the Clinical Trials Transformation Initiative) and ICN (the ImproveCareNow network). She holds degrees from Cambridge University, ESSEC Business School (Paris), and the University of York (UK).
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Jag Chhatwal, PhD
Harvard Medical School / Massachusetts General Hospital, Boston, MA, United States
Jag Chhatwal, PhD, is the director of the Institute for Technology Assessment at Massachusetts General Hospital and an associate professor at Harvard Medical School. He also serves as core faculty at the Center for Health Decision Science, Harvard T.H. Chan School of Public Health. Dr. Chhatwal has co-authored more than 125 original research articles and editorials in leading peer-reviewed journals. His research has informed health policy decisions at prominent organizations including the White House, the World Health Organization, and the CDC, and has been featured in major media outlets such as CNN, Forbes, National Public Radio, The New York Times, and The Wall Street Journal. Dr. Chhatwal serves as an associate editor of Value in Health and as guest editor for its special issue on artificial intelligence. He is also a member of the ISPOR Generative AI Working Group.
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Dalia Dawoud, BSc, MSc, PhD
Cytel Inc., London, United Kingdom
Dalia Dawoud, PhD, is Research Principal, HTA Policy and Strategy. She is also the Director and CEO of PEHTA Consulting Ltd. and holds a professor position at the Faculty of Pharmacy, Cairo University. She has over 15 years experience as a health economist and researcher. Her work is largely focused on the application of HEOR in HTA and clinical guideline development. She worked at leading organizations including NICE, where she led a portfolio of HORIZON Europe projects such as HTx, EDiHTA and SUSTAIN HTA, and the Royal College of Physicians, London. She is widely published in the areas of health economics and outcomes research and serves as associate editor for Value in Health and as director on ISPOR Board of Directors (2023-2026). She is also a member of the ISPOR AI Working Group and ISPOR Living HTA Working Group.
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Turgay Ayer, PhD
Value Analytics Labs, Boston, MA, United States
Turgay Ayer, PhD, holds the Virginia C. and Joseph C. Mello Chair and serves as the research director for Healthcare Analytics and Business Intelligence at the Center for Health & Humanitarian Systems at Georgia Tech. He is also the chief technology officer at Value Analytics Labs. Dr. Ayer holds a courtesy appointment at Emory Medical School where he teaches Big Data Analytics courses and serves as a Senior Scientist at the Centers for Disease Control and Prevention (CDC). Dr. Ayer’s research focuses on health economics modeling (HEOR), real-world evidence, data science, machine learning, econometric modeling, and healthcare analytics. He has published over 80 peer-reviewed journal papers and more than 300 conference abstracts, with his work featured in top-tier business, engineering, medical, and health policy journals. His research has attracted substantial attention from major media outlets, including The Wall Street Journal, The Washington Post, US News, and NPR. A recognized expert in HEOR, Dr. Ayer has been at the forefront of applying generative AI to navigate healthcare systems and support better decision-making. He has contributed significantly to the development of advanced models for predicting healthcare outcomes and designing innovative cost-effectiveness analysis frameworks. Under his leadership, Value Analytics Labs has focused on the development of cutting-edge technologies, including ValueGen.AI, to enhance healthcare analytics and improve the efficiency of healthcare decision-making processes.
Leveraging Real-World Data Throughout the Medical Devices and Diagnostics Product Lifecycle
Session Type: Short Course
Topics: Real World Data & Information Systems
Level: Intermediate
Separate registration required.
This course will focus on the opportunities and practical applications of conducting real-world data (RWD) studies and generating real-world evidence (RWE) for medical devices and diagnostics (MDD). RWD is increasingly being leveraged to support a variety of purposes in the MDD space, including regulatory, reimbursement, health technology assessment (HTA), and business needs. Leveraging RWD, especially secondary data sources, for MDD poses unique challenges, such as the difficulty in identifying devices in RWD sources, device operator characteristics potentially influencing outcomes, and the need to consider continuous device iterations in RWE generation. Thus, high-quality data and carefully designed studies are critical to increase the credibility and acceptance of RWD/E for MDD.
Additionally, the course will provide an overview of the best practices, processes, and methods to design and execute studies to gather market insights and generate high-quality evidence for multiple stakeholders. The course will review different types of secondary data sources and methods to conduct descriptive analyses and comparative effectiveness research along the MDD product lifecycle. Specific topics will include the common questions that are answered with secondary data and the challenges and potential solutions that are unique to MDD products. Case studies will focus on a variety of technologies, from new technologies to follower products, and the strategies that are used to increase the chances of acceptance to gain and expand market access.
PREREQUISITES: Participants should be familiar with general HEOR methods and tools used in MDD, and the general concepts of real-world data and evidence, including the types of healthcare data that is generated as part of routine healthcare.
Speakers
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Belinda A Mohr, PhD
Medtronic, Phoenix, AZ, United States
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Arthi Chandran, MPH, MS, DrPH
ABBOTT, Santa Clara, CA, United States
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Bijan J Borah, MSc, PhD
Mayo Clinic College of Medicine, Edina, MN, United States
Causal Inference and Causal Diagrams in Big, Real-World Observational Data and Pragmatic Trials
Session Type: Short Course
Topics: Real World Data & Information Systems
Level: Advanced
Separate registration required.
Innovative causal inference and target trial emulation methods are needed for the design and analysis of big real-world observational data and pragmatic trials. This course will introduce the principles of causation in comparative effectiveness research, the use of causal diagrams (directed acyclic graphs; DAGs) and focus on causal inference methods for time-independent confounding (multivariate regression, propensity scores) and time-dependent confounding (g-formula, marginal structural models with inverse probability of treatment weighting, and structural nested models with g-estimation). The “target trial” concept and a counterfactual approach with “replicates” will be used to apply causal methods to big real-world datasets with case examples from oncology, cardiovascular disease, HIV, nutrition and obstetrics. The course will consist of lectures, case examples drawn from the published literature and interactive discussion. The intended audience includes researchers from all substance matter fields, statisticians, epidemiologists, outcome researchers, health economists and health policy decision makers interested either in methods of causal analysis or causal interpretation of results based on the underlying method.
PREREQUISITE: Students are expected to have a basic knowledge in epidemiologic studies and methods (including the concept of confounding).
Speakers
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Uwe Siebert, MPH, MSc, ScD, MD
UMIT TIROL - University for Health Sciences and Technology; Harvard Chan School of Public Health, Hall in Tirol, Austria
Uwe Siebert, MD, MPH, MSc, ScD, is a professor of Public Health, Medical Decision Making and Health Technology Assessment (HTA), chair of the Department of Public Health, Health Services Research and HTA at UMIT TIROL-University for Health Sciences and Technology in Austria and director of the Division for HTA in the ONCOTYROL–Center for Personalized Cancer Medicine in Austria. He is also adjunct professor of Epidemiology and Health Policy & Management at the Harvard T.H. Chan School of Public Health and Affiliated Researcher in the Program on Cardiovascular Research at the Institute for Technology Assessment and Department of Radiology at the Massachusetts General Hospital, Harvard Medical School, Boston.
After medical school, he worked for several years as a physician in international public health projects in West Africa, Brazil, and Germany. He then earned an MPH at the Munich School of Public Health and completed an MSc in Epidemiology and a ScD in Health Policy and Management with a concentration in decision sciences at the Harvard School of Public Health.
His research interests include applying real-world evidence-based quantitative, causal and translational methods from public health, epidemiology, artificial intelligence, comparative effectiveness research, health services and outcomes research, economic evaluation, modeling, and health data a d decision science in the framework of health care policy advice and HTA as well as in the clinical context of routine health care, clinical guideline development, public health policies and patient guidance. His research focuses on cancer, infectious disease, cardiovascular disease, neurological disorders, and others.
He has been leading projects/work packages in several EU FP7, H2020 and Horizon Europe projects (eg, ELSA-GEN, BiomarCaRE, MedTecHTA, DEXHELPP, EUthyroid, FORECEE, MDS-RIGHT, RECETAS, CORE-MD, EUREGIO-EFH, CIDS, OnCoVID, 4D PICTURE, CATALYSE). He teaches HTA, health economics, modeling, epidemiology, causal inference and target trial emulation, and data and decision science for academia, industry, and health authorities in Europe, North and South America, and Asia. He directs the Continuing Education Program on Health Technology Assessment & Decision Sciences (htads.org).
He has served as member of the ISPOR Directors Board and as president of the Society for Medical Decision Making (SMDM). He is a leadership member of the ISPOR Personalized/Precision Medicine SIG, a member of the Latin America Consortium Advisory Committee of ISPOR, and co-chair of the ISPOR-SMDM Modeling Good Research Practices Task Force. He is a member of the Oncology Advisory Council and the National Committee for Cancer Screening of the Austrian Federal Ministry of Health.
He has authored more than 400 publications (> 30,000 citations, H index > 80), and is editor of the European Journal of Epidemiology. Further information Internet: http://htads.org, umit-tirol.at/dph, hsph.harvard.edu/uwe-siebert, Twitter: @UweSiebert9, LinkedIn: uwe-siebert9.
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Douglas Faries, PhD
Consultant, Alma, AR, United States
Doug Faries has a PhD in Statistics from Oklahoma State University. He spent 34 years as a statistician in the pharmaceutical industry, retiring as a vice president of Real-World Access and Analytics at Eli Lilly and Company where he led the development of real-world analytical capabilities for the business. Doug has extensive experience with the design and analysis of observational research including comparative effectiveness analyses and sensitivity analysis for unmeasured confounding. He remains active in the statistical community with over 150 peer-reviewed manuscripts, authoring books and book chapters on analysis of observational data, and teaching short courses on causal inference at national meetings.
Designing a Patient-Centered Strategy for Drug Development and Value
Session Type: Short Course
Topics: Patient-Centered Research
Level: Intermediate
Separate registration required.
This course focuses on how to design and govern a fit-for-purpose patient-centered strategy before instruments, endpoints, or implementation approaches are locked into a clinical program. Rather than teaching how to execute a specific measurement system, the course equips participants to make informed, defensible decisions about whether, when, and how tools such as patient-reported outcomes should be used to support patient-centered evidence generation across development, regulatory review, reimbursement, and value communication. The course will provide an overview of where and how patient-centered evidence can provide value to decision makers across the drug development lifecycle.
Participants will learn structured frameworks for identifying what aspects matter most to patients and other decision makers, identifying available measures and other ways to gather patient-centered information, assessing the strengths and limitations of existing instruments, determining when adaptation or new development may be warranted, and how to develop a measurement strategy to inform multiple decision makers. The course emphasizes critical judgment over mechanics, helping participants understand how qualitative and quantitative evidence expectations vary by decision maker (patients, clinicians, regulators, HTA bodies, payers) and how these differences influence early strategy choices.
Through interactive discussion and real-world examples, the course explores common strategic missteps—such as misaligned endpoints, overambitious claims, or inappropriate instrument selection—that can undermine downstream clinical, regulatory, or access objectives. Success stories are used to illustrate how strong upfront strategy development enables smoother execution later. By the end of the course, participants will be prepared to lead patient-centered strategy conversations, challenge assumptions, align cross-functional decision makers, and set realistic objectives—whether the next step is selecting an existing measurement system, adapting a legacy instrument, or deciding not to pursue patient-reported outcome endpoints at all.
PREREQUISITE: This course assumes that participants will have a basic knowledge of key PRO-related concepts (eg, health-related quality of life, symptoms, impacts, a general knowledge of the PRO development steps, and a working knowledge of PRO measurement within clinical programs)
Speakers
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Ari Gnanasakthy, MBA, MSc
RTI- Health Solutions, RESEARCH TRIANGLE PARK, NC, United States
Ari Gnanasakthy is head of Patient-Reported Outcomes at RTI-HS. Prior to RTI-HS.
Mr. Gnanasakthy was the executive director and head of the Patient-Reported Outcomes Center of Excellence at Novartis Pharmaceuticals. He has almost 25 years of experience in the pharmaceutical industry. At Novartis, he worked in several departments, including Biostatistics, Health Economics, Pricing, and Outcomes Research. After receiving his bachelor's degree in mathematics, statistics, and computing, Mr. Gnanasakthy joined Rothamsted Experimental Station (UK), where he was responsible for the statistical analysis of survey data of agricultural soil in England and Wales. He then joined the Milk Marketing Board (UK), where he was a part of the team responsible for modeling lactation curves of dairy cows. Mr. Gnanasakthy's extensive experience in the field of statistics and outcome research has resulted in numerous abstracts and almost 40 publications. Throughout his career, Mr. Gnanasakthy has developed and validated over a dozen patient-reported outcomes instruments and currently serves in the editorial board of Cancer Clinical Trials and a reviewer for many professional journals, including Value in Health.
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Rebecca Crawford, MA
RTI Health Solutions, Manchester, United Kingdom
Ms. Crawford has 13 years of experience providing consultative support to pharmaceutical companies with a focus on the development of patient-reported outcome (PRO) measurement strategies to best meet the needs of their clinical trial programs.
Ms. Crawford has developed, culturally adapted, and validated clinical outcome assessment measures, including PROs for several different therapeutic areas. Ms. Crawford has expertise in research design and in the application of both traditional and innovative qualitative research methods, including the collection and analysis of social media data to provide insights into the patient disease and treatment experience.
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Shanshan Qin, PhD
RTI- Health Solutions, Research Triangle Park, NC, United States
Shanshan Qin, PhD, received her training on Qualitative Methodology (including statistic inference and estimation, traditional and modern testing theories, structural equation modeling, and mixed and mixture modeling) at University of Georgia. She has 10 years of experience as a psychometric analyst and statistic consultant and has been working on psychometric evaluation of clinical outcome assessments (COAs) and support of regulatory review of COA labeling claims in various therapeutic areas, including dermatology, gastroenterology, diabetes, oncology, ophthalmology, and mental disorder. She is an experienced programmer of SAS, R, and IRT PRO.
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Lynda Doward, MSc
RTI- Health Solutions, Manchester, United Kingdom
Ms. Doward has over 30 years of experience conducting patient-centered outcomes research including the provision of strategic advice to pharmaceutical companies in the incorporation of the patient voice into drug development programs. Ms. Doward is an expert in the development of clinical outcome assessment (COA) strategies including the development of patient-centered clinical trial endpoints, the implementation of patient-reported and other COA outcome measures in clinical trial programs, and the inclusion of PRO and other COA value messages at key drug development hurdles. Ms. Doward has extensive experience in supporting pharmaceutical clients in their COA-related submissions to regulatory agencies in Europe and the US and advises on health-utility measurement strategies for reimbursement agencies in Europe. Ms. Doward has led the development of over 40 COA questionnaires that have been adapted and validated for use in over 60 languages worldwide.
Ms. Doward currently serves on the ISPOR COA Special Interest Group (leadership committee) and the ISPOR Patient Council (member) and was a member of the leadership committee of the completed ISPOR Good Research Practices Task Force for the measurement of health state utilities in clinical trials. Ms. Doward has acted as a consultant to the World Health Organization and has served as a Research Advisor to the UK Department of Health, and medical charities in the United Kingdom.
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Diane Whalley, PhD
RTI- Health Solutions, Manchester, United Kingdom
8:00 AM - 3:30 PM
Budget Impact Analysis in Practice: A Hands-On Course on Strategic Conceptual Design, Model Building, and Communication
Session Type: Short Course
Topics: Economic Evaluation
Level: Intermediate
Separate registration required.
This hands-on, interactive course equips participants with the conceptual and practical tools needed to develop, adapt, and communicate budget impact analyses (BIA) for real-world decision making.
The course begins with a brief review of BIA concepts and a 6-step approach to strategically design these analyses. We will discuss practical applications, including customization to accommodate payer-specific data; balance of structural simplicity, accuracy, and face validity; interpretation of results; and development and communication of compelling value messages. Technical topics will include static versus dynamic budget impact models, good Excel model-building practices, considerations for device and diagnostic technologies, and incorporation of realistic features such as patient copayments and availability of generics.
Instructors will walk through 2 budget impact models programmed in Excel (1 static and 1 dynamic) and will work with participants during hands-on exercises to customize and adapt these models to specific real-world circumstances. These Excel-based models will be provided to participants in advance, both for use during the session and for later reference. Throughout the course, participants will have opportunities to network and to work in small groups to discuss key concepts, plan and implement model adaptations, and develop and communicate value narratives.
This course is designed for participants seeking to deepen their understanding of BIA, gain practical exposure to Excel-based models, and strengthen their ability to communicate BIA in ways that influence decision making. Registrants who wish to participate in the interactive portions of the course will need to bring materials for handwrtten activities.
PREREQUISITE: Participants are expected to have familiarity with basic budget-impact analysis concepts and working knowledge of Microsoft Excel. Individuals who need foundational knowledge of budget impact models are encouraged to register for the introductory level virtual short course “Primer on a 6-Step Approach to Budget Impact Analysis” on March 25, 2026. A microcourse on the basics of Budget Impact Analysis is available in the ISPOR Education Center.
Speakers
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Stephanie Earnshaw, PhD
Access Strategy Consulting, Pittsboro, NC, United States
Stephanie Earnshaw has performed health outcomes and health services research for 30+ years. Her research focuses on applying decision-analysis techniques (eg, decision trees, Markov processes, simulation) to industry-related issues and health care problems. In addition to developing budget-impact and cost-effectiveness models to support health technologies for the pharmaceutical, biotechnology, and diagnostic and medical device industry, she has developed innovative mathematical models using these methods to determine pricing strategy, predict clinical outcomes, allocate resources, and cost care pathways particularly in support of medical diagnostics.
Dr. Earnshaw received her PhD in Industrial Engineering at North Carolina State University and is a member of ISPOR and the Institute for Operations Research and Management Sciences. She has presented her work at professional conferences and has published in several peer-reviewed journals. She has presented workshops and various courses on decision-analytic modeling techniques for pharmaceutical companies and organizations such as ISPOR, the Academy of Managed Care Pharmacy (AMCP), and the Centers for Disease Control and Prevention (CDC). Dr. Earnshaw has served on the ISPOR Board of Directors and as Chair of the Audit Committee and Educational Council. She has held an Adjunct Faculty appointment at the University of North Carolina’s Eshelman School of Pharmacy, Division of Pharmaceutical Outcomes and Policy, is honored as a Distinguished Alumni in Industrial and Systems Engineering at North Carolina State University and is one of the lead authors of “Budget-Impact Analysis of Health Care Interventions: A Practical Guide.”
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Anita Brogan, MSc, PhD
AESARA, San Diego, CA, United States
Anita Brogan is vice President of Value Evidence at AESARA, Inc. In her role, she uses analytical techniques to assess and communicate the health and economic impact of emerging pharmaceutical and biotechnology interventions. She leads development of user-friendly and transparent cost-effectiveness, budget-impact, optimization, population, and other models programmed in Microsoft Excel and other platforms. She has expertise in modeling methodologies such as Markov and other stochastic models, infectious disease dynamic transmission models, simulation, regression, linear and nonlinear programming, and various types of sensitivity analysis. Dr. Brogan has developed models and analyses in the areas of HIV, hepatitis C, RSV, norovirus, Ebola, influenza, cystic fibrosis, bone health, mental health, women’s health, oncology, chronic pain, age-related macular degeneration, hospital-acquired infection, financial portfolio optimization, and vehicle routing. Her research has been presented at various professional conferences and published in peer-reviewed journals.
Dr. Brogan holds a PhD in Operations Research from the University of North Carolina at Chapel Hill. She serves on editorial board of Pharmacoeconomics and the ISPOR education council. She has presented workshops and short courses on decision-analytic modeling techniques in a variety of venues, including meetings of ISPOR and the Academy of Managed Care Pharmacy (AMCP). She is co-author of the book “Budget-Impact Analysis of Health Care Interventions: A Practical Guide.”
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Ashley Davis, PhD
RTI Health Solutions, Research Triangle Park, NC, United States
Ashley Davis is a senior director within the Health Economics division at RTI Health Solutions (RTI-HS). She holds a PhD in Industrial Engineering and Management Sciences from Northwestern University and has been with RTI- HS for 10 years. She has presented short courses on budget impact modeling techniques in a variety of venues, including meetings of The Professional Society for Health Economics and Outcomes Research (ISPOR).
In her role at RTI-HS, Dr. Davis uses analytical methodologies to evaluate the clinical and economic value of upcoming pharmaceutical products and changes to healthcare policies. She has developed user-friendly and transparent cost- effectiveness, cost-utility, and cost-consequence models; budget-impact models; resource allocation models; and infectious disease transmission models programmed in Microsoft Excel and other platforms. She has experience with numerous types of modeling techniques, including Markov and other stochastic models, simulation, statistical analysis, linear and nonlinear programming, robust optimization, and various types of sensitivity analysis. Dr. Davis has developed models and analyses in the areas of HIV, hepatitis C, cystic fibrosis, herpes zoster, influenza, pneumococcal disease, respiratory syncytial virus, severe asthma, chronic obstructive pulmonary disease, eosinophilic esophagitis, spinal surgery, cytomegalovirus, and organ transplantation. Her research has been presented at various professional conferences and published in peer- reviewed journals.
11:00 AM - 12:00 PM
First-Time Attendee Orientation
Session Type: General Meeting
New to ISPOR? Join us for this engaging and informative session designed to help first-time attendees make the most of their experience at ISPOR 2026. You’ll gain insights into the conference structure, key sessions, and networking opportunities while connecting with fellow newcomers and ISPOR leaders. Whether you’re looking to navigate the agenda, maximize learning, or build professional relationships, this session will set you up for success. Don’t miss this chance to start your ISPOR journey with confidence!
12:00 PM - 1:00 PM
Break (Lunch on Own)
Session Type: General Meeting
1:00 PM - 5:00 PM
Applied Generative AI for HEOR: Advanced Architectures
Session Type: Short Course
Topics: Methodological & Statistical Research
Level: Intermediate
Separate registration required.
Generative AI (GenAI) is rapidly transforming how health economics and outcomes research (HEOR) is conducted from literature reviews and evidence synthesis to economic modeling and HTA submissions. As the field moves beyond experimentation, professionals face a new challenge: how to responsibly validate, implement, and scale GenAI solutions in real-world HEOR settings.
This intermediate-level course builds upon basic concepts and is designed for HEOR professionals, data scientists, and decision makers seeking to understand not only how GenAI works, but how to implement and evaluate it effectively within regulated and evidence-driven environments. The course provides a practical framework for moving “from prototype to practice,” describing the lifecycle of GenAI implementation—from early sprints and pilot projects to production deployment. Participants will explore both technical and organizational perspectives, including workflow orchestration, modularization, scaling, and change management.
Retrieval-Augmented Generation (RAG) is a cornerstone architecture that integrates external knowledge bases into LLM workflows. Faculty will discuss why RAG is particularly relevant for HEOR, demonstrating how external information (eg, clinical data, published evidence, HTA guidance) can be incorporated in GenAI workflows according to best practice standards and used to improve factual accuracy and traceability. A guided practical session is included so participants become familiar with how to implement a simple RAG pipeline, learning how to chunk data, generate embeddings, and augment prompts for domain-specific use. The course will also provide an extensive overview of Agentic AI, a fast-evolving frontier in AI automation. Participants will examine how autonomous AI “agents” can coordinate multi-step HEOR processes—such as literature updates, model maintenance, or simulated committee reviews—while maintaining control and accountability. A second practical session will demonstrate an agentic workflow in action, showcasing task orchestration, monitoring, and boundary setting. Beyond technical topics, there will be a focus on evaluation and validation of GenAI solutions for HEOR, where participants will learn how to critically assess GenAI tools in terms of reliability, reproducibility, and regulatory alignment. This will also be discussed in the context of potential ethical concerns around the application of AI. Using frameworks such as ELEVATE-GenAI, and referencing NICE and FDA guidance, participants will learn how to ensure that AI-driven outputs meet HEOR’s high standards for quality and transparency. By the end of this course, participants will understand how to bridge the gap between exploratory AI use and operational excellence. They will leave with actionable frameworks and hands-on knowledge to evaluate, implement, and govern GenAI tools that enhance productivity, transparency, and scientific integrity across HEOR activities.
PREREQUISITES: Completion of the “Applied Generative AI for HEOR: Introduction” ISPOR course or familiarity with concepts such as prompt engineering, APIs, and LLM workflows. A basic understanding of Python or other similar scripting languages is recommended to get the most benefit from the guided practical sessions.
Speakers
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Sven L Klijn, MSc
Bristol Myers Squibb, Utrecht, Netherlands
Sven Klijn is director at Bristol Myers Squibb in the Global HEOR Economic & Predictive Modeling group, where he leads the innovative modeling agenda in hematology and cell therapy. In addition, Sven has an active role in providing modeling education and masterclasses at international congresses. He has widely published on innovative methods, especially in the field of survival extrapolation and Generative AI. Sven has training in public health and health economics and previously had various roles in CROs related to health economic modeling.
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Rajdeep Kaur, PhD
Pharmacoevidence Pvt. Ltd., Mohali, India
Dr. Rajdeep Kaur is the Lead of AI Sciences at Pharmacoevidence, with a Ph.D. in Computer Science and Engineering and 17+ years of expertise in advanced technologies. Her work focuses on Generative AI, machine learning, and cloud-enabled data systems, with a strong emphasis on real-world healthcare applications. She has successfully led multiple GenAI projects, combining deep technical expertise to deliver impactful AI-driven solutions.
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Ghayath Janoudi, MD, PhD
Loon, Ottawa, ON, Canada
Dr. Ghayath Janoudi, MBBS, MSc, PhD, is the Founder and CEO of Loon, an AI-driven clinical research and market access company developing scientifically validated AI agents for Health Economics and Outcomes Research (HEOR), Health Technology Assessment (HTA), and reimbursement strategy.
A medical doctor and health outcomes researcher by training, Dr. Janoudi holds a PhD in Clinical Epidemiology with a specialization in artificial intelligence for clinical research. He previously held senior leadership roles at Canada’s Drug Agency (formerly CADTH) and at clinical research organizations, where he led work on HTA, drug reimbursement policy, and value evidence evaluation.
A recognized thought leader in AI for clinical discovery, Dr. Janoudi is a well-published author in AI-enabled evidence synthesis, and was named Canada’s 2024 Emerging Healthcare Leader for his contributions to accelerating timely and equitable access to innovative therapies.
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Siguroli Teitsson, BSc, MSc
Bristol Myers Squibb, Denham, United Kingdom
Siguroli Teitsson is a Director in Global HEOR Economic & Predictive Modeling at Bristol Myers Squibb. In his role, Siguroli leads the advancement of innovative modeling and analytics in oncology, and drives the integration of cutting-edge AI automations in HEOR and market access, streamlining workflows to accelerate patient access to medicines. With a background in engineering and health economics, he has previously held senior roles in CROs and has extensive publication record in innovative analytics within the field of HEOR, contributing to advancements in methodology and practice.
Developing Decision-Grade Real-World Evidence
Session Type: Short Course
Topics: Real World Data & Information Systems
Level: Intermediate
Separate registration required.
In this course, participants will be introduced to the principles of what makes real-world evidence (RWE) decision-grade, including an extended example. In the first half of the course, we will review the most recent RWE frameworks and guidelines and examine case studies in which RWE was used in regulatory and HTA approval. The second half of the course is an extended example in which participants will examine a study that could support an indication expansion and interactively discuss how choices made in the design and implementation may affect the meaning and interpretability of results.
PREREQUISITE: Students are expected to be familiar with relevant concepts and methodologies for analyzing real-world data.
Speakers
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Sebastian Schneeweiss, ScD, MD
Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States
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Jeremy Rassen, ScD
Aetion, Inc., New York, NY, United States
Jeremy A. Rassen, MS, ScD is a pharmacoepidemiologist with 25 years of academic and industry experience. He is cofounder, president, and chief technology officer at Aetion, a healthcare technology company that delivers real-world evidence for life sciences companies, payers, and regulatory agencies. Prior to founding Aetion, Dr. Rassen was assistant professor of medicine at Harvard Medical School, where he focused on methods to improve the quality and validity of real-world data studies. He also worked in Silicon Valley in a variety of tech companies. Dr. Rassen received his bachelor’s degree in computer science from Harvard College and his master’s and doctorate degrees in Epidemiology from the Harvard TH Chan School of Public Health.
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Shirley Wang, PhD
Brigham & Women's Hospital, Harvard Medical School, Boston, MA, United States
Dr. Wang is an associate professor at Brigham and Women’s Hospital, Harvard Medical School and lead epidemiologist for the Food and Drug Administration's (FDA) Sentinel Innovation Center. She leads the Meta-Research in Pharmacoepidemiology program, with recent projects aimed at improving the transparency, reproducibility, and robustness of evidence from healthcare databases (www.repeatinitiative.org) and informing when and how real-world evidence studies can draw causal conclusions to inform regulatory or other healthcare decision-making (www.rctduplicate.org). She is currently PI on multiple NIH R01s and is also funded by FDA. Her methods work has received 3 awards from international societies.
Using RWE to Inform the Value and Affordability Assessment of Cell and Gene Therapies
Session Type: Short Course
Topics: Real World Data & Information Systems
Level: Intermediate
Separate registration required.
This short course explores the role of real-world evidence (RWE) in supporting the economic evaluation of cell and gene therapies (CGTs). Many CGTs are one-time therapies that have the potential to offer transformative sustained benefits for patients with severe conditions. In many situations, the ‘do-nothing’ alternative is the norm, so the need for a control arm may be futile yet reducing the options for patients to be included in allegedly active arms. However, at launch there is often resistance from payers to reimburse these potentially transformative therapies due to the limited validity of the supporting evidence (small, single arm trials, etc) which leads to uncertainty regarding: the size and heterogeneity of the patient population eligible for CGTs; the definition of standard of care and natural disease progression, given CGTs may unlock treatment possibilities of previously deemed untreatable and rare diseases; the novel therapy’s duration of benefit; and the relative effectiveness of the novel therapy compared to the current standard of care, particularly, as cell and gene therapies are often only supported by a single arm trial.
Payer concerns with these uncertainties in the evidence are heightened by the typically high up-front costs associated with cell and gene therapies and the consequence for their affordability. While there is generally not a good understanding of the effect sizes and costs of standard of care. This course will provide an overview of the potential contribution, planning and use of RWE to help address these concerns. We will assume payer archetypes that are focused on one or more of relative effectiveness and cost-effectiveness (value), and budget impact (affordability). Within these archetypes, we will discuss the role and acceptability of RWE to inform payment and policy with emphasis on eligibility, appropriate comparators, durability of benefit, spending for patients that meet criteria for eligibility and the development of appropriate outcome-based agreements. A strong focus will be brought on validity (internal and external) of the existing data. We will further provide participants with real-world examples of using RWE to inform policy making.
This course will target a wide range of participants, from medical operations to HEOR, interested in understanding the depth of issues to consider when balancing access with payment for CGTs.
PREREQUISITE: This course requires familiarity with basic economic evaluation and HTA concepts and methodologies of pharmaceuticals.
Speakers
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Daniel Gladwell, BA, MSc, PhD
Lumanity, Sheffield, United Kingdom
Dan Gladwell is the chief scientific officer for Lumanity HE&HTA. A health economist by background, he has a particular passion for demonstrating the value of highly innovative therapies that make a transformative difference to patient outcomes. Dan supported one of the first CAR T-cell therapies to be assessed by NICE. Since that appraisal Dan has been continuously engaged in supporting patient access to cell and gene therapies through engaging in HEOR evidence generation planning efforts at the Global, Regional and National levels; and informing efforts to shape the HTA policy context for cell and gene therapies.
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Antal T Zemplenyi, MSc, PhD
University of Colorado Skaggs School of Pharmacy and Pharmaceutical Science, Denver, CO, United States
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Oriol de Sola-Morales, MSc, PhD, MD
Fundacio HiTT, Barcelona, Spain
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Renske MT ten Ham, PhD
Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Amsterdam, Netherlands
PROs in Clinical Trials: Endpoint Selection, Regulatory Strategy and Label Claims
Session Type: Short Course
Topics: Patient-Centered Research
Level: Advanced
Separate registration required.
This short course shows clinical development teams how to implement PROMIS® (Patient-Reported Outcomes Measurement Information System) in registration trials and regulatory submissions, using FDA Patient-Focused Drug Development guidance. Participants learn regulator-aligned methods applicable to other PRO measures, from endpoint selection to labeling claims. PROMIS provides comprehensive health assessment across physical, mental, and social domains using IRT-based scoring, computer-adaptive testing, digital capabilities, and validation across 80+ languages. The course covers domain/measure selection, protocol specification, estimands, meaningful change determination, psychometric evaluation, digital ePRO implementation, global translations, and regulatory review preparation. Interactive case-based learning uses real disease examples to guide participants through endpoint selection, protocol development, and regulatory defense. Faculty analyze successful label claims and challenging submissions to identify critical success factors and common pitfalls applicable across PRO instruments, including real-world evidence and HTA applications. A laptop is recommended for interactive exercises and accessing online resources.
PREREQUISITES: Participants should have basic familiarity with clinical trials and patient-reported outcomes, clinical trial design and regulatory processes. Prior PROMIS® knowledge is not required.
Speakers
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David Cella, PhD
Northwestern University, Chicago, IL, United States
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Maja Kuharic, PhD
Northwestern University Feinberg School of Medicine, CHICAGO, IL, United States
Maja Kuharic, MPharm, MSc, PhD, is an Assistant Professor in the Department of Medical Social Sciences at Northwestern University Feinberg School of Medicine. Her research focuses on patient-reported outcomes (PROs), health-related quality of life, and economic evaluation. She specializes in the development, validation, and application of PROMIS measures and preference-based instruments such as the EQ-5D and EQ-HWB.
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Xiaodan Tang, PhD
Northwestern University, Chicago, IL, United States
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Heather Gelhorn, PhD
PPD Evidera Patient-Centered Research, Thermo Fisher Scientific, Winter Park, CO, United States
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Selena Daniels, PharmD, PhD
US Food and Drug Administration, Silver Spring, MD, United States
Dr. Selena Daniels serves as the Deputy Division Director in the Division of Clinical Outcome Assessment at the FDA. She provides direction, oversight, and leadership to a team of expert analysts who provide consultation and advice on clinical outcome assessment (COA) endpoint development and validation, including considerations for clinical trial design, conduct, analysis, interpretation, and reporting for regulatory determinations of medical product benefit.
Prior to joining the FDA in 2015, Dr. Daniels worked in the Health Economic and Outcomes Research (HEOR) group at Allergan, Inc (now Abbvie), where she developed and executed HEOR strategies, as well as developed and implemented innovative COA strategies and endpoints for clinical trials.
Dr. Daniels received her Doctor of Philosophy degree in Education at Nova Southeastern University and Doctor of Pharmacy degree at Loma Linda University.
Societal Valuation of Innovative Medicines: Emphasis on Investment Perspective and Orphan Disease
Session Type: Short Course
Topics: Health Policy & Regulatory
Level: Intermediate
Separate registration required.
Explore the value assessment of innovative drugs from the perspectives of relevant stakeholders, their respective data requirements, and their methods and processes. Gain a better understanding of the value assessment from the investor perspective, with a focus on orphan drugs and advanced therapy medical products (ATMPs). The value of medical innovation depends on a stakeholder's perspective in different decision contexts. Regulatory authorities (EMA, FDA) mainly consider the clinical value of medical innovation. In the context of coverage decisions, national health authorities may adopt a broader perspective by including clinical, economic criteria, and sometimes even other criteria such as equity and social values. For pricing and reimbursement, ""value-based pricing"" is the most widely accepted approach across countries, but it can vary from a narrow concept based on the incremental cost-effectiveness ratio (ICER) threshold to broader societal or holistic approaches.
Value-based pricing determines the maximum price from the national payer perspective. In the context of the investment decision, this price should exceed the minimum price for the investor acting in the international financial market to make a financial valuation. Furthermore, there are numerous other stakeholders, eg, patients, physicians, healthcare insurers, and employers--with their specific assessment of the value of medical innovation including, for example, patient and family quality of life, real-world effectiveness, budget impact, and the costs of lost productivity. Familiarity with health economic evaluation is desirable, but the course assumes little or no familiarity with economic valuation theory.
Speakers
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Lou Garrison, PhD
The Comparative Health Outcomes, Policy, and Economics (CHOICE) Institute, Seattle, WA, United States
Lou Garrison, PhD, is professor emeritus in The Comparative Health Outcomes, Policy, and Economics Institute in the School of Pharmacy at the University of Washington, where he joined the faculty in 2004.
For the first 13 years of his career, Dr. Garrison worked in non-profit health policy at Battelle and then the Project HOPE Center for Health Affairs, where he was the Director from 1989-1992. Following this, he worked as an economist in the pharmaceutical industry for 12 years. From 2002-2004, he was vice president and head of Health Economics & Strategic Pricing in Roche Pharmaceuticals, based in Basel, Switzerland.
Dr. Garrison received a BA in Economics from Indiana University, and a PhD in Economics from Stanford University. He has more than 150 publications in peer-reviewed journals. His research interests include national and international health policy issues related to personalized medicine, benefit-risk analysis, and other topics, as well as the economic evaluation of pharmaceuticals, diagnostics, and other technologies.
Dr. Garrison was elected as ISPOR President for July 2016-June 2017, following other leadership roles since 2005. He recently co-chaired the ISPOR Special Task Force on US Value Frameworks. He was selected in 2017 by PharmaVOICE as being among “100 of the Most Inspiring People” in the industry. He recently received the PhRMA Foundation and Personalized Medicine Coalition 2018 Value Assessment Challenge First-Prize Award as lead author on a paper on “A Strategy to Support the Efficient Development and Use of Innovations in Personalized and Precision Medicine.”
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Marlene Gyldmark, MPhil
Beigene, Basel, Switzerland
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Mark J Nuijten, MBA, PhD, MD
A2M - Minerva, bergen op zoom, Netherlands
Mark Nuijten is a medical doctor, health economist, valuation economist, and healthcare publicist. He is a visiting professor at Ben-Gurion University in Israel, setting up the department on Clinical and Economic Valuation of Medical Innovation. He has become a leading health policy and economics expert over the last 2 decades, reflected in more than 200 publications and leading positions in scientific societies and editorial boards. Dr. Nuijten was board director of ISPOR (2002-2004) and chair of the Management Board of Value in Health (2002-2004). He was a member of the Editorial Advisory Board of Value in Health. He obtained his PhD in health economics (2003) on the thesis “In search for more confidence in health economic modelling” at the Erasmus University, Rotterdam.
Mark Nuijten is founder of A2M (Ars Accessus Medica) and founding partner of the Minerva International Health Economic Network. He was trained as a physician and worked in clinical research before obtaining his international MBA from Erasmus University, Rotterdam, where he later was a senior staff member. Prior to setting up Ars Accessus Medica, Dr. Nuijten was the founding managing director of the IQVIA Quintiles office in the Netherlands, which included European responsibility for the policy and health economic division.
He is a pioneer in the field of healthcare innovation in biotechnology and has been the first classical health economist successfully applying and developing Discounted Cash Flow methodologies for valuation of biotechnology innovation (eg, a pricing model to assess prices of expensive orphan drugs from an investor’s perspective—published in a Nature journal). He also developed an integrated valuation model, an interactive dynamic tool for the economic valuation of R&D projects, which can be used to optimize the initial clinical program (eg, indication, comparator, outcomes, and study design), and the associated pricing and market access pricing strategy.
5:30 PM - 7:00 PM
ISPOR Quiz Bowl
Session Type: General Meeting
Join us for a competition of HEOR knowledge where student chapter teams go head-to-head for bragging rights and prizes! Formerly known as the Student Research Competition, this bracket-style tournament is an exciting and rapidly growing event.
7:00 PM - 8:00 PM
ISPOR Student and Faculty Icebreaker Reception
Session Type: General Meeting
Students, New Professionals, and Faculty are invited to connect and unwind in a relaxed setting after a full day of short course sessions. Following the ISPOR Quiz Bowl, continue the conversation over light bites and refreshing drinks before heading out to explore Philadelphia by night.
Mon May 18
7:00 AM - 8:30 AM
Morning Coffee Service
Session Type: General Meeting
Don't miss the start of the day with the Plenary Session. Enjoy your morning coffee as you listen to dynamic presentations intended to inspire and empower.
7:00 AM - 5:00 PM
Registration Hours
Session Type: General Meeting
8:30 AM - 10:00 AM
Plenary Session: US Pharmaceutical Policy: Leading or Following?
Session Type: Plenary
Topics: Health Policy & Regulatory, Economic Evaluation, Health Technology Assessment
Track: Access and Drug Pricing
Level: Advanced
Americans have run out of patience with paying three times more for innovative medicine than other developed countries. President Trump is negotiating ways to bring US drug prices in line with other countries through a most-favored-nation (MFN) approach. This strategy builds on efforts of the Biden Administration's Inflation Reduction Act (IRA) to directly negotiate drug prices in Medicare. In a wide-ranging discussion with Trump Administration officials, the biopharmaceutical industry, and payers, we will discuss MFN, IRA, and other efforts to lower drug prices in the United States -- with a view toward the economic and regulatory consequences and long-term consequences for the US and abroad.
Moderator
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Dana P. Goldman, PhD
University of Southern California Schaeffer Institute for Public Policy & Government Service, Los Angeles, CA, United States
Dana P. Goldman is University Professor of Public Policy, Pharmacy, and Economics at the University of Southern California and founding director of the USC Schaeffer Institute for Public Policy & Government Service. He has led the Schaeffer Center for Health Policy & Economics since its inception, establishing it as one of the world’s premier health economics organizations. He previously served as Dean of the USC Price School of Public Policy.
Dr. Goldman’s scholarship lies at the intersection of economics, medicine, and public policy. He is the author of more than 350 articles with more than 24,000 citations. He pioneered a “Netflix model” to improve access to treatments and has been awarded more than $50 million in grants from NIH. Dr. Goldman is an elected member of the National Academy of Medicine, the National Academy of Social Insurance, and the National Academy of Public Administration — three of his field’s highest honors. USC appointed him University Professor “for his decades of excellence as a policy leader and champion of interdisciplinary collaboration.”
He is a co-founder of EntityRisk and (formerly) Precision Health Economics and a scientific advisor to GRAIL, Edwards Lifesciences, and Mark Cuban Cost Plus Drug Company. He is a research associate at the National Bureau for Economic Research. He graduated from Cornell University and earned a Ph.D. in economics from Stanford University.
Speakers
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Courtney Piron
Novartis, Washington, DC, United States
Courtney Piron
Head, US Public Affairs
As Head of US Public Affairs, Courtney leads strategy, development and execution of federal and state government affairs, public policy, and issues advocacy activities for Novartis in the US. She also serves as Chair of the Novartis Patient Assistance Foundation, the Novartis US Foundation and the Novartis Political Action Committee.
Prior to joining Novartis, Courtney held leadership roles in a range of healthcare environments. Courtney served as Vice President, Federal Government Affairs at AbbVie. She led the global health care practice at APCO Worldwide, a public affairs consulting firm headquartered in Washington, DC. She was director of economic policy and research at Pfizer and director of public policy at Wyeth.
Courtney holds a bachelor’s degree from Dickinson College and a master’s degree in public policy from the University of Pittsburgh.
She has two sons and lives in Washington, D.C. with her husband.
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Liz Fowler, PhD, JD
Johns Hopkins Bloomberg School of Public Health, Arlington, VA, United States
Plenary Session: ISPOR Welcome Remarks and Keynote
Session Type: Plenary
Join us as we kick off ISPOR 2026. Under this year’s conference theme, HEOR at the Forefront of Policy, Access, and Value, ISPOR’s Chief Executive Officer will set the stage with opening remarks highlighting the transformative role of health economics and outcomes research in advancing patient-centered care, strengthening global health systems, and addressing pressing challenges such as affordability, adoption, and health disparities.
This session will also feature a keynote address. Keynote speaker to be announced.
Immediately following the opening presentations, the scientific plenary panel will take the stage.
Speaker
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Rob Abbott
ISPOR, Lawrenceville, NJ, United States
9:30 AM - 7:00 PM
Exhibit Hall Hours
Session Type: General Meeting
10:00 AM - 10:30 AM
Coffee and Connect
Session Type: General Meeting
Head to the exhibit hall to connect with fellow attendees and exhibitors over a steaming cup of coffee.
10:30 AM - 11:30 AM
Operationalizing Artificial Intelligence Guidance to Create Best in Class Abstraction and Curation Approaches
Session Type: Issue Panel
Topics: Health Policy & Regulatory, Real World Data & Information Systems, Study Approaches
Track: AI
Level: Intermediate
The panel will discuss global regulatory guidance on the use of artificial intelligence (AI) to support regulatory decision-making. The increasing prevalence of AI and its intersection with real-world data (RWD) is fundamentally changing how evidence is generated and assessed. AI’s ultimate value relies on extracting meaningful insights from complex RWD sources. A vast amount of this RWD exists in unstructured formats such as clinician notes and pathology reports. There is a pressing need to curate this data using natural language processing and other AI techniques. These techniques must be of sufficient quality so that the resulting analytic dataset can inform regulatory decision-making.
The moderator will provide an overview of global guidances from authorities such as EMA, NICE, and CDA and they compare. Following the introduction, panelists will debate how best to operationalize the guidance, what is still needed from a regulatory perspective, and what biopharma needs in terms of assurances from data providers to meet regulatory expectations. The panelists will provide two differing company approaches to dissecting and implementing FDA’s 7-step process for establishing and assessing the credibility of an AI model for a specific context of use and the challenges they have encountered. A key piece of the discussion will focus on assessing data quality for data generated through this approach. Panelists will also discuss the need for more information from regulatory authorities on how to best operationalize certain aspects of the guidances, how this scheme may conflict with existing regulatory schemes such as 21 CFR Part 11, and what is needed from an international convergence or harmonization perspective.
This session will equip HEOR professionals with multiple perspectives on how to navigate the technical and regulatory landscape of AI abstraction and curation approaches, ensuring that evidence generation strategies and HTA submissions create the best possible body of evidence.
Moderator
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Nicholaas Honig, JD
Highlander Health, Duxbury, MA, United States
Speakers
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Jolyon Fairburn-Beech
GSK, London, United Kingdom
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Nate Nussbaum, MD
Target RWE, Durham, NC, United States
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Dan Riskin, MBA, MD
Verantos, Inc., Menlo Park, CA, United States
Is There a Consensus on the Framework for Evaluating Artificial Intelligence (AI)-Assisted Systematic Review Tools in HEOR?
Session Type: Issue Panel
Topics: Methodological & Statistical Research, Health Technology Assessment
Track: AI
Level: Intermediate
Issue:
AI-assisted systematic literature reviews (AI-SLRs) have rapidly expanded, with dozens of commercial and open-source tools now available. However, the HEOR and HTA community lacks shared standards for evaluating tool performance, ensuring reproducibility, documenting risk, and benchmarking AI-SLR output against human-conducted reviews. As evidence synthesis teams increasingly adopt AI-SLRs for HEOR and HTA projects, a possible solution is to establish an evaluation framework from the perspectives of multiple stakeholders. A case competition (a.k.a. challenge) using AI-SLR tools could be used to test the common evaluation framework. This session will discuss the need for a common evaluation framework and a process to conduct the HEOR/HTA community-driven benchmarking challenge.
Overview:
This panel will bring together perspectives from ISPOR leadership, academia, AI methodology, and the pharmaceutical industry to co-create a path forward. An overview provided by Dr. Mullins will outline the current landscape and the role of ISPOR in shaping good-practice guidance for AI in evidence synthesis (5 min).
A senior evidence generation lead (Dr. Zhang) will share real-world insights on the challenges and opportunities of AI-SLR adoption, highlighting vendor assessment, validation requirements, compliance considerations, quality control, and the balance between efficiency gains and decision-grade reliability (15 min).
Dr. Shi will introduce the concept of case competitions, discussing the feasibility of shared reference datasets, “gold-standard” systematic reviews, and open evaluation protocols to support innovation and methodological rigor (10 min).
Dr. Yang will then present a structured framework for evaluating AI-SLR tools, covering reference standard construction, accuracy metrics, reproducibility, workload reduction, hallucination/error types, and governance considerations aligned with GenAI reporting expectations (15 min).
The session will conclude with interactive polling and collaborative consensus to identify priority actions, including whether HEOR/HTA communities should form a working group, issue guidance, or sponsor an AI-SLR challenge.
Moderator
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C. Daniel Mullins, PhD
University of Maryland School of Medicine, Baltimore, MD, United States
C. Daniel Mullins is a Professor at the University of Maryland School of Pharmacy. He is Founder and Executive Director of the University of Maryland PATient-centered Involvement in Evaluating effectiveNess of TreatmentS (PATIENTS) Program, a community-academic partnership for patient-driven research. Dr. Mullins has received approximately $25 million in funding as a Principal Investigator from AHRQ, FDA, NCI, NHLBI, NIA, NIMHD, the Patient-Centered Outcomes Research Institute (PCORI) and various patient advocacy organizations and pharmaceutical companies. At the University of Maryland Baltimore (UMB), he received the Dr. Patricia Sokolove Outstanding Mentor Award and the Dr. Martin Luther King Jr. Faculty Diversity Award. He was named Researcher of the Year at UMB and was awarded a University System of Maryland Wilson H. Elkins Professorship. At ISPOR, he has served as Editor-in-Chief of Value in Health since 2010 and received the Marilyn Dix Smith Leadership Award in 2017 and the Avedis Donabedian Lifetime Achievement Award in 2024.
Speakers
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Lizheng Shi, PhD
Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, United States
Lizheng Shi, PhD, MsPharm, MA, is the Neal A. and Mary Vanselow Endowed Chair in the Department of Health Policy and Management at the School of Public Health and Tropical Medicine of Tulane University. He is the founding director of Tulane’s Health Systems Analytics Research Center (HSARC). Dr. Shi’s current health services research interest focuses on innovative health technologies to improve healthcare quality, access, and cost of patient-centered care from the equity perspective, using pharmaco-economics, health technology assessment, health analytics, and policy evaluation. Dr. Shi is dedicated to disseminating and translating population health knowledge at the local, national, and international levels. He is the associate editor of Value In Health and co-editor in chief for Pharmacoeconomics and Policy.
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Yiduo Zhang, BA, MA, PhD
AstraZeneca, Gaithersburg, MD, United States
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Mei Yang, PhD
NouStarX, Short Hills, NJ, United States
Patient Experience Data as a Non-Negotiable: Can US Payers Afford to Stay Behind?
Session Type: Issue Panel
Topics: Patient-Centered Research, Health Technology Assessment, Economic Evaluation
Track: Access and Drug Pricing
Level: Intermediate
Issue
While patient experience data (PED) - including PROs, quality-of-life measures, treatment preferences, and patient-generated data - are central to evidence expectations in U.S. regulatory decisions, their use in payer decision-making remains inconsistent. The FDA’s Patient-Focused Drug Development (PFDD) Guidance Series and the European Medicines Agency draft Reflection Paper on PED signal that patient experience data are considered part of the totality of evidence required for regulatory and access decisions. European HTA bodies increasingly treat QoL and patient-relevant outcomes as core determinants of added benefit and price negotiation. In contrast, the use of PED in formulary and access decisions by payers remains variable, limited to PRO data and coverage exceptions.
Overview
The panel will explore 3 questions:
1. Why does PED matter now?
Panelists will discuss how PED strengthens clinical credibility, captures health outcomes beyond survival, and reflects elements of total cost of care such as functioning, productivity, and caregiver burden. Drawing on ISPOR Europe 2025 themes, the FDA PFDD Guidance Series, and the EMA PED Reflection Paper, the session will highlight expectations that PED be proactively incorporated into regulatory and reimbursement submissions.
2. Why hasn’t PED meaningfully influenced payer decisions?
Despite increasing availability of PROs and PED, analyses show limited uptake in coverage and utilization management. Panelists will address methodological uncertainty, lack of standardization, perceived operational burden, and the belief that PED does not materially influence comparative effectiveness.
3. What would it take to change the dynamic?
The discussion will identify practical actions for key stakeholders:
• Industry: embed fit-for-purpose PED in pivotal trials and real-world studies; develop concise, payer-ready evidence packages.
• Regulators/HTA bodies: clarify evidentiary standards; signal PED relevance beyond labeling; align approaches with EMA and FDA initiatives.
• Payers: define how PED could influence access thresholds and contracting; increase transparency when PED informs decisions.
Moderator
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Martin Rost, PhD
AESARA, Boca Raton, FL, United States
Speakers
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Brian O'Rourke, BSc, PharmD
Brian O'Rourke Health Care Consulting Inc., Ottawa, ON, Canada
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Robyn Carson, MPH
AbbVie, Morris Plains, NJ, United States
Robyn T. Carson, MPH, is Vice President & Head of Patient-Centered Outcomes Research and HEOR-Strategy Aesthetics where she leads teams focused on integrating the patient voice through generation of patient experience data (PED) and ensuring deployment of best practices for clinical outcome assessment (COA) development, validation, and implementation across therapeutic areas at AbbVie. Robyn has driven patient-centered research in the pharmaceutical industry for 19 years where she has held roles in of increasing responsibility at Pfizer, Forest Labs, Actavis, Allergan and AbbVie. During her career, Robyn has made significant contributions to major product approvals and launches, as well as the development of multiple novel patient-reported outcome (PRO) instruments and innovative real-world research platforms. In addition, Robyn has led key departmental and enterprise-wide initiatives related to patient-focused drug development (PFDD) and patient-centricity. Robyn has also been a leader within the cross-industry Critical Path Institute PRO Consortium since 2008, currently serving as the Industry Co-Director. Prior to joining the pharmaceutical industry, Robyn conducted research at Columbia University, NYC Department of Health & Mental Hygiene, and served as a Research Fellow at the National Cancer Institute. Robyn holds a MPH in Epidemiology from Columbia University.
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Denise Sánchez Palomo, MA, MS, JD
Opus Regulatory, New York, NY, United States
Evolving Approaches to Measuring Benefits in Economic Evaluation: Do the Health Economics Methods Advisory (HEMA) Recommendations Go Far Enough for Global HTA Practice?
Session Type: Issue Panel
Topics: Health Technology Assessment, Economic Evaluation, Methodological & Statistical Research
Track: Expanded Value Measures
Level: Intermediate
Purpose: The Health Economics Methods Advisory (HEMA) group recently released recommendations proposing updated approaches to defining and measuring benefits in economic evaluation. These recommendations respond to growing interest in broader value elements, alternative benefit metrics, and approaches that better capture patient and societal outcomes. However, questions remain about whether HEMA's recommendations sufficiently reflect the field’s expanding methodological frontier and the needs of HTA agencies operating in diverse policy environments.
Overview: This issue panel will examine the opportunities and limitations of the HEMA recommendations through a structured, multi-perspective debate. Dr. Padula will open the session with a brief overview (10 minutes) of the HEMA initiative and the international context for expanded value frameworks. Dr. Lakdawalla will assess the conceptual foundations of the proposals and their relationship to emerging economic methods. Dr. Ollendorf will discuss implementation challenges from an HTA practitioner’s perspective, while Dr. Steuten will evaluate the recommendations’ alignment with global HTA practice and consider whether they go far enough to accommodate novel value concepts. Each panelist will present for approximately 10 minutes, followed by a moderated exchange and audience discussion (20 minutes). The session will benefit HTA researchers, policymakers, payers, and methodologists seeking clarity on how evolving benefit-measurement approaches can be responsibly adopted in practice.
Moderator
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William V Padula, PhD
University of Southern California, Rancho Palos Verdes, CA, United States
Speakers
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Darius Lakdawalla, PhD
University of Southern California, Los Angeles, CA, United States
Darius Lakdawalla is a widely published, award-winning researcher and a leading authority on health economics and health policy. He holds the Quintiles Chair in Pharmaceutical Development and Regulatory Innovation at the University of Southern California, where he sits on the faculties of the School of Pharmacy, the Sol Price School of Public Policy, and the Leonard D. Schaeffer Center for Health Policy and Economics, one of the nation’s premier health policy research centers.
His academic research has focused primarily on the economics of risks to health, the value and determinants of medical innovation, the economics of health insurance markets, and the industrial organization of healthcare markets. Dr. Lakdawalla serves as associate editor at the Journal of Health Economics and has previously served in this role at the American Journal of Health Economics and the Review of Economics and Statistics. His academic work has appeared in leading peer-reviewed journals of economics, health policy, and medicine, including the American Economic Review, Quarterly Journal of Economics, Health Affairs, the Journal of Health Economics, and the New England Journal of Medicine. In addition, his work has been featured by prominent popular press outlets, such as the Wall Street Journal, National Public Radio, Forbes, and the New York Times. Dr. Lakdawalla has also received the PhRMA Foundation Value Assessment Challenge Award, designed to encourage innovative approaches to defining and measuring value in health care, in 2019 (third place) and 2020 (first place), along with the ISPOR Excellence in Research Methodology Award, the Garfield Prize, and the Milken Institute Award for Distinguished Economic Research.
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Dan Ollendorf, MPH, PhD
Institute for Clinical & Economic Review, Boston, MA, United States
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Lotte Steuten, MSc, PhD
Office of Health Economics, London, United Kingdom
Lotte Steuten, PhD Deputy Chief Executive of the Office of Health Economics; former Member, Board of Directors, ISPOR
Prof Lotte Steuten is deputy chief executive of the Office of Health Economics (OHE), the world’s oldest independent health economics research organization, based in London, UK, and a globally recognized expert in health economics and outcomes research (HEOR).
Her research addresses challenges in valuing and paying for innovative therapies, with the aim of achieving effective, accessible, affordable, and efficient healthcare for all. She has published over 150 peer-reviewed papers on topics including the value of novel treatments, diagnostics and prevention for a wide range of non-communicable and infectious diseases.
With 2 decades of experience across Europe, the United States, and Asia Pacific, she advises governments, industry, and other organizations worldwide. She is frequently sought by media and international stakeholders for expert commentary on HEOR, value assessment, health policy innovation, and evolution of health technology assessment globally.
Alongside her position at OHE, Prof Steuten is a visiting honorary professor at City St George’s, University of London. Prior to joining OHE, she held academic faculty positions at the Fred Hutch Cancer Research Center and the University of Washington in the United States. She earned her PhD (with honors) from Maastricht University in the Netherlands.
Metabolic Conditions: Clinical Outcomes in Real-World Studies
Session Type: Research Podiums
This session explores the metabolic revolution by shifting focus from simple weight loss to hard clinical endpoints through high-quality research. Utilizing target trial emulations and pragmatic randomized designs, these studies demonstrate how GLP-1 and SGLT2 therapies significantly reduce mortality and cardiovascular risk across Medicare and complex chronic disease populations.
Moderator
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Sandhya Mehta, MS, PhD
Celgene, Summit, NJ, United States
CLINICAL OUTCOMES OF TIRZEPATIDE VERSUS DULAGLUTIDE ON TYPE 2 DIABETES WITH OBESITY AND HEART FAILURE
OBJECTIVES: A prior study using real-world data found that tirzepatide conferred cardiovascular benefits for patients with type 2 diabetes mellitus (T2DM), obesity, and ischemic heart disease; however, its effects in patients with T2DM, obesity, and heart failure remain unexplored. Therefore, this study evaluated the effectiveness and safety of tirzepatide and dulaglutide in patients with T2DM, obesity, and heart failure in routine clinical practice, using real-world data.
METHODS: We conducted a target trial emulation using data from the TriNetX Global Collaborative Network (November 2022-November 2025). Adults aged ≥40 years with T2DM, defined by ICD-10 codes and HbA1c levels of ≥7.0% and ≤10.5%, obesity (BMI ≥25 kg/m²), and established heart failure were included. Outcomes of interest were all-cause mortality, hospitalization, and end-stage renal disease during a 36-month follow-up period after treatment initiation. Gastrointestinal (GI) symptoms were also evaluated as a safety outcome. Propensity score matching (1:1) was used to balance baseline characteristics between treatment groups. Cox proportional hazards models were used to estimate hazard ratios (HRs) with 95% confidence intervals (CIs). A sensitivity analysis was also performed for heart failure with preserved ejection fraction (HFpEF).
RESULTS: A total of 6,622 matched pairs of tirzepatide and dulaglutide users were identified. Compared to dulaglutide, tirzepatide was linked with significantly lower risks of all-cause mortality (HR 0.657; 95% CI 0.559-0.773), hospitalization (HR 0.862; 95% CI 0.808-0.919), and end-stage renal disease (HR 0.768; 95% CI 0.63,0.935). However, for gastrointestinal symptoms, tirzepatide showed a similar outcome to dulaglutide (HR 0.995; 96% CI 0.937-1.055). Similar results were observed for HFpEF.
CONCLUSIONS: In this real-world patient cohort with T2DM, obesity, and heart failure, tirzepatide showed improved clinical outcomes, such as reduced risks of all-cause mortality, hospitalization, and end-stage renal disease, with a safety profile comparable to dulaglutide.
COMPARATIVE EFFECTIVENESS OF GLP-1RA AND SGLT2I IN PATIENTS WITH DIABETIC KIDNEY DISEASE: A TARGET TRIAL EMULATION
OBJECTIVES: Diabetic kidney disease (DKD) represents a major global health burden. The novel glucose-lowering therapies, particularly glucagon-like peptide-1 receptor agonists (GLP-1RA) and sodium-glucose cotransporter-2 inhibitors (SGLT2i), have transformed the therapeutic landscape by demonstrating significant cardiorenal protective effects beyond glycemic control. However, comparative cardiovascular benefits with long-term follow-up remain limited among patients with DKD in real-world practices. We aimed to compare GLP-1RA with SGLT2i for a composite cardiovascular outcome.
METHODS: We conducted a target trial emulation using the largest electronic medical records database from seven hospitals in Taiwan. We included patients with type 2 diabetes and an estimated glomerular filtration rate (eGFR) of less than 60 mL/min/1.73 m². Patients newly receiving GLP-1RA or SGLT2i were included between January 2016 and December 2021. A composite major adverse cardiovascular event included myocardial infarction, stroke, cardiovascular death, and hospitalization for heart failure. We followed each patient until the occurrence of MACEs, loss of follow-up, or June 30, 2025, whichever came first. Inverse probability of treatment weighting (IPTW) by propensity score was applied to make baseline balance.
RESULTS: Among 9,951 eligible patients, 1,747 initiated GLP-1RA therapy, and 5,233 initiated SGLT2i therapy. After IPTW, baseline characteristics were comparable, with a mean age of 67.7 years and a mean eGFR level of 44.3 mL/min/1.73 m². With a mean follow-up of 4.2 years, SGLT2i (HR 0.85, 95% CI: 0.79-0.90) were associated with significantly lower risk of MACEs compared with GLP-1RA based on intention-to-treatment analysis. SGLT2i also shows better clinical benefits in individual MACE events. Sensitivity analyses, including propensity score matching and alternative definitions of MACE, yield consistent results.
CONCLUSIONS: Our findings indicate that SGLT2i provide substantial cardiovascular benefits in patients with DKD. Further study is warranted to confirm our results.
REAL-WORLD COMPARATIVE EFFECTIVENESS OF SEMAGLUTIDE 2.4 MG VERSUS OTHER COMMERCIALLY AVAILABLE MEDICATIONS FOR CHRONIC WEIGHT MANAGEMENT IN ADULTS WITH OBESITY IN THE UNITED STATES: A PRAGMATIC CLINICAL STUDY
OBJECTIVES: To demonstrate the real-world comparative effectiveness of once-weekly subcutaneous semaglutide 2.4 mg versus other commercially available anti-obesity medications (AOMs) on body weight reduction in adults with obesity in a multiple-employer US setting.
METHODS: This was a 52-week, randomized, open-label, parallel-group, active comparator-controlled, pragmatic study (NCT05579249). Participants were aged ≥18 years, had body mass index ≥30.0 kg/m2, were employed at Loma Linda University or Inland Empire Health Plan, and had no history of type 1 or type 2 diabetes mellitus. Following the investigators’ decision to initiate treatment for chronic weight management, participants were randomized 1:1 to semaglutide 2.4 mg or other AOMs. The primary endpoint was ≥10% body weight reduction. Secondary confirmatory endpoints were change in body weight and physical function measured by the Impact of Weight on Quality of Life-Lite Clinical Trials Version (IWQOL-Lite-CT). Results are presented for the treatment policy estimand, which assesses treatment effects regardless of adherence.
RESULTS: Of 565 screened participants, 500 were randomized and 311 (62.2%) completed treatment (semaglutide 2.4 mg, n=176 [70.4%]; other AOMs, n=135 [54.0%]). The most common other AOMs were liraglutide (58.3%) and phentermine/topiramate (39.7%). A significantly greater proportion of participants treated with semaglutide 2.4 mg (63.8%) achieved body weight reduction ≥10% at week 52 versus other AOMs (34.5%; odds ratio, 3.2 [95% CI: 2.1, 4.8]; P<0.0001). Mean change in body weight was significantly greater with semaglutide 2.4 mg (−11.9%) versus other AOMs (−6.3%; estimated treatment difference [ETD], −5.6% [−7.2%, −4.0%]; P<0.0001). Slightly greater improvements in IWQOL-Lite-CT physical function score were observed with semaglutide 2.4 mg versus other AOMs (23.0 vs 19.0 points) but this difference was not significant (ETD, 4.0 [−2.3, 10.2]; P=0.2126). Safety and tolerability were consistent with the established profile of semaglutide.
CONCLUSIONS: These findings demonstrate real-world effectiveness of semaglutide 2.4 mg comparable to that observed in phase 3 randomized controlled trials.
REAL-WORLD EFFECTIVENESS OF ANTI-OBESITY PHARMACOTHERAPY IN MEDICARE: INTEGRATED 100% FEE-FOR-SERVICE CLAIMS AND EMR ANALYSIS OF BMI REDUCTION AND CARDIOVASCULAR OUTCOMES
OBJECTIVES: Modern anti‑obesity pharmacotherapy vs non‑pharmacologic management among 100% CMS Medicare Fee‑for‑Service (FFS) beneficiaries with obesity was evaluated, focusing on BMI change and cardiovascular (CV) risk markers/tests using claims linked with laboratory results and EMR.
METHODS: Columbia Data Analytics’ Medicare-Enhanced Lab & Demographics (MELDTM) dataset was used to conduct retrospective analysis of beneficiaries with obesity (baseline BMI≥30kg/m²) 2021-2024. Claims were deterministically linked to laboratory results and EMR (serial BMI, CV-related tests). Among several million beneficiaries, 420,000 had continuous enrollment and ≥2 BMI and CV measurements. Of these, 125,000 initiated anti‑obesity medication (treatment group); 295,000 received lifestyle counseling without medication (non‑treatment group). Two-year outcomes: BMI change; systolic/diastolic BP; LDL/HDL cholesterol; triglycerides; HbA1c; new abnormal stress tests, left ventricular ejection fraction (LVEF) change, incident MACE. Inverse probability of treatment weighting and multivariable regression adjusted for demographics, baseline BMI, comorbidities, prior CV disease.
RESULTS: Baseline mean (SD) BMI=37.2kg/m² (5.1) (treatment), 36.9kg/m² (5.3) (non‑treatment); 68% female, 72% had hypertension, 64% dyslipidemia, and 48% diabetes. Two-year adjusted mean BMI decreased 6.2kg/m² (treatment; 16.3% mean weight loss) vs 1.4kg/m² (4.1% weight loss) (non‑treatment; between‑group difference −4.8kg/m², p<0.001). Mean systolic BP declined 8.1mmHg vs 3.0mmHg, respectively (difference −5.1mmHg, p<0.001), diastolic BP by 3.1 vs 1.0mmHg (difference −2.1mmHg, p<0.01). LDL cholesterol decreased 19.5% vs 6.8%, respectively; HDL increased 5.2% vs 1.6%; triglycerides declined 21.3% vs 7.4% (all p<0.001). Among beneficiaries with diabetes, mean HbA1c declined 0.9 percentage points vs 0.3, respectively (p<0.001). New abnormal stress tests=7.8% vs 11.9%, respectively (adjusted risk ratio [ARR]=0.68, 95%CI=0.64-0.73), and worsening LVEF (≥50% to <50%) in 5.4% vs 8.7% (ARR=0.62, 95%CI=0.57-0.68). Over median 2.1 years, adjusted HR of MACE=0.78 (treatment; 95%CI=0.72-0.84) vs non‑treatment.
CONCLUSIONS: Anti‑obesity pharmacotherapy showed roughly four‑fold greater BMI reduction, 5-6mmHg greater systolic BP reduction, improved lipid/glycemic profiles, fewer abnormal CV test findings, and 22% lower MACE risk vs non‑treatment.
Integrating Equity Into HTA: Are Population Preferences Enough?
Session Type: Issue Panel
Topics: Health Technology Assessment, Economic Evaluation, Health Policy & Regulatory
Track: Expanded Value Measures
Level: Intermediate
Issue: Reducing health inequities requires prioritizing the health of those who are systematically disadvantaged. Equity-informative approaches to cost-effectiveness analysis (CEA), such as distributional CEA, assess equity impacts by weighting outcomes and opportunity costs of interventions across equity-relevant characteristics. These weights have been elicited through population surveys, often fielded online, under the assumption that in a tax-funded or insurance-based system, “the public” should decide the value of reducing health inequities. Yet, this seemingly democratic solution raises questions about whether these approaches are best suited to inform real-world decision making. In this issue panel we will discuss three challenges: representativeness, heterogeneity, and context. The use of online surveys may under-represent the preferences of those most disadvantaged and requires high literacy and numeracy. Results are heterogenous and sensitive to the allocation scenario, framing effects, survey design considerations, and individual characteristics. Finally, equity is context specific, and stakeholder priorities and political dynamics can shift across countries, health conditions, and equity dimensions. As decision contexts shift, the value ascribed to improving health equity may also shift, raising concerns that societal preferences elicited via online choice experiments misalign with real-world decisions. Taken together, these challenges highlight the need to clarify whose preferences should guide equity weighting in practice, and whether population-level surveys can meaningfully represent the priorities of those who experience the greatest health disadvantages. Overview: Following an introduction to equity preference research (Cadham), panelists will briefly present on the current state of elicitations in Canada (Iragorri) and the US (Slejko) with an eye towards the challenges outlined above. Kowal will then outline future directions for gathering preferences, focusing on subgroup definitions, sampling strategies, and ways to manage data gaps. Presentations will be followed by a 15-minute moderated discussion and 15-minute audience discussion.
Moderator
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Christopher Cadham
Fred Hutchinson Cancer Center, Seattle, WA, United States
Speakers
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Julia F. Slejko, PhD
University of Maryland Baltimore, Baltimore, MD, United States
Dr Julia F. Slejko is associate professor in the Department of Practice, Sciences, and Health Outcomes Research at the University of Maryland School of Pharmacy. She serves as co-director of the Patient-Driven Values in Healthcare Evaluation Center and as director of the Pharmaceutical Health Services Research Graduate Program.
Dr Slejko earned her BA in molecular, cellular, and developmental biology from the University of Colorado Boulder and her PhD with a focus on pharmacoeconomics from the University of Colorado School of Pharmacy Center for Pharmaceutical Outcomes Research. She completed postdoctoral training at the University of Washington School of Pharmacy. Prior to her doctoral training, she spent 7 years in drug discovery at Array BioPharma in Boulder, Colorado.
Her research focuses on real-world health economics and outcomes research, economic modeling applications, and patient-informed value assessment. Her recent projects included multistakeholder consensus on patient-centered value assessment and US public preference elicitation of health inequality aversion.
Dr Slejko is active in ISPOR, serving as co-lead of the Women in HEOR initiative, associate editor at Value in Health, and member of the Health Science Policy Council. She was co-chair of the Faculty Advisor Council 2023-2025.
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Nicolas Iragorri, MS
University of Toronto, Toronto, ON, Canada
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Stacey Kowal, BS, MSc
Genentech, Alameda, CA, United States
The Hows and Whys of Estimating Return on Investment (ROI) of HEOR to the Biopharmaceutical Industry
Session Type: Workshop
Topics: Economic Evaluation, Study Approaches
Level: Intermediate
Purpose: Health economics & outcomes research (HEOR) has become integral in the biopharmaceutical industry, yet its contributions to product success have rarely been quantified. This contrasts sharply with other components of biopharma spending, such as R&D and commercialization campaigns, in which measurement of financial impact and calculation of return on investment (ROI) are routine. The objective of this workshop is to describe the hows and whys of estimating the ROI of HEOR.
Description: Participants of this workshop will learn the opportunities and challenges associated with ROI estimation to inform decision making on projects in the HEOR, RWE, and market access domains. Chris Blanchette (moderator) will set the stage by providing an overview of the issues and showcasing non-financial metrics historically adopted by industry to demonstrate impact (10 minutes). David Thompson will describe the ROI estimation framework, which combines decision-analytic modeling techniques with expected Net Present Value (eNPV) calculations of project costs and product revenues accruing over time to assess the potential value of an HEOR project (16 minutes). Montserrat Vera-Llonch will describe criteria that can be used to select HEOR projects for ROI estimation, based on high degrees of: (1) topicality, those projects at the forefront of current methodology and policy discussions; (2) quantifiability, those projects for which impact is clearcut and estimable; and (3) applicability, those projects that comprise a significant share of internal HEOR budgets (12 minutes). Craig Roberts will describe why biopharma HEOR functions may or may not want to routinely assess project value and how doing so could impact budget allocation decisions (12 minutes). The workshop will culminate with an interactive session in which attendees will be asked to suggest and prioritize HEOR projects for ROI assessment based on the criteria introduced in the session (10 minutes).
Moderator
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Christopher M. Blanchette, MA, MBA, MSc, PhD
Novo Nordisk, Doylestown, PA, United States
Speakers
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David Thompson, PhD
Rubidoux Research LLC, Manchester, MA, United States
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Montserrat Vera-Llonch, MD MPH
Ionis Pharmaceuticals, Inc, Carlsbad, CA, United States
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Craig Roberts, MBA, PharmD
Merck & Co. Inc, North Wales, PA, United States
Evidence Synthesis Across Multiple Outcomes: Unlocking the Value of Multivariate Methods
Session Type: Workshop
Topics: Methodological & Statistical Research, Clinical Outcomes, Patient-Centered Research
Track: Expanded Value Measures
Level: Intermediate
PURPOSE: Traditional network meta-analyses (NMA) typically focus on single outcomes like progression-free survival, yet clinical decision-making inherently requires balancing multiple endpoints simultaneously. This workshop brings together diverse perspectives to discuss innovative methods and the promising potential of multivariate evidence synthesis. How can multivariate approaches bridge otherwise disconnected treatment networks allowing for broader treatment comparisons? Can we jointly synthesize progression-free and overall survival through multi-state modeling for improved economic modelling? Can multivariate methods enable a more patient-centered treatment ranking by considering efficacy and safety related outcomes simultaneously? There are challenges to overcome and we address the complexities of between-outcome and between-comparison correlations, how to leverage these correlations to improve the precision of treatment effect estimates, and how to provide more comprehensive evidence that better reflects the multifaceted nature of clinical decision-making.
DESCRIPTION: Attendees will gain practical insights into when and how to implement multivariate methods, understand their advantages over univariate analyses, and learn about emerging tools for the visualization of complex multi-outcome evidence. Dr. Williams will chair the session and begin by summarizing current practice (8 min). Dr. Campbell will then review how different multivariate NMA models can be used to bridge otherwise disconnected networks (15 min). Dr. Jansen will explain multi-state NMA of progression-free- and overall survival that is based on a Markov state-transition model where time-varying transition rates and relative treatment effects are modeled using aggregate-level data (15min). Finally, Dr. Chen will consider a new framework for PAtient-centered treatment ranking via Large-scale Multivariate NMA, termed as PALM (15 min). This workshop will engage attendees with real-time polling and structured discussion, leveraging the different perspectives of the panel to probe how multivariate methods can ultimately improve clinical decision-making.
Moderator
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Rhys Williams, PhD
BeOne Medicines Ltd, Las Vegas, NV, United States
Dr. Rhys Williams joined BeOne Medicines as the Vice President, Integrative Evidence Generation and Health Economics, Global Medical Affairs in February 2023. Previously, he was the Vice President, Health Economics and Outcomes Research at Sunovion Pharmaceuticals. Prior to that, Rhys was an Executive Director in Global Health Economics at Amgen, where he worked for fourteen years. He’s also worked at Aetna health plans, Pfizer, BMS, Janssen and Knoll. Rhys is a native of the UK and received his BS (honors) degree in Statistics from Aberystwyth University in Wales. He has two Masters Degrees in Mathematics and Applied Statistics from Tulane University and a Doctoral degree in Epidemiology from Boston University. Rhys has authored over 100 peer-reviewed publications which have appeared in New England Journal of Medicine, Journal of Clinical Oncology, Blood Cancer Journal and Archives of Internal Medicine, among others. He also serves as an ad hoc reviewer for the Journal of the American Medical Association, Stroke, Value in Health and Obesity Research.
Speakers
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Jeroen P Jansen, PhD
UCSF, San Francisco, CA, United States
Jeroen P. Jansen, PhD, is a methodologist working at the intersection of evidence synthesis, biostatistics, and health economics. He is an associate professor in the Department of Clinical Pharmacy in the School of Pharmacy at the University of California, San Francisco, and chief scientist, Health Economics & Outcomes Research at the Precision Medicine Group.
For the past 15 years, Dr. Jansen has worked on research to understand the clinical and economic value of healthcare interventions. His research has frequently been conducted in the context of health technology assessment (HTA) with a focus on comparative effectiveness and cost-effectiveness. Prompted by the challenges encountered in applied research projects, he has performed methodological research. Notable contributions are the development of novel statistical methods to overcome the typical challenges in model-based cost-effectiveness evaluations characterized by gaps in the evidence base and complex evidence structures. Furthermore, Dr. Jansen led initiatives to develop guidance for consumers and producers of network meta-analysis studies. He has promoted a more transparent and credible approach to model-based health economic evaluations and led the development of open-source simulation models to illustrate its feasibility.
Dr. Jansen has been involved in the ongoing development of an R software package to develop simulation models for health economic evaluations. His current research interests are the clinical and economic value of precision medicine, incorporating health disparities in health economic modeling studies, and statistical methods for evidence synthesis. He has published extensively in his areas of expertise and is widely cited. He is co-author of a textbook on network meta-analysis for decision-making and was associate editor for the Journal for Research Synthesis Methods. Dr. Jansen has a PhD in epidemiology from the Erasmus University in the Netherlands.
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Yong Chen
University of Pennsylvania, Philadelphia, PA, United States
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Harlan Campbell
Precision AQ, Rossland, BC, Canada
Value-Based Pricing for CMS Drug Price Negotiation: Mission Impossible?
Session Type: Issue Panel
Topics: Health Policy & Regulatory
Track: Access and Drug Pricing
Level: Intermediate
Issue/Overview:
The CMS Medicare Drug Price Negotiation Program has now completed two negotiation cycles. Although the statute directs CMS to consider comparative clinical effectiveness, unmet clinical need, R&D and production costs, and other factors, the translation of these considerations into final negotiated prices remains opaque. With recent methodological work by Li et al. (2025) Xie et al. (2025), both in Value in Health, and Neumann et al. (2025) in Health Affairs Forefront, there is an interest in whether value-based pricing could serve as a transparent and analytically rigorous foundation for CMS.
This issue panel will explore how negotiated prices might differ under value-based versus non–value-based approaches and examine the opportunities and challenges of integrating value assessment into CMS pricing decisions.
The panel will discuss the practical, methodological, and policy implications of using value-based pricing to inform CMS negotiations, including transparency, feasibility, data requirements, stakeholder acceptance, and potential impacts on innovation and access.
Moderator
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Peter Neumann, ScD
Tufts Medical Center, Boston, MA, United States
Speakers
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Feng Xie, PhD
McMaster University, Hamilton, ON, ON, Canada
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Sean D Sullivan, PhD
University of Washington, Seattle, WA, United States
Sean D. Sullivan, BScPharm, MSc, PhD, is Professor and Dean, School of Pharmacy. He holds a joint appointment as Professor of Health Services in the School of Public Health. He holds adjunct appointments in the School of Medicine, the Public Health Sciences Division at the Fred Hutchinson Cancer Research Center, and at the Kaiser Permanente Washington Health Research Institute. He completed training in pharmacy at Oregon State University in 1983, obtained a master’s degree at the University of Texas in 1986 and a PhD in health economics and policy at the University of California, Berkeley in 1992. Dr. Sullivan has authored more than 400 journal articles, book chapters, task force reports and organizational and governmental publications. In many of these writings, he has assessed the evidence and applications of medical technology in relation to coverage and reimbursement decisions. His research interests include technology assessment, medical decision-making, and economic evaluation of medical technology. He is past president of the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) and past chair of the Academy of Managed Care Pharmacy (AMCP) Executive Committee of the Format for Formulary Submissions – the United States evidence-based guidelines for formulary decision making. Dr. Sullivan served as a past member of the Medicare Evidence Development and Coverage Advisory Committee, a past member of the Regence Blue Shield and Premera Blue Cross P/T Committee, and the Chair of the Premera Blue Cross Value Assessment Committee. He is also on the editorial boards of Value in Health, PharmacoEconomics, Journal of Medical Economics, and the European Journal of Health Economics. He was awarded the 2014 Stephen G. Avey Lifetime Achievement Award from the Academy of Managed Care Pharmacy (AMCP) and the 2015 APhA Academy of Pharmaceutical Research Sciences (APRS) Research Achievement Award.
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Joshua Cohen, PhD
Tufts Medical Center, Boston, MA, United States
Next-Generation Methods: AI-Enabled Evidence Curation, Transparent Modeling, and HTA Readiness
Session Type: Research Podiums
This session highlights next-generation methods that integrate artificial intelligence into economic evaluation and HTA workflows while maintaining transparency and decision relevance. Presentations span benchmarking large language models for model input curation, human-governed agentic AI approaches to health economic modeling, and a systematic assessment of methodological gaps in evaluating the value of AI in healthcare. The session concludes with an applied case study demonstrating AI-assisted real-time evidence synthesis to support PICO development for European Joint Clinical Assessment. Together, these presentations illustrate how AI can enhance HTA processes when accompanied by appropriate methodological safeguards.
Moderator
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Stefan Walzer
MArS Market Access & Pricing Strategy GmbH, Germany
BENCHMARKING GENERATIVE AI TOOLS FOR COST-EFFECTIVENESS ANALYSIS (CEA) MODEL INPUT CURATION: A COMPARATIVE EVALUATION OF LARGE LANGUAGE MODELS
OBJECTIVES: Identifying high-quality parameter inputs for cost-effectiveness analysis (CEA)models is critical but time-consuming. However, the application of large language models (LLMs) in this context remains insufficiently evaluated. We aimed to assess the accuracy, transparency, and reproducibility of three LLMs in sourcing and documenting CEA model parameters from published literature.
METHODS: A structured evaluation of generative artificial intelligence tools (ChatGPT, Claude, Gemini) was conducted to assess their accuracy, transparency, and reproducibility in curating inputs for CEA models. Using a previously developed cost-effectiveness model in major depressive disorder as a reference framework, the ChatGPT, Claude, and Gemini LLMs were used to source five predefined model inputs using standardized prompts. Inputs included probabilities, utilities, and cost estimates relevant to the model’s structure and perspective. Outputs were scored by two reviewers independently using a rubric adapted from ELEVATE-GenAI, PALISADE, and CHEERS-AI across eight domains, including accuracy, transparency, and citation validity, with a max score of 12.
RESULTS: All three LLMs retrieved literature-based parameter estimates relevant to the predefined CEA framework. ChatGPT and Claude achieved the highest overall performance (10/12 points each), demonstrating strong accuracy, contextual relevance, and citation validity across most parameters. Gemini scored 9/12, with comparable relevance and efficiency but more limitations in completeness and reproducibility. Across models, minor performance deficits were driven by incomplete uncertainty reporting and occasional ambiguity in citation traceability rather than incorrect values. All three LLMs provided similar CEA outputs. All tools completed parameter retrieval within the predefined 10-minute efficiency threshold, suggesting meaningful time savings over manual literature search.
CONCLUSIONS: Generative AI tools demonstrate feasible and accurate performance with similar CEA outputs, supporting initial economic model development. While overall accuracy and relevance were high, variability in transparency, completeness, and reproducibility highlights the need for structured prompting and expert verification, particularly for reporting uncertainty and confirming citations.
OPENING THE BLACK BOX: A HUMAN-GOVERNED AGENTIC AI FRAMEWORK FOR HEALTH ECONOMIC MODELING
OBJECTIVES: The application of agentic AI in health economic modeling remains limited by concerns regarding transparency, reproducibility, and insufficient human oversight. We propose a human-governed framework that integrates multi-layer agents to enhance analytic efficiency while maintaining methodological control, evaluated for survival analysis with external real-world validation and model parameterization via AI-enabled evidence synthesis.
METHODS: We developed a five-layer, modular, agentic AI architecture that combines retrieval-augmented generation with deterministic statistical computation under explicit human governance. The framework comprises: (1) a MDP orchestrator defining model structure and analytic workflows in accordance with NICE guidance; (2) a data and evidence executor agent performing auditable tasks including real-world evidence synthesis, individual patient data reconstruction, and survival modeling; (3) a modeling and analysis agent executing the economic modeling including scenario analyses; (4) a validation and optimization agent evaluating outputs against statistical, clinical, and real-world plausibility criteria and refines model specifications; and (5) a reporting agent generating HTA-compliant documentation and visualizations. The KEYNOTE-024 trial was used to benchmark survival analysis and evidence-based parameterization workflows. Two human experts independently evaluated all critical checkpoints of agent-generated outputs.
RESULTS: The agentic framework achieved a 99.94% reduction in analysis time, completing survival analyses in 17 minutes with a total 2.5 hours completion including structured human validation, compared with a traditional 2-3 week workflow. Kaplan-Meier digitization closely matched published results, including 6-month OS for pembrolizumab (80.4% vs 80.2%) and chemotherapy (73.0% vs 72.4%). Reconstructed treatment effects were consistent with trial estimates (OS HR 0.61 vs 0.60; >95% CI overlap). The validator agent excluded 36 of 84 clinically implausible models, confirmed by experts. Survival extrapolations were externally validated against real-world data with consistency.
CONCLUSIONS: A human-governed agentic AI framework can markedly accelerate health economic modeling while maintaining transparency, reproducibility, and HTA-aligned methodological rigor.
ECONOMIC VALUE OF ARTIFICIAL INTELLIGENCE IN HEALTHCARE: A SYSTEMATIC REVIEW OF COST-EFFECTIVENESS ANALYSIS HIGHLIGHTING METHODOLOGICAL GAPS
OBJECTIVES: AI/ML are increasingly used in healthcare to enhance diagnosis, prognosis, treatment optimization, and resource allocation. Despite expanding clinical adoption, their economic value remains uncertain, and existing CEAs/CUAs vary substantially in rigor and transparency. This systematic review evaluates CEAs of AI/ML interventions versus conventional care and assesses methodological quality using CHEERS-AI and the Drummond checklist.
METHODS: Following PRISMA 2020 guidelines (PROSPERO CRD420250654972), we searched PubMed, Embase, and the Cochrane Library through February 2025 for peer-reviewed CEAs/CUAs of AI/ML interventions. Data on study characteristics, methods, reporting quality, and economic outcomes were extracted using adapted CHEERS-AI domains.
RESULTS: Thirty-four studies (2018-2025) met inclusion criteria, most of which were model-based economic evaluations (n=27), primarily using Markov or hybrid models; seven were trial-based. AI/ML interventions mainly targeted diagnosis or screening (n=26) and were typically implemented as add-on tools integrated into existing clinical workflows rather than as stand-alone systems (n=31). Among studies reporting incremental cost-effectiveness ratios (ICERs) (30/34), 27 studies found AI/ML interventions to be cost-effective under at least one analytic perspective or scenario, with dominance (lower costs with equal or greater effectiveness) reported in 18 studies. Assessment using the CHEERS-AI extension revealed substantial reporting gaps: no study modeled AI learning over time or reported population differences between training and deployment datasets (0/34), and reporting of AI/ML development, testing, and validation was heterogeneous and often incomplete. Drummond checklist assessments indicated moderate-to-high overall methodological quality, with consistent reporting of core economic evaluation elements but persistent gaps in productivity costing, discounting transparency, and selected uncertainty analyses.
CONCLUSIONS: AI/ML interventions are often cost-effective or dominant, but inconsistent reporting and poor adherence to key CHEERS-AI elements, especially learning over time and deployment population differences, limit confidence and policy relevance. Transparent, lifecycle-aware, and equity-sensitive CEAs are needed to inform reimbursement and implementation decisions.
LIVING SYSTEMATIC REVIEWS (LSRS) AND ARTIFICIAL INTELLIGENCE (AI) IN THE EUROPEAN JOINT CLINICAL ASSESSMENT (JCA) ERA: ALIGNMENT AND GAPS ACROSS PRISMA, COCHRANE, ISPOR, AND HEALTH TECHNOLOGY ASSESSMENT (HTA) GUIDANCE
OBJECTIVES: LSRs aim to provide the most up-to-date information required in a highly dynamic landscape of pharmaceutical and clinical research. AI technologies can improve the speed and quality of LSRs; however, a clear methodological framework for their use is lacking. We evaluated whether existing methodological and HTA guidance address LSRs and AI-assisted LSRs conduct, reporting, and use in HTA and JCA.
METHODS: A structured review of publicly available guidance was conducted across six sources: PRISMA (PRISMA 2020, PRISMA-LSR extension, PRISMA-trAIce), Cochrane Handbook and LSR guidance, RAISE, ISPOR Good Practices and publications, NICE methods manuals, and JCA scoping guidance. Each document was reviewed for explicit guidance on: update frequency, versioning, study mapping, governance of changing inclusion/exclusion criteria, AI use (screening, extraction, synthesis), transparency/auditability, and PICO-stratified outputs. Findings were summarized quantitatively.
RESULTS: Across 14 distinct guidance documents, 50% explicitly defined or endorsed LSRs, but only 2 specified operational update mechanisms beyond periodic updates (for example continuous surveillance). None provide recommendations for daily/real-time updating. Guidance on AI use for systematic reviews was identified in 8/14 of documents; none presented clear, auditable requirements for model validation, performance variations, or traceability of AI decisions. Rules for managing multiple publications of the same study were partially addressed in 50% of documents, but without formal processes for grouping and documenting publications of the same study-family. Only one document discussed governance of evolving inclusion/exclusion criteria in response to new evidence. JCA guidance mandates PICO-specific reporting, yet there were no clear recommendations on dynamically re-synthesizing evidence by PICO as evidence changes.
CONCLUSIONS: Current guidance treats LSRs and AI-enabled systematic reviews as separate concepts, resulting in fragmented standards. Existing frameworks do not adequately support real-time LSRs aligned with JCA PICO requirements. An extension to PRISMA-LSR (“PRISMA-LSR+”) is needed to formalize real-time updating, study-family management, AI transparency, and dynamic PICO-based reporting.
10:30 AM - 1:30 PM
Poster Session 1
Session Type: Research Posters
Poster Tours 11:45AM–12:30PM | Presenters will be with their posters from 12:30PM–1:30PM
11:30 AM - 12:00 PM
Unlocking the Power of Mortality Data in Real-World Evidence: Overcoming Barriers and Driving Innovation
Session Type: Fast Facts
Topics: Real World Data & Information Systems, Methodological & Statistical Research, Study Approaches
Track: Real-World Evidence (RWE)
Level: Intermediate
This session explores the critical role of mortality data within real world evidence (RWE), highlighting the challenges posed by fragmented sources, inconsistent reporting, limited granularity, and analytic biases. Expert panelists will discuss practical solutions—including data standardization, infrastructure modernization, advanced analytics, and collaborative data sharing—to strengthen the reliability and utility of mortality information in RWE. Attendees will gain actionable guidance on sourcing, evaluating, and integrating mortality data to enhance evidence generation for clinical, regulatory, and payer decision making.
Speakers
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Jason LaBonte, PhD
Claymont, DE, United States
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Phani Veeranki, MPH, DrPH, MD
Optum Life Sciences, CYPRESS, TX, United States
11:30 AM - 12:15 PM
HEOR Impact Cases Poster Tour
Session Type: HEOR Impact Cases
This tour will take place during Poster Session 1, Posters will be hung from 10:30 AM - 1:30 PM.
Oncology Poster Tour
Session Type: Research Posters
This tour will take place during Poster Session 1, Posters will be hung from 10:30 AM - 1:30 PM.
Posters featured in this tour:
PT1: RECEIPT OF SARS-COV2 MRNA VACCINE PRIOR TO IMMUNE CHECKPOINT INHIBITOR THERAPY ASSOCIATED WITH SIGNIFICANTLY IMPROVED OVERALL SURVIVAL ACROSS MULTIPLE METASTATIC CANCERS: RESULTS FROM A REAL-WORLD EVIDENCE STUDY
PT2: EVIDENCE-BASED PICO MAPPING FOR EU JOINT CLINICAL ASSESSMENT (JCA) USING A REAL-TIME AI-ASSISTEDLIVINGSYSTEMATIC LITERATURE REVIEW (REAL-SLR): AN ADVANCED NON-SMALL CELL LUNG CANCER (NSCLC) CASE STUDY
PT3: ENHANCING REAL-WORLD DATA (RWD) QUALITY: IMPLEMENTATION OF REGULATORY DATA QUALITY FRAMEWORK WITHIN A LARGE US ONCOLOGY ELECTRONIC HEALTH RECORD (EHR)-DERIVED DATABASE
PT4: INTEGRATING MEDICINES AND MEDICAL SERVICES IN REAL-WORLD VALUE ASSESSMENT: EVIDENCE FROM SUBCUTANEOUS ONCOLOGY FORMULATIONS IN A DAY CARE SETTING
PT5: REAL WORLD HEALTHCARE RESOURCE UTILIZATION AND COSTS IN METASTATIC COLORECTAL CANCER (MCRC) PATIENTS BY LINE OF THERAPY IN THE UNITED STATES
PT6: TARGETED THERAPY, IMMUNOTHERAPY, AND MOLECULAR TESTING IN ADVANCED SOLID TUMORS: A 2021-2025 MEDICARE ANALYSIS
11:30 AM - 1:15 PM
Lunch Service (Exhibit Hall)
Session Type: General Meeting
As you enjoy your lunch in the Poster and Exhibit Hall, seize the opportunity to engage in meaningful conversations with fellow attendees. Take this time to exchange ideas, forge new partnerships, or simply enjoy casual conversations.
12:15 PM - 1:15 PM
Transforming HEOR with Artificial Intelligence and Real-World Data
Session Type: Educational Symposia
Topics: Real World Data & Information Systems, Methodological & Statistical Research
Level: Intermediate
AI is rapidly transforming healthcare research. Initially applied to automate routine analytical tasks, artificial intelligence is increasingly being explored for its potential to support evidence generation and healthcare decision-making.
In HEOR, AI may support new approaches to analyzing real-world health data, examining patient experiences, and evaluating treatment outcomes. . By strengthening the analysis of large and complex datasets, has the potential to contribute to more scalable and timely evidence generation across the therapy lifecycle.
This symposium will examine how modern AI technologies are applied to generate real-world evidence (RWE) from early development through post-launch evaluation. Speakers will share practical examples of AI in economic modeling, data organization and extraction, advanced analytics, and the integration of patient-reported outcomes while preserving their nuance and integrity. The session will discuss how these approaches are being explored in practice and the methodological considerations associated with their implementation.
The session will also address key considerations for responsible implementation. Discussion will focus on where may offer meaningful analytical contributions, where expert oversight remains essential, and where methodologies continue to evolve. Emphasis will be placed on transparency, reproducibility, validation, and governance as foundations for trustworthy AI-enabled research.
The symposium will conclude with a forward-looking discussion on how emerging approaches involving large language models, agent-based AI systems, and real-world data are being explored in areas such as digital twins and synthetic data generation The discussion will consider the potential implications of these developments for evidence generation, patient-centered research, value assessment, and healthcare decision-making, including applications such as personalized outcome simulation, continuously updating economic models, synthetic comparator construction, adaptive reimbursement strategies, and AI-assisted analytical workflows that may support evolving approaches to real-world evidence studies.
Living HTA in the Age of AI Innovation: Supporting HTA Decisions at the Speed of Evolving Evidence
Session Type: Forums
Topics: Health Technology Assessment
Track: Access and Drug Pricing
Level: Intermediate
Health systems worldwide are navigating an era defined by rapid scientific innovation, rising uncertainty, and increasing pressure to deliver affordable and equitable care. Traditional Health Technology Assessment (HTA), primarily implemented as one-time evaluation of new health technologies. This process often falls short in supporting timely and iterative decision-making as evidence, technologies and system contexts evolve.
Living HTA reimagines HTA as a dynamic process by offering a systematic, ongoing assessment that captures the evolving nature of the evidence base, the technology itself or the dynamic context in which health technologies are adopted leading to an update of the linked recommendation, when needed.
This interactive forum, hosted by the ISPOR Living HTA Working Group (WG), will present the WG’s shared definition of Living HTA and key findings from ongoing reviews conducted across the HTA landscape. The session will stimulate discussion by encouraging audience participation on the following topics:
• What approaches enable continuous and dynamic HTA processes?
• Which methodological and technological advances may support the operationalization of Living HTA?
• How may the operationalization of Living HTA differ between higher resourced and lower resourced settings?
The goal of this session is to generate multi-stakeholders’ informed insights that will help refine the building blocks of a Living HTA approach and shape the next phase of the WG’s deliverables.
Moderator
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Grammati Sarri, MSc, PhD
Cytel, London, United Kingdom
Speakers
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Seye Abogunrin, MPH, MSc, MD
Roche, Basel, Switzerland
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Dalia Dawoud, BSc, MSc, PhD
Cytel Inc., London, United Kingdom
Dalia Dawoud, PhD, is Research Principal, HTA Policy and Strategy. She is also the Director and CEO of PEHTA Consulting Ltd. and holds a professor position at the Faculty of Pharmacy, Cairo University. She has over 15 years experience as a health economist and researcher. Her work is largely focused on the application of HEOR in HTA and clinical guideline development. She worked at leading organizations including NICE, where she led a portfolio of HORIZON Europe projects such as HTx, EDiHTA and SUSTAIN HTA, and the Royal College of Physicians, London. She is widely published in the areas of health economics and outcomes research and serves as associate editor for Value in Health and as director on ISPOR Board of Directors (2023-2026). She is also a member of the ISPOR AI Working Group and ISPOR Living HTA Working Group.
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Hector E Castro Jaramillo, MSc, PhD, MD
Health-R LLC, Arlington, VA, United States
The Enduring Challenge of Medical Device Identification in Real-World Data: Is Artificial Intelligence Abstraction Ready for Broad Use and Acceptance?
Session Type: Forums
Topics: Real World Data & Information Systems, Medical Technologies, Patient-Centered Research
Track: Real-World Evidence (RWE)
Level: Introductory
A challenge to generating real-world evidence for medical devices and diagnostics (MDD) is the ability to identify unique MDD products in real-world data. Device specific information, which is not readily available in structured claims data, is typically manually abstracted from unstructured data such as medical charts and physician notes, before being placed into a database for research. This process is lengthy, costly, and can lead to inaccuracies in data capture. Artificial intelligence (AI) methods, such as natural language processing (NLP) and machine learning (ML), have been shown to be a potential solution to this challenge. These methods can lead to fit-for-purpose curated databases that can be used for generating real-world evidence that may meet the needs of regulators, payers, and other healthcare decision makers. AI methods have the potential to identify MDD products within unstructured data and create structured databases that provide information not only on the device of interest, but also on comparators, patient characteristics, and outcomes. The panel will discuss the challenges and opportunities associated with these techniques, including current practice, reliability and validity, and chances of acceptance by regulators and payers. Panel members will discuss use cases from their own experiences. Each speaker will present their perspective for 15 minutes with an additional 15 minutes reserved for audience questions facilitated by the moderator towards the end of the session. Individuals interested in the challenges in extracting unique MDD product and patient data from real world data would benefit from attending.
Moderator
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Belinda A Mohr, PhD
Medtronic, Phoenix, AZ, United States
Speakers
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Abimbola Williams
United States
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Lisa Weiss, MPH, PhD
Stieber Health Consulting, LLC, NEW YORK, NY, United States
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Jimmy Royer, BA, MA, PhD
Analysis Group, Montreal, QC, Canada
Dr. Royer applies a broad range of AI and GenAI tools to address client needs in data science and HEOR. His recent work includes using AI models to predict treatment resistance and the potential future onset of rare or undiagnosed conditions. In addition, Dr. Royer has conducted extensive academic research and coauthored books and papers on using neural networks to predict treatment resistance in tuberculosis, using new AI advances in HEOR, using machine learning algorithms in propensity score models, and determining the impact of hypertension therapies on mortality, among other topics.
Advancing Patient Experience Data to Strengthen Patient-Centered Real-World Evidence
Session Type: Forums
Topics: Patient-Centered Research, Real World Data & Information Systems, Study Approaches
Track: Real-World Evidence (RWE)
Level: Introductory
As real-world evidence (RWE) continues to play an increasingly central role in healthcare decision making, there is growing recognition that patient experience data (PED) should be more systematically and meaningfully integrated to ensure RWD and evidence generation reflect what matters most to patients. PED cannot be fully understood or responsibly applied without intentional and sustained patient engagement (PE) across the research lifecycle. Without PE, PED risks being incomplete, misinterpreted, or disconnected from lived experience.
Despite the overall positive trend in the increasing use of both terms (PE and PED) across regulatory and health technology assessment (HTA) contexts, practical challenges remain in aligning PED with RWE methods, standards, and use cases. Many RWD studies continue to prioritize clinical and administrative data while underutilizing PED, limiting the relevance and impact of RWE for patients.
Building on recent methodological advances, regulatory developments from EMA and FDA emphasizing the importance of incorporating PED, and insights from the ISPOR Global Patient Representatives Meeting, this session will highlight how PED can strengthen the relevance, credibility, and usability of RWE for healthcare decision making. Panelists will discuss current gaps and challenges incorporating PED into RWE, emerging frameworks for meaningful patient involvement, and case examples and practical approaches for how PED has informed RWE.
By centering patient engagement as foundational to PED, this forum aims to promote more transparent, patient-centered, and globally applicable RWE. An interactive discussion with the audience will help inform the development of additional guidance, frameworks, and tools to advance shared understanding of more patient-centered RWE. This Forum will be presented on behalf of the ISPOR Patient Council.
Moderator
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Alan Balch, MS, PhD
Patient Advocate Foundation and National Patient Advocate Foundation, Hampton, VA, United States
Dr. Balch has more than 22 years of executive leadership in the non-profit sector spanning multiple advocacy areas including access and affordability, health equity, prevention and early detection, and cancer research. He became the CEO of both PAF and NPAF in 2013 and has served as a member of both Boards of Directors since 2007. From 2006-2013, he served as Vice President of the Preventive Health Partnership -- a national health promotion collaboration between the American Cancer Society, American Diabetes Association, and American Heart Association. Dr. Balch currently serves on dozens of selective boards, steering committees, and councils for an array of institutions. Most recently, Dr. Balch was selected as the Chair of the Global Patient Council for the American Patient Representatives Roundtable for the Professional Society for Health Economics and Outcomes Research (ISPOR) after serving as the Co-Chair of the North American Patient Representatives Roundtable.
Dr. Balch recently stepped into the role of Editor-in-Chief of Journal of Clinical Pathways. He has served on the editorial board and as a contributing editor for many years and on the advisory board for the Journal of Oncology Navigation and Survivorship. He is frequently invited to peer review article submissions to various publications including the Journal of Health Care for the Poor and Underserved, Journal of Clinical Oncology, American Journal of Preventive Medicine, and the American Journal of Public Health.
He earned his PhD in 2003 from the University of California Santa Cruz, his master’s degree in 1997 from the University of Texas San Antonio; and his bachelor’s degree in 1994 from Trinity University in San Antonio
Speakers
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Elisabeth Oehrlein, MS, PhD
Applied Patient Experience, LLC, Washington, DC, United States
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Mehmet Burcu, BA, MSc, PhD
Merck, Bel Air, MD, United States
Building Your HEOR Skillset: Core Skills for Advancing Your Career
Session Type: Forums
Topics: Organizational Practices
Track: Professional Development
Level: Introductory
Purpose: To explore strategies for influencing without authority in Health Economics and Outcomes Research (HEOR), to highlight the critical role of professional networks, and to provide tips to strengthen skills that will enable HEOR professionals to drive impact across various organizations and beyond.
Description: HEOR individual contributors have the ability to shape perceptions and guide behaviors that are essential for advancing evidence-based decisions. Influencing without authority begins by leveraging networks to build coalitions and align stakeholders around shared goals. Professional success also requires negotiation and persuasion skills to shift perspectives and secure commitment to new ways of thinking. Communicating the value of HEOR in clear and compelling terms, while speaking the language of business, ensures findings resonate with senior leaders and align with organizational priorities. Finally, adaptability allows professionals to remain effective in an environment of constant change, characterized by evolving markets, shifting policies, and competing demands. The new winning combination for HEOR professionals is deep technical expertise paired with a flexible, adaptive mindset that embraces change and drives impact.
This session will begin with an introduction to the concept of influencing without authority in HEOR (10 minutes, Abhijit). This will be followed by building and utilizing professional networks to extend reach and credibility (10 minutes, David). Strategies for applying negotiation and sales skills to change perceptions and behaviors will then be reviewed (10 minutes, Grace). Insights on mapping stakeholders and tailoring influence strategies to different roles including Medical, Access, and Commercial will follow (10 minutes, Haijun). The session will conclude with demonstrating adaptability to remain impactful in dynamic contexts (10 minutes, Min). Then questions to the panel, an audience Q&A, summary, and conclusion of the panel will follow (10 minutes, Abhijit).
Moderator
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Abhijit Gadkari
Novartis, East Hanover, NJ, United States
Speakers
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David Bruhn, MBA, PharmD
Otsuka, San Diego, CA, United States
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Grace E Fox
OPEN Health, New York, NY, United States
Grace Fox, PhD is an Associate Director in Strategic Market Access based in the United States. Her expertise includes evidence synthesis, pricing and reimbursement, and value communications. Grace has experience across multiple therapeutic areas, including cardiology, dermatology, infectiology, nephrology, neurology, oncology, psychiatry, and rheumatology, and brings expertise in global regulatory and health technology assessment submissions.
Prior to joining OPEN Health, Grace worked within PRECISIONheor to lead evidence synthesis activities to support global regulatory and health technology assessment submissions. Before transitioning to a consulting role, Grace led evidence synthesis projects at the Institute for Clinical and Economic Review. Previous to that, Grace leveraged evidence and analytics to create strategies for value-based formulary management at GHX.
Grace earned a PhD in Neuroscience from the Medical College of Georgia, where she developed a protocol for 512-channel neural recording, discovered an algorithm that enables intelligence, and investigated the neurobiology of anxiety disorders and depression.
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Haijun Tian, PhD
Eli Lilly, Chatham, NJ, United States
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Min Yang, MS, PhD, MD
Analysis Group, Boston, MA, United States
12:45 PM - 1:15 PM
The Global Pricing Pendulum: Value Assessment, and the Future of Pharmaceutical Innovation in A World Driven by Trade Incentives
Session Type: Fast Facts
Topics: Health Technology Assessment, Clinical Outcomes, Health Policy & Regulatory
Track: Access and Drug Pricing
Level: Intermediate
The session will begin with a brief overview of the evolving global health policy landscape, highlighting how recent changes in the U.S. and internationally may reshape the role of Europe, Japan, and Canada in pharmaceutical R&D and innovative launches, while increasingly treating medicines as tradable goods rather than products assessed through HTA frameworks. A moderated discussion will then explore the challenges of generating evidence in fragmented regulatory environments, the strategic balance between pricing optimization and value creation, and the impact of uncertainty on capital allocation and market prioritization. The session will feature perspectives from pharma experts and conclude with audience engagement on how these forces may shape the future of pharmaceutical innovation, affordability, and patient access.
Moderator
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Cristina Masseria
Aesara, Madrid, Spain
Speakers
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Gergana Zlateva, PhD
Pfizer Inc., New York, NY, United States
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Neal Masia, PhD
EntityRisk, Inc., Princeton, NJ, United States
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Diane Munch, PhD, MD
Pfizer Inc, New York, NY, United States
Beyond the Claim: What Your Real-World Evidence (RWE) May Be Missing Without Retail Pharmacy Data
Session Type: Exhibit Hall Theaters
Topics: Real World Data & Information Systems
Level: Intermediate
In this session, we will cover the practical fundamentals and evidentiary gains of incorporating retail pharmacy data into your real-world evidence (RWE) pipeline:
- Hidden Patient Therapies: Integrating retail pharmacy fill data provides visibility into critical aspects of patient behavior that traditional medical and pharmacy claims often miss. These data reveal adherence gaps and patient reliance on cash payments to cover medication costs — transactions that typically do not appear in standard claims feeds. They also expose mid-therapy switches that occur within the pharmacy workflow and may never be reflected in payer-submitted claims.
- Care Path Visibility: Retail pharmacy data also trace the broader journey from the physician’s initial prescription to the patient’s final fill and pickup. This care pathway visibility helps uncover where friction occurs — whether in prescribing, dispensing or patient follow-through.
- Unique Data: Elements specifically captured at the pharmacy counter, such as real-time pickup behavior, partial fills and pharmacist-patient interactions, offer deeper insights into medication utilization patterns. These insights support a more accurate understanding of adherence, persistence, and therapy uptake.
- Earlier Identification: Retail pharmacy data enable earlier identification of eligible patients for patient-reported outcomes (PRO) studies. Capturing activity before the first dose is dispensed; these data make it possible to reach out to patients proactively — often during the critical pre-initiation period — ensuring timely engagement before therapy begins.
1:45 PM - 2:45 PM
Use of Agentic AI to Create Health Economic Models in Both R and Excel
Session Type: Workshop
Topics: Methodological & Statistical Research
Track: AI
Level: Intermediate
Purpose
Health economic models are designed to forecast health and cost outcomes associated with a specific treatment in a particular disease area. Technical specifications for such a model must be sufficiently detailed to serve as a blueprint for model programming. From the blueprint, the model can be implemented in Excel or coded in R. We will demonstrate how to leverage agentic AI to go from model concept to full implementation in both R and Excel.
Description
Workshop attendees will get working knowledge on the use of agentic AI to generate both the blueprint and the implemented economic model. The workshop will show how AI, with human in the loop, is used for the blueprint development and then for implementation. A detailed example in autoimmune disease will be used throughout. Participants will also receive a link to a site from where they can download the Excel engine, templates and the full example.
[Jaime] will moderate the session, introducing the problem and guiding the active participation from the audience. [Brian] will describe the humans’ role in conceptualizing the model and introduce the autoimmune disease example. [Baris] will explain how a multi-agentic AI system with structured prompting can be used to develop, review and edit the specifications based on a modelling paper to generate the blueprint and then how a complementary agentic system can generate the corresponding R code, run analysis and develop the technical report. Then [Apoorva] will show how the same blueprint can be used with a general Excel template to create the spreadsheet version of the same model. [Jaime] will then lead the interaction with the participants, aided by probing questions and polling.
This workshop will be valuable to researchers interested in leveraging agentic AI to create health economic models. The methodology of structured prompting with automated templates also can help with many other research tasks in the HEOR space.
Moderator
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J. Jaime Caro, MD
Thermo Fisher Scientific, Lincoln, MA, United States
Speakers
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Brian Reddy, BA, MSc, PhD
Pfizer, Dublin, Ireland
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Baris Deniz, MSc
AIde Solutions, Chapel Hill, NC, United States
Baris Deniz is a seasoned expert in Health Economics and Outcomes Research (HEOR) and market access, with over 20 years of experience. His expertise spans integrated evidence strategies, health economic evaluations, evidence synthesis, and technology assessments. Baris has a deep understanding of the strategic role HEOR plays in bridging regulatory approvals with patient access, while generating robust evidence to demonstrate the value of medical interventions. Recently, his work has been in exploring innovative technologies and their applications in the HEOR domain to drive more effective outcomes and data-driven decision-making. He is the founder of AIde Solutions LLC, which focuses on leveraging GenAI in HEOR and scientific research.
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Apoorva Ambavane, MPH
Thermo Fisher Scientific, Dubai, United Arab Emirates
Bridging Evidence and Affordability
Session Type: Research Podiums
This session addresses how healthcare systems navigate the intersection of clinical value, cost, and evidence requirements to shape pharmaceutical access and reimbursement. Featured studies highlight policy interventions, affordability trends, and evidence frameworks that influence medication use, illustrating contemporary challenges in balancing timely access, patient financial burden, and value-based decision-making across diverse healthcare settings.
Moderator
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Yifei Liu, BS, MS, PhD
The University of Missouri-Kansas City School of Pharmacy, Kansas City, MO, United States
EFFECTS OF INSULIN COPAYMENT CAPS AND COINSURANCE ON USE, ADHERENCE, AND OUT-OF-POCKET SPENDING IN THE UNITED STATES: A SYSTEMATIC REVIEW
OBJECTIVES: To systematically review recent U.S. evidence on the effects of insulin copayment caps and coinsurance levels on insulin use, medication adherence, out-of-pocket (OOP) spending, and healthcare utilization among adults with diabetes.
METHODS: We conducted a systematic review following PRISMA 2020 guidelines. MEDLINE, Embase, Web of Science, and the Cochrane Library were searched for studies published between January 2020 and November 2025. Eligible studies included observational and quasi-experimental designs, such as difference-in-differences and pre-post analyses with comparison groups, that evaluated insulin cost-sharing policies. Two reviewers independently screened studies, extracted data using standardized templates, and assessed risk of bias using ROBINS-I. Findings were synthesized narratively following SWiM guidance and stratified by outcome domain, insurance type, and policy context.
RESULTS: Fourteen studies met inclusion criteria from 1,981 identified records. Most studies employed quasi-experimental designs and large administrative claims or nationally representative survey data, with sample sizes ranging from tens of thousands of beneficiaries to national populations of insulin users. Twelve studies (86%) reported statistically significant reductions in insulin-related OOP spending following implementation of copayment caps or reduced coinsurance, with several studies documenting relative reductions exceeding 20%. Nine studies (64%) reported increases in insulin prescription fills, days’ supply, or adherence measures such as proportion of days covered, with improvements most consistently observed among Medicare beneficiaries and commercially insured populations subject to state or federal caps. Evidence on healthcare utilization was mixed: five studies reported reductions in diabetes-related hospitalizations or emergency department visits, while others found no significant short-term changes. Overall risk of bias was assessed as low to moderate, with stronger internal validity among quasi-experimental studies.
CONCLUSIONS: Insulin cost-sharing reductions are consistently associated with lower patient OOP spending and modest but meaningful improvements in insulin use and adherence, while short-term effects on healthcare utilization remain heterogeneous.
LIFE COURSE TRAJECTORIES OF ANTI-CANCER DRUGS THROUGH THE NATIONAL DRUG PRICE NEGOTIATION IN CHINA
OBJECTIVES: Studies on the global medical insurance access have largely focused on static assessments of negotiation outcomes. This study aims to identify typical patterns and influencing factors within the dynamic life trajectory of anti-cancer drugs, from marketing authorization to inclusion in the National Reimbursement Drug List (NRDL).
METHODS: Anti-cancer drugs included in the 2025 negotiated drugs in China were selected. Data was obtained from Pharmcube and the Nation Healthcare Security Administration (NHSA) website. Descriptive statistical analysis was used to summarize drug characteristics. Social Sequence Analysis was introduced to cluster the life course states of medical insurance admission, with sequence analysis and hierarchical clustering via the Sequenzo tool describing the life trajectory patterns. Regression analysis was employed to identify factors influencing life trajectories.
RESULTS: 118 anti-cancer drugs were analyzed, among which 110 were innovative drugs (93.22%) and 12 had orphan drug designation (10.17%), covering 45 tumour types. 85 listed drugs were approved through the Accelerated Drug Marketing Registration Procedures (ADMRPs). Trajectory patterns were labeled using three components: (i) the timing of marketing authorization (early/middle/late), (ii) the lag from authorization to formal review approval (short/long), and (iii) the lag from approval to NRDL listing (short/long). 229 drug-indication combinations were clustered, recognizing four typical patterns: Middle-Long-Long (marketing authorization - review lag - inclusion lag, n=26), Late-Short-Short (n=92), Early-Long-Short (n=27) and Middle-Short-Long (n=84). The trajectories were associated with multiple factors, including drug category (p=0.0163), age indication (p=0.0001), import status (imported vs. domestic) (p=0.0279), orphan drug designation (p=0.0279) and ADMRP status (p=0.0002).
CONCLUSIONS: This study maps 4 typical patterns for anti-cancer drugs following the negotiated admission in China, from the perspective of drug life cycle. The observed drug and regulatory characteristics relate to the listing speed, and support procedural optimization to shorten the lags displayed in heterogeneous delays before and after the formal review.
ROLE OF INTEGRATED REAL WORLD EVIDENCE AND PATIENT REPORTED OUTCOMES IN LIFECYCLE HTA
OBJECTIVES: Health technologies often launch amid uncertainty, making post‑launch evidence generation critical for payer and regulatory decisions. Lifecycle Health Technology Assessment (HTA) is an iterative approach that reassesses technology’s value over time, using real-world evidence (RWE) and stakeholder input. However, integration of RWE and patient‑reported outcomes (PROs) remain inconsistent. This study evaluated how major HTA agencies integrate RWE and PROs within lifecycle HTA processes to address post-launch uncertainty.
METHODS: Targeted review of publicly available appraisal and reassessment documents from NICE, HAS, CADTH, and ICER (2021-2025) was conducted. Evaluations were included if they demonstrated at least one lifecycle feature (managed-access or scheduled re‑evaluation, evidence‑update requirements), and documented RWE/PRO use. A standardized analytic matrix compared access frameworks, RWE source categories, PRO instrument presence, stopping rules, and cost‑effectiveness reassessment. Analyses were descriptive given heterogeneity; counts were reported.
RESULTS: Forty evaluations met inclusion criteria (NICE: 15, HAS: 12, CADTH: 6, ICER: 7), with 53% (n=21) targeting rare diseases. All evaluations incorporated PROs and utilized RWE sources to inform lifecycle assessments. Dominant RWE sources were clinical trial/extension data (n=17), registries (n=15), observational studies (n=14), and National Health Service datasets (n=11). Formal managed‑access frameworks appeared in 14/40 evaluations (primarily NICE: 12; HAS: 2). Cost‑effectiveness reassessments occurred in 18/40 (NICE: 8, ICER: 7, HAS: 3). Stopping/continuation rules were reported in 29/40. Patient/equity input was explicit in 33/40 evaluations. Cross‑agency comparisons showed NICE and ICER applied the structured lifecycle mechanisms (managed access and scheduled reassessment), while HAS emphasized stopping rules and registry follow‑up; CADTH combined conditional reimbursement with registry planning, and universal patient/clinician input.
CONCLUSIONS: Lifecycle integration of RWE and PROs is heterogeneous across HTA agencies. PROs were consistently incorporated, whereas RWE adoption varied markedly. NICE and ICER lead with formal managed-access and reassessment pathways; HAS and CADTH increasingly embed registry-based approaches for high-cost innovations. Harmonized post-launch evidence frameworks are essential for reducing uncertainty and supporting value-based decisions.
TRENDS IN OUT-OF-POCKET SPENDINGFOR MEDICATIONAMONG INDIVIDUALS WITH DIABETES: EVIDENCE FROM MEPS, 2013-2023
OBJECTIVES: Understanding trends in out-of-pocket (OOP) spending for diabetes care is essential for evaluating healthcare policies such as the Affordable Care Act (ACA) and Inflation Reduction Act (IRA). Despite rising drug prices, little is known about how OOP spending has changed over time or whether trends differ by insurance coverage and income.
METHODS: We used data from the Medical Expenditure Panel Survey (MEPS), a nationally representative survey of the U.S. civilian noninstitutionalized population. Annual total OOP spending among individuals with diabetes was measured in inflation-adjusted 2023 U.S. dollars. Survey-weighted generalized linear models were used to estimate linear trends in OOP spending over time, with calendar year specified as a continuous variable. Effect modification by insurance coverage (private, public, uninsured) and income category was assessed using interaction terms. All analyses accounted for the complex MEPS survey design.
RESULTS: Among individuals with diabetes, mean annual OOP spending declined substantially over the study period, from $814 (95% CI: $740-$887) in 2013 to $424 (95% CI: $368-$480) in 2023, corresponding to an average annual decrease of $38 (95% CI: −$44 to −$32). OOP spending declined significantly among privately insured ($44 per year; 95% CI: −$52 to −$37) and publicly insured individuals ($28 per year; 95% CI: −$36 to −$21). In contrast, no statistically significant trend was observed among uninsured individuals (annual change: $16; 95% CI: −$53 to $85). Declines in OOP spending were observed across all income categories.
CONCLUSIONS: Despite rising prices for newer diabetes therapies, average OOP spending among individuals with diabetes has declined substantially over time, driven primarily by reductions among privately and publicly insured populations. Uninsured individuals did not experience similar improvements, highlighting persistent disparities in financial burden.
Behavioral Phenotyping for Value Assessment: Trajectory and AI Approaches to Rethink Medication Adherence Measurement
Session Type: Issue Panel
Topics: Patient-Centered Research, Methodological & Statistical Research, Health Policy & Regulatory
Track: AI
Level: Intermediate
ISSUE: Value assessments of health technologies are increasingly incorporating medication adherence data. Yet these analyses often rely on static metrics, such as the proportion of days covered (PDC) or the medication possession ratio (MPR), typically applying an arbitrary 80% cutoff to classify patients as “adherent” or “nonadherent”. While simple and widely used, these metrics mask substantial heterogeneity in real-world medication taking behavior, including intermittent use, early discontinuation, or overuse. Relying on static measures risks can misestimate the true clinical and economic impact of nonadherence and undervalue adherence enhancing interventions. Newer approaches, such as group-based trajectory modeling (GBTM) and latent class mixed models, combined with artificial intelligence (AI) and machine-learning (ML) models offer a way to move from static thresholds to dynamic, pattern-based classifications of nonadherence. The purpose of this workshop is to examine how advanced trajectory- and AI/ML-based adherence measures can be appropriately defined, validated, and incorporated into value assessment, and to identify the conditions under which they add real decision value beyond traditional metrics and can be practically embedded into economic evaluations and broader value frameworks. OVERVIEW: This session explores why measuring adherence is a critical structural input in in the value assessment of health technologies. Dweeti Nayak will introduce the importance of adherence measurement in these contexts (5 minutes). Bijan Borah will compare the traditional static measures with emerging trajectory-based approaches and illustrate how they capture dynamic adherence patterns (15 minutes). Chao Cai will introduce latent mixed models and compare their performance with GBTM and unsupervised learning methods for classifying adherence behaviors (15 minutes). Tamas Agh will discuss the integration of AI/ML methods into adherence trajectory modeling and present a real-world case demonstration (15 minutes). The final 10 minutes will be dedicated to audience discussion and Q&A, facilitated through ISPOR’s polling tools to encourage active engagement.
Moderator
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Dweeti Nayak, MS
Precision Medicine Group, Jersey City, NJ, United States
Speakers
Global Readiness for the Next Wave of Biotech Innovation: How Development Economics and Regulatory Context Predict Whether North America, Europe, or Asia Will Lead
Session Type: Issue Panel
Topics: Health Policy & Regulatory, Health Technology Assessment, Medical Technologies
Level: Introductory
Purpose: Concerns about where biotech innovation will originate, scale, and mature are intensifying as global R&D activity expands. North America continues to dominate investment dollars and capital markets, but Asia has rapidly increased clinical trial activity and developer participation at a fraction of the cost, suggesting gains in development efficiency. Europe occupies an intermediate position shaped by regulatory harmonization, public financing, and evolving innovation incentives. These divergent trajectories raise important questions for HEOR and policy. From an HEOR perspective, it remains unclear whether lower-cost development environments translate into comparable regulatory success and clinical value. Specifically, to what extent do development economics and regulatory context predict a region’s ability to efficiently generate evidence, sustain innovative pipelines, and deliver long-term value to health systems? Addressing these questions is critical as governments, investors, and manufacturers seek to allocate resources efficiently while balancing innovation, quality, and access.
Overview: This multi-perspective panel will debate global readiness for the next wave of biotech innovation, grounded in HEOR principles. Padula will moderate the session and open with an overview of global biotech development trends, highlighting differences in investment intensity, evidence generation, and regulatory pathways across North America, Europe, and Asia (10 minutes). Panelists will each present for 10 minutes, offering data-driven, industry perspectives on regional strengths and limitations, and discuss whether lower-cost development environments translate into durable innovation and value creation, how cross-regional partnerships shape efficiency and risk, and whether these ecosystems retain advantages in regulatory success, market access, and reimbursement. The session will conclude with moderated exchange and audience discussion (20 minutes). This panel will benefit HEOR researchers, industry leaders, investors, and policymakers seeking to understand how development economics and regulatory environments shape the evolving geography of biotech innovation.
Moderator
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William V Padula, PhD
University of Southern California, Rancho Palos Verdes, CA, United States
Speakers
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Natalie Reid, MBA, MPH, PhD
Stage Analytics, Severna Park, MD, United States
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Andrew Lee, PhD
BridgeBio, San Francisco, CA, United States
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Michael Duffy, PhD
OrgaNova, Philadelphia, PA, United States
Whose Preferences Should Govern Health Technology Adoption? Debating the Foundations and the Future of Value Assessment
Session Type: Issue Panel
Topics: Health Technology Assessment, Economic Evaluation, Methodological & Statistical Research
Track: Expanded Value Measures
Level: Intermediate
Issue: At the center of health technology assessment (HTA) lies the question of whose preferences should drive decisions about health technology adoption. Should value assessment reflect the preferences of patients, premium- and tax-paying consumers, regulators, third-party payers, healthcare providers or some combination of these stakeholders? This question arises in a number of timely and difficult resource-allocation decisions, like how to manage soaring patient demand for anti-obesity medicines. It also underlies debates over whether to use so-called “novel” elements of value from the ISPOR “value flower,” the salience of patient-centered economic theories like Generalized Risk-Adjusted Cost-Effectiveness (GRACE), proper approaches for measuring health-related quality of life and equity, and the role of risk preferences in value assessment. Focusing on the preferences of patients and consumers supports the adoption of novel value elements and the incorporation of risk preferences into value assessment. In contrast, aligning HTA with the preferences of payers or regulators, or a notion of aggregate societal preferences, supports QALY-based decision making.
Overview: Goodman will introduce the debate over whose preferences matter most, and its implications for a variety of current debates over the ISPOR value flower, QALYs, GRACE, and other methodological questions (5 minutes). Lakdawalla will present the case for incorporating individual-level risk preferences into value assessment and argue why such approaches may better align with welfare economics and decision-making (10 minutes). Briggs will argue that healthcare decision making should be anchored in aggregate societal preferences, while critically examining where, and under what conditions, departures from this approach may be justified (10 minutes). Whittington will provide an inclusive perspective, outlining strengths and weaknesses of both approaches, and practical solutions for the consideration within HTA (10 minutes). The panel will then “negotiate” a preference realignment for technology adoption, followed by questions and critique from the audience (25 minutes).
Moderator
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Clifford Goodman, MS, PhD
Clifford Goodman LLC, Bethesda, MD, Canada
Speakers
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Darius Lakdawalla, PhD
University of Southern California, Los Angeles, CA, United States
Darius Lakdawalla is a widely published, award-winning researcher and a leading authority on health economics and health policy. He holds the Quintiles Chair in Pharmaceutical Development and Regulatory Innovation at the University of Southern California, where he sits on the faculties of the School of Pharmacy, the Sol Price School of Public Policy, and the Leonard D. Schaeffer Center for Health Policy and Economics, one of the nation’s premier health policy research centers.
His academic research has focused primarily on the economics of risks to health, the value and determinants of medical innovation, the economics of health insurance markets, and the industrial organization of healthcare markets. Dr. Lakdawalla serves as associate editor at the Journal of Health Economics and has previously served in this role at the American Journal of Health Economics and the Review of Economics and Statistics. His academic work has appeared in leading peer-reviewed journals of economics, health policy, and medicine, including the American Economic Review, Quarterly Journal of Economics, Health Affairs, the Journal of Health Economics, and the New England Journal of Medicine. In addition, his work has been featured by prominent popular press outlets, such as the Wall Street Journal, National Public Radio, Forbes, and the New York Times. Dr. Lakdawalla has also received the PhRMA Foundation Value Assessment Challenge Award, designed to encourage innovative approaches to defining and measuring value in health care, in 2019 (third place) and 2020 (first place), along with the ISPOR Excellence in Research Methodology Award, the Garfield Prize, and the Milken Institute Award for Distinguished Economic Research.
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Andrew Briggs, DPhil
London School of Hygiene & Tropical Medicine, London, United Kingdom
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Melanie D Whittington, MS, PhD
Leerink Center for Pharmacoeconomics, Boston, MA, United States
Melanie Whittington is the Managing Director and Head of the Leerink Center for Pharmacoeconomics where she leads pharmacoeconomic evaluations of in-development and recently approved pharmaceuticals and studies incentives for innovation. She is also a Senior Fellow at the Center for the Evaluation of Value and Risk in Health (CEVR) where she advises on CEVR projects related to value assessment, economic modeling, and CEVR databases.
Resolved That HEOR and RWE Scientists Should Actively Architect RWD vs. Be An End User of RWD: A Debate
Session Type: Issue Panel
Topics: Real World Data & Information Systems
Track: Real-World Evidence (RWE)
Level: Intermediate
PURPOSE:
The growing interest in incorporating real-world data (RWD) into regulatory and payer decision-making combined with expanding technical capabilities for generating RWD creates a dynamic data ecosystem. Against this backdrop, users of RWD must decide: are we practical consumers of the data or active architects? Based on the intended real world evidence (RWE) generation purpose, practical consumers of RWD curate, manipulate, and link available RWD sources while active architects shape RWD infrastructure and specifications. Although Health Economics and Outcomes Research (HEOR) and RWE professionals extensively use RWD, there is little discussion of which role to play, limiting our ability to navigate the changing ecosystem with intention.
Using a formal debate structure, speakers will explore implications for research, policy, industry, and patient outcomes, and identify actionable steps as we consider the strategic future of HEOR and RWE generation: Will we develop evidence using RWD as they are available to us or embrace the opportunity to actively architect RWD?
DESCRIPTION:
During this session, the speakers will present positions for and against the resolution that “HEOR and RWE scientists should actively architect RWD vs be an end user of RWD”. The active architect team (Aaron Kamauu and Mary Beth Ritchey) and practical consumer team (Sandipan Bhattacharjee and Ravinder Dhawan) will each deliver opening and rebuttal statements on two topics (40 mins). The session will include audience polls and an audience Q&A session (10 min). A final poll will determine the debate winner. Eberechukwu Onukwugha will introduce the session in context of the ISPOR-ISPE Data Specifications initiative, provide ground rules, facilitate the polls and Q&A, and summarize the discussion and next steps (10 min total). Attendees will gain a better understanding of the tradeoffs associated with each role and the implications for navigating the RWD ecosystem.
Moderator
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Eberechukwu Onukwugha, MSc, PhD
University of Maryland, Baltimore School of Pharmacy, Baltimore, MD, United States
Eberechukwu Onukwugha, PhD is a Professor in the Department of Practice, Sciences, and Health Outcomes Research and Executive Director of Pharmaceutical Research Computing at the University of Maryland School of Pharmacy. She received a Doctor of Philosophy in economics (concentration: econometrics) from Virginia Polytechnic Institute and State University (Virginia Tech). Dr. Onukwugha completed a two-year postdoctoral fellowship in pharmacoeconomics and health outcomes research at the University of Maryland School of Pharmacy. She was a recipient of the PhRMA Foundation’s Post-Doctoral Fellowship in health economics and outcomes research. Dr. Onukwugha’s research interests are in cost analysis, health disparities, and medical decision-making by individuals and institutions. She has approximately 20 years of experience conducting health economics and outcomes research using administrative medical and pharmacy claims, hospital discharge, and prospectively-collected data. Dr. Onukwugha has authored or co-authored over 140 peer-reviewed articles in health economics and outcomes research. She is an Editorial Board member for PharmacoEconomics and an Associate Editor for Ethnicity & Disease. Dr. Onukwugha serves as President, ISPOR Board of Directors, 2024-2025, and serves on the Maryland Prescription Drug Affordability Board.
Speakers
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Aaron Kamauu, MPH, MS, MD
Navidence, Inc., Bountiful, UT, United States
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Mary Beth Ritchey, MSPH, PhD
Med Tech Epi, LLC, Philadelphia, PA, United States
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Sandipan Bhattacharjee, MS, PhD
Bayer U.S. LLC, Belle Mead, NJ, United States
Advancing Real-World Evidence in FDA Regulatory Decision-Making
Session Type: Spotlight
Topics: Real World Data & Information Systems, Health Policy & Regulatory, Epidemiology & Public Health
Track: Real-World Evidence (RWE)
Level: Intermediate
Purpose: The FDA Center for Drug Evaluation and Research regulates drug products and has a program for the evaluation of real-world data (RWD) to generate real-world evidence (RWE) for regulatory decision-making. This workshop offers a forum for sharing key activities and accomplishments of FDA’s RWE program with ISPOR attendees. The session will showcase topics of broad interest to ISPOR membership, including recent approvals that involved RWE, FDA funded research projects, new Agency-level RWE initiatives, and ongoing efforts to advance RWE policy to support regulatory decision-making. This aligns with ISPOR’s interest in using RWE to inform healthcare decisions. Description: Workshop participants will learn how FDA determines whether RWD are fit-for-use, study designs provide adequate scientific evidence, and study conduct meets regulatory requirements. They will be able to summarize key messages from FDA RWE guidance documents and explain how FDA-supported RWE research projects have addressed gaps in knowledge to support medical product development. Dr Bradley will chair the session and provide a brief overview of RWE-related activities of the FDA RWE program. Drs. Rahman and Weissfeld will cover notable RWE-based product approvals, draft and final RWE guidance documents, and selected RWE-related demonstration projects. Prof. Shirley Wang will provide perspective as an FDA funded collaborator on efforts in advancing the use of RWE in regulatory decision making.
Moderator
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Marie Bradley
FDA, Silver Spring, MD, United States
Speakers
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Motiur Rahman, MS, PhD
US Food and Drug Administration, Silver Spring, MD, United States
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Joel Weissfeld, MPH, MD
US Food and Drug Administration, Silver Spring, MD, United States
About the Speaker: Dr. Joel Weissfeld is a Real-World Evidence Analyst in FDA's Office of Medical Policy, where he evaluates RWE submissions for regulatory decision-making. He previously served over 10 years as Senior Medical Officer in FDA's Office of Surveillance and Epidemiology, where he conducted the primary epidemiological reviews. Prior to joining FDA, Dr. Weissfeld spent 25 years in academic medicine at the University of Pittsburgh, where he was Associate Professor of Epidemiology and a member of the Cancer Institute. He has authored over 200 peer-reviewed publications and served as principal investigator on major NIH-funded studies, including the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. Dr. Weissfeld holds an MD from Johns Hopkins University and an MPH in Epidemiology from the University of Pittsburgh.
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Shirley Wang, PhD
Brigham & Women's Hospital, Harvard Medical School, Boston, MA, United States
Dr. Wang is an associate professor at Brigham and Women’s Hospital, Harvard Medical School and lead epidemiologist for the Food and Drug Administration's (FDA) Sentinel Innovation Center. She leads the Meta-Research in Pharmacoepidemiology program, with recent projects aimed at improving the transparency, reproducibility, and robustness of evidence from healthcare databases (www.repeatinitiative.org) and informing when and how real-world evidence studies can draw causal conclusions to inform regulatory or other healthcare decision-making (www.rctduplicate.org). She is currently PI on multiple NIH R01s and is also funded by FDA. Her methods work has received 3 awards from international societies.
Policy Evidence: Data-Driven Decision-Making for Policymaking
Session Type: Issue Panel
Topics: Health Policy & Regulatory, Study Approaches, Organizational Practices
Track: Real-World Evidence (RWE)
Level: Introductory
ISSUE: Healthcare systems around the world are experiencing unprecedented pressures, balancing budget and economic, capacity and infrastructure, and workforce pressures. Every decision made has downstream effects and tradeoffs on patient outcomes, short-term budgets, and/or longer term fiscal impact. The strategic use of real world data (RWD) and real world evidence (RWE) is essential for informed evidence-based policymaking. Industry and government collaboration is necessary to generate timely, credible evidence policy using RWD to improve health outcomes, enhance system sustainability, and benefit society.
OVERVIEW: This session will discuss the types of data policymakers are looking for, generating evidence targeting stakeholders who are contemplating policy change, and how policy evidence and complements traditional medical and HEOR studies, and the potential to advance the field of policy evidence.
Moderator
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Lisa B Feng, DrPH
Bristol Myers Squibb, Washington, DC, United States
Speakers
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Josh Trent, MA
Leavitt Partners, Washington, DC, United States
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Nirosha Lederer, PhD
AstraZeneca, Washington, DC, United States
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Liz Fowler, JD, PhD
Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
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Erin Trish, PhD
United States
Real-World Patient Voice at Scale: Can Social Media Listening Inform US Payer and Access Decisions?
Session Type: Issue Panel
Topics: Patient-Centered Research, Study Approaches
Track: Real-World Evidence (RWE)
Level: Introductory
Health plans and value assessment bodies increasingly recognise the importance of patient experience, yet conventional real-world data (claims, EHRs, registries) rarely capture treatment burden, stigma, or cost-related non-adherence in sufficient depth. In parallel, patients and caregivers openly discuss these topics in online communities and social media. This panel will debate whether, when, and how social media listening (SML) can move beyond “insight” to become decision-relevant real-world evidence for US payer and access strategy.
Panelists will explore methodological standards for SML (sampling, bias mitigation, validation), and how insights on discontinuation, switching, financial toxicity, and daily-life impact can complement traditional RWD and PRO data. A health plan or PBM perspective will consider what type of digital patient-voice evidence is credible enough to influence formulary or utilization-management discussions. An HEOR/RWE lead from industry will discuss practical use cases where SML shaped evidence generation plans, value messages, or payer engagements. A patient-community or digital-ethnography expert will highlight ethical considerations, representation of vulnerable groups, and how to avoid over-interpreting “loud voices.”
The panel will use short opening statements followed by moderated debate around three questions:
- What is the “minimum bar” for SML to be considered robust enough for payer dialogue?
- How should SML be integrated with PROs and RWD in economic models and value dossiers?
- In which therapeutic areas (e.g., oncology, rare diseases, chronic conditions) is SML most likely to change access strategy?
Real-time polling and audience questions will be used to surface areas of consensus vs controversy.
Moderator
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Dimple Dang, MA
MarksMan Healthcare Communications Private Limited, Hyderabad, India
She is the Co-Founder and Director at MarksMan Healthcare, helping pharmaceutical and healthcare organizations turn evidence into informed access and business decisions. She brings over 17 years of overall professional experience and more than nine years in healthcare consulting, strategy, and client engagement across HEOR, Real-World Evidence (RWE), and medical affairs.
Her work sits at the intersection of evidence, access, and strategy. She partners with pharma, biotech, and healthcare organizations to move from data generation to decision impact, ensuring evidence is commercially relevant, policy-aligned, and patient-centric.
With a strong business lens and relationship-first approach, she focuses on building long-term client partnerships, enabling repeat engagements, and shaping evidence strategies that support market access, pricing, reimbursement, and stakeholder engagement objectives.
Speakers
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Reina Natero, PharmD
CVS Health, Portland, OR, United States
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Shreekant Parasuraman, PharmD, PhD
Incyte, Wilmington, DE, United States
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Mukul Singhal, PhD
Johnson and Johnson, Horsham, PA, United States
Economic Evaluation of Vaccines: Methods, Equity and Policy Implications
Session Type: Research Podiums
This podium session brings together leading experts to explore how economic evaluation informs vaccine policy, pricing, and access decisions across diverse settings. Presentations will examine methodological advances and real-world applications of cost-effectiveness analysis, budget impact modeling, and value assessment in national immunization programs.
Topics include a comprehensive review of economic evaluations and value considerations shaping ACIP routine vaccine recommendations; empirical evidence on willingness to pay for childhood vaccination in Tanzania, highlighting equity implications; a cost-effectiveness and budget impact analysis of adjuvanted trivalent influenza vaccination for older adults in Argentina; and a scoping review of how indirect effects are incorporated into national vaccine evaluations and recommendations.
Together, these studies illustrate the evolving role of economic evidence in guiding vaccine prioritization, addressing affordability constraints, and integrating equity considerations into decision-making frameworks. Attendees will gain insights into methodological best practices, cross-country perspectives, and policy-relevant findings that can strengthen transparent and equitable immunization strategies.
Moderator
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Richard Chapman, MS, PhD
Innovation and Value Initiative, Alexandria, VA, United States
CONSIDERATION OF INDIRECT EFFECTS IN NATIONAL VACCINE EVALUATIONS AND RECOMMENDATIONS: A SCOPING REVIEW
OBJECTIVES: Guidance from the World Health Organization and other organizations recommends considering indirect effects, such as herd immunity, serotype replacement, and age shift, in vaccine value assessments. This scoping review examined whether and how indirect effects are considered in national vaccine evaluations and recommendations.
METHODS: Vaccine evaluation frameworks from seven national immunization technical advisory groups (NITAGs) were reviewed: US ACIP, UK JCVI, Canada NACI, Australia ATAGI, France CTV, Germany STIKO, and the Netherlands Health Council. Case studies of pneumococcal conjugate vaccine (PCV) and human papillomavirus (HPV) vaccine evaluations by the ACIP and JCVI were assessed. Supplementary searches in MEDLINE and Embase (July 2025) identified publications describing NITAG evaluation practices or perspectives related to indirect effects.
RESULTS: Two NITAGs (JCVI and CTV) did not publish formal evaluation frameworks. Although JCVI generally follows the methodological guidance from the National Institute for Health and Care Excellence for economic evaluation, it does not publish guidelines. Three NITAGs (ACIP, ATAGI, and STIKO) explicitly referenced indirect effects beyond herd immunity, including serotype replacement and age shift. NACI recommended considering positive and negative indirect effects, while the Netherlands Health Council treated herd effects primarily as vaccination goals rather than evaluation criteria. In case studies, ACIP documentation provided limited detail on indirect effects, which were typically addressed through economic evaluations. In contrast, JCVI meeting minutes documented extensive discussion of herd immunity, serotype replacement, and age shift across epidemiological, modeling, and decision-making contexts. Differences in publicly available source materials may explain this contrast. Among 19 studies identified in the supplementary searches, most mentioned indirect effects briefly, and none detailed how NITAGs quantified or weighted them in decision-making.
CONCLUSIONS: Although indirect effects are widely acknowledged, their evaluation in national vaccine decision-making remains inconsistent and methodologically underdeveloped. Clearer guidance on assessing indirect effects could improve cross-country comparability and support evidence generation.
ECONOMIC EVALUATIONS AND VALUE CONSIDERATIONS IN ACIP ROUTINE VACCINE RECOMMENDATIONS: A COMPREHENSIVE REVIEW
OBJECTIVES: To assess economic evaluations and value considerations in Advisory Committee on Immunization Practices (ACIP) recommendations for routine vaccines on the U.S. immunization schedule, specifically examining types of economic outcomes reported, gaps in value element inclusion, and variation in cost-effectiveness across vaccine recommendations.
METHODS: We identified all ACIP recommendations for routine vaccines as of January 1, 2025, excluding travel vaccines and non-routine population recommendations. Of 16 routine vaccines on the CDC schedule, 3 lacked cost-effectiveness analysis (CEA) data in their MMWR publications since 2006. The remaining 13 vaccines with CEA data comprised 17 ACIP recommendations with available economic evaluations, reflecting multiple recommendations per vaccine for different subpopulations and immunization scenarios. Using Claude 4.5 Sonnet (Anthropic), we extracted economic data from MMWR publications and cited CEAs through a Claude Project environment and standardized extraction criteria. We extracted cost-effectiveness ratios (cost per QALY, cost per life-year), incremental costs, health outcomes (infections/hospitalizations/deaths averted, QALYs/life-years gained), and productivity costs. Validation employed stratified random sampling for independent human verification, as well as using ChatGPT-5.2 (OpenAI) extraction for comparison with inter-rater reliability (IRR) assessed using Cohen's kappa and intraclass correlation coefficients.
RESULTS: Among 17 ACIP recommendations, economic evaluations reported cost per QALY in 100%, cost per life-year in 29%, and incremental costs in 100%. Infections averted were reported in 100%, hospitalizations averted in 82%, and deaths averted in 71%. QALYs gained were quantified in 88% and life-years gained in 24%. Productivity costs were explicitly quantified in 82% of evaluations. 53%, 59%, and 65% of recommendations were less than $100K, $150K, and $200K/QALY, respectively. IRR demonstrated substantial agreement (κ=0.94, 95% CI: 0.89-0.99).
CONCLUSIONS: This comprehensive review reveals substantial variation in completeness of economic evaluations across ACIP routine vaccine recommendations, with notable gaps in life-year metrics and intermediate health outcomes. These findings highlight opportunities to standardize economic reporting in vaccine policy recommendations.
COST-EFFECTIVENESS AND BUDGET IMPACT ANALYSIS OF THE TRIVALENT ADJUVANTED INFLUENZA VACCINE IN PEOPLE OVER 50 YEARS OF AGE FOR ARGENTINA
OBJECTIVES: Influenza affects millions of people worldwide, particularly adults aged 50-64 with comorbidities and those aged ≥ 65 years. Annual vaccination is the most effective strategy to prevent influenza-related complications. The adjuvanted trivalent influenza vaccine (aTIV) has demonstrated greater effectiveness compared to non-adjuvanted vaccines. This study evaluates the cost-effectiveness and budget impact of introducing aTIV for high-risk adults aged 50-64 years, alongside its use in adults aged ≥ 65 years from the perspective of the Argentine health system.
METHODS: A decision-analytic static model was developed to compare aTIV with standard-dose trivalent influenza vaccine (SD-TIV) over a single influenza season, considering a cohort of approximately 12 million. In addition, a 5-year budget impact analysis (BIA) was conducted under scenarios of progressive uptake: up to 40% coverage among high-risk adults aged 50-64 years, and an increase from 55% to 80% among adults aged ≥ 65 years. Model parameters were sourced from international literature, local sources, and expert consultations. Deterministic and probabilistic sensitivity analyses were performed.
RESULTS: Expanding aTIV compared to SD-TIV resulted in an incremental cost-effectiveness ratio of USD 5,999 per quality-adjusted life years (QALYs) gained, well below Argentina’s reference cost-effectiveness threshold (USD 11,059/QALY), corresponding to a gain of 1,489 QALYs at an incremental cost of USD 8.34 million. Although vaccine acquisition costs were higher, these were largely offset by avoided medical visits and hospitalizations. The BIA estimated that, under targeted adoption, average annual per-member-per-month costs would increase by only USD 0.0025, remaining below the Argentine moderate reference budget impact threshold (USD 0.0065).
CONCLUSIONS: Implementing aTIV in high-risk adults aged 50-64 years and adults aged ≥ 65 years would be both cost-effective and affordable for the health system in Argentina. These findings support the consolidation and potential expansion of current vaccination strategies to reduce influenza burden.
MOTHERS’ WILLINGNESS TO PAY FOR CHILDHOOD VACCINATION IN TANZANIA: EVIDENCE FROM A TWO-PART INTERVAL REGRESSION MODEL WITH EQUITY IMPLICATION
OBJECTIVES: This study elicited mothers’ willingness to pay (WTP) for routine childhood vaccination in Tanzania using double-bounded contingent valuation methods. WTP was analyzed using a two-part interval-censored regression model that accommodated left- and interval censoring and skewness in WTP data, while producing equity-relevant welfare measures.
METHODS: A cross-sectional cluster sample survey of 400 mothers from 4 rural districts in Tanzania was conducted from June-July 2024. Mothers were asked how much they would be willing to pay for each vaccination if they were no longer freely available. Using a two-part interval regression approach, we estimated the probability of strictly positive WTP (stage one) and the magnitude of WTP among payers (stage two). Conditional (among WTP-positive) and unconditional (population) mean WTP were estimated using parametric log-normal retransformations with Duan’s smearing correction and bootstrapped standard errors. Equity analysis involved comparisons of conditional and unconditional mean WTP across wealth quintiles.
RESULTS: Approximately 85% of respondents indicated a positive WTP. The conditional mean WTP among WTP-positive mothers was TSH 3608 (USD 1.34) (95% CI TSH 3107 - 4510) after applying Duan’s smearing correction (1 USD = 2685 TSH). Unconditional population-average WTP, accounting for zero WTP among a subset of mothers, was substantially lower: TSH 3237 (USD 1.21) (95% CI TSH 2536 - 3837). Both the probability of positive WTP and the unconditional WTP increased monotonically with wealth quintile, reflecting a pro-rich gradient.
CONCLUSIONS: Distinguishing between conditional and unconditional WTP reveals substantial equity implications for vaccination financing. While many mothers are willing to pay something for childhood vaccination, the population-level average WTP has a substantial wealth gradient. An introduction of user fees would need to be accompanied by targeted subsidies and exemption mechanisms to sustain high vaccination coverage in this setting.
2:45 PM - 3:15 PM
Coffee and Connect
Session Type: General Meeting
Head to the exhibit hall to connect with fellow attendees and exhibitors over a steaming cup of coffee.
3:15 PM - 4:15 PM
Translating Equity Goals Into Practical Methods, Evidence, and Decision Tools: Lessons From Global Practice. A Value in Health Regional Issues Forum
Session Type: Forums
Topics: Health Service Delivery & Process of Care, Health Technology Assessment, Methodological & Statistical Research
Level: Intermediate
Equity considerations are playing an increasingly prominent role in health technology assessment (HTA) and health economics and outcomes research, yet translating equity goals into practical methods, evidence, and decision tools remains challenging. This Forum highlights the recently published health equity themed section in Value in Health Regional Issues (VIHRI), while drawing connections to complementary methodological advances featured in a forthcoming issue of Value in Health (VIH). Together, these efforts illustrate how equity research is evolving from conceptual foundations to pragmatic applications across diverse health systems.
Moderated, Stacey Kowal and Manuel Espinoza, the session opens by summarizing what these equity-focused papers collectively show; where the field is moving; and how context, data, and decision systems shape what is possible. The Forum will showcase new research contributions demonstrating how equity methods are being applied in practice. Julia Slejko will present findings from recent research in VIH on eliciting inequality aversion in the United States, before highlighting companion work in VIHRI by Ricci and colleagues that provides practical guidance for adapting benefit trade-off exercises across settings. Together, these studies show how equity-relevant preferences can be measured in one context and localized, tested, and implemented in others.
Nancy Devlin will review work examining how the Australian Pharmaceutical Benefits Advisory Committee has incorporated equity into vaccine-listing decisions, showing that equity considerations are increasingly referenced but inconsistently applied, rarely quantified, and embedded in processes with limited transparency. Their evaluation framework offers a replicable approach for assessing how equity is reflected in decision making across HTA settings.
The session will include moderated audience discussion and Q&A, as well as brief updates on developments at VIHRI relevant to the ISPOR community.
Moderator
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Stacey Kowal, BS, MSc
Genentech, Alameda, CA, United States
Speakers
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Julia F. Slejko, PhD
University of Maryland Baltimore, Baltimore, MD, United States
Dr Julia F. Slejko is associate professor in the Department of Practice, Sciences, and Health Outcomes Research at the University of Maryland School of Pharmacy. She serves as co-director of the Patient-Driven Values in Healthcare Evaluation Center and as director of the Pharmaceutical Health Services Research Graduate Program.
Dr Slejko earned her BA in molecular, cellular, and developmental biology from the University of Colorado Boulder and her PhD with a focus on pharmacoeconomics from the University of Colorado School of Pharmacy Center for Pharmaceutical Outcomes Research. She completed postdoctoral training at the University of Washington School of Pharmacy. Prior to her doctoral training, she spent 7 years in drug discovery at Array BioPharma in Boulder, Colorado.
Her research focuses on real-world health economics and outcomes research, economic modeling applications, and patient-informed value assessment. Her recent projects included multistakeholder consensus on patient-centered value assessment and US public preference elicitation of health inequality aversion.
Dr Slejko is active in ISPOR, serving as co-lead of the Women in HEOR initiative, associate editor at Value in Health, and member of the Health Science Policy Council. She was co-chair of the Faculty Advisor Council 2023-2025.
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Nancy J Devlin, PhD
University of Melbourne, Melbourne, Australia
Nancy is Professor of Health Economics at the University of Melbourne and Editor-in-Chief at Value in Health. Her principal areas of research expertise are the measurement and valuation of patient reported health outcomes; the cost effectiveness thresholds used in making judgments about value for money in health care; and priority setting in health care.
Nancy has published >200 original peer reviewed journal articles on a wide range of empirical and theoretical topics in health economics, and is co-author of Economic Analysis in Health Care, a textbook on health economics widely used in the UK and elsewhere. In 2025 Nancy was named in the Stanford/Elsevier ‘top 2% scientists’. In 2024, she was ranked 3rd in the world’s ‘Highly Ranked Scholars’™ in Health Economics based on productivity, impact and research quality. Her work was highlighted in the UK’s NIHR 10-year anniversary report, which noted ‘The impact of her research is worldwide and highly significant in improving health and health care decision making’ . Her research, submitted as a case study to the UK’s 2014 REF exercise, was judged by the sub-panel as ‘demonstrating very considerable impact in terms of reach and significance' .
She was the lead investigator on QUOKKA, a multi-million dollar programme of research on health outcomes in children, funded by the Medical Research Future Fund (Australia) (2020 – 2025), results from which have been described as “…a huge leap forward for the field of health-related quality of life measurement in child health”
She is the elected Chair of the Board of the EuroQol Research Foundation (2020-2025), the European-based not for profit body that developed the EQ-5D, the world’s leading generic measure of patient reported outcomes. Nancy has also served as the 2019/20 elected international President of ISPOR, the peak international professional society for health economics and outcomes research.
Prior to joining the University of Melbourne in 2019, Nancy was Director of Research at the Office of Health Economics, London for ten years, leading the development of its research programme, culminating in OHE achieving Independent Research Organisation (IRO) status in 2019. Prior to OHE she was Professor of Economics at City University of London, where she held the positions of Head of the Economics Department and Dean of Social Sciences. She has 40 years of experience as a researcher and as an advisor to health care organisations, both in the public and private sectors, in the UK and internationally.
Collaborating With Patients to Define Digital Endpoints and Biomarkers That Truly Matter
Session Type: Forums
Topics: Medical Technologies, Clinical Outcomes, Patient-Centered Research
Level: Intermediate
Developing meaningful measures of patient health, function, and daily life is key to understanding the value of interventions and to ensure patient access. Contrary to traditional clinical trials where endpoints and biomarkers are collected at clinic visits, digital technologies enable passive real-time health data collection from wearables, smartphones, and other connected devices. While these technologies offer the opportunity to reflect outcomes more relevant to patients in their daily lives, issues such as equity in access, usability, and data privacy can also arise.
This forum will explore three perspectives on how digital technologies can be developed to represent outcomes which improve access. The process of clinical trial implementation and regulatory acceptance of digitally derived patient data will be provided by the first speaker. A medical device developer will cover issues related to enabling improved data capture, real-time monitoring, and continuous evaluation. Ultimately, the power of digital technologies relies on their meaningfulness to patients, which will be addressed from the lens of a patient/carer representative.
This session convenes experts from four Special Interest Groups (Digital Health, Medical Devices and Diagnostics, Clinical Outcome Assessment and Patient-Centered). Panelists will share experiences and offer solutions to align expectations of the promise of digital technologies to represent meaningful differences across regulatory, manufacturer, patient and payer perspectives.
Moderator
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Anita D Burrell, BA, MA, MBA
Anita Burrell Consulting LLC, Flemington, NJ, United States
Anita Burrell is a dynamic, dedicated professional with extensive knowledge of health economics and global market access for pharmaceutical products as well as a regular speaker in the industry.
Anita has led teams to success across a wide variety of roles and geographies. At Sanofi, she headed Global Health Economics, Worldwide Pricing and Reimbursement and was an R&D champion bringing Aubagio, the oral MS therapy, to market ahead of schedule. She has served on the HBA Board of Directors and led the ISPOR Special Interest Group for Digital Health
As a consultant Anita has helped companies to:
Understand market dynamics and payer behavior across many diseases including immunology, cardiovascular, oncology, hematology and endocrinology in the top 11 markets including Europe, Japan and the US
Design integrated evidence plans to demonstrate robust demonstration of product benefits for faster market uptake
Establish credibility for a Global Market Access Insights function through thought leadership, strategic vision and producing three product lines within 9 months
Understand the Global Evolution of the Biosimilar Market and prepare for the future implications in Europe and the United States
Anita holds a BA (Hons) Economics from the University of Stirling, an M.A. Economics from Dalhousie University, Nova Scotia, Canada, and an MBA from Kingston University, Surrey UK. She speaks French at an advanced level.
Speakers
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Bryan Bennett, BSc, PhD
Jazz Pharma, Berwick-upon-Tweed, United Kingdom
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Angie Botto-van Bemden, PhD
Musculoskeletal Research International, Holiday, FL, United States
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Arturo Cabra, BS, MSc
GE HealthCare, Miami, FL, United States
The Business of Evidence: HEOR for C-Suite Decision-Making
Session Type: Forums
Topics: Organizational Practices
Track: Professional Development
Level: Introductory
Purpose: To explore the business value of HEOR from a C-Suite perspective. To achieve this goal, the speakers will highlight strategies for communicating HEOR impact in executive settings and will share practical examples where HEOR clearly influenced decision making, organizational priorities, and market outcomes.
Description: HEOR leaders (managers of HEOR teams) are increasingly asked to convey value concepts to C-suite leaders and external audiences who may be less familiar with technical concepts. Executives often prioritize financial impact, strategic positioning, and shareholder value, which requires HEOR leaders to adapt their communication strategies. The session will focus on the language and framing necessary to connect HEOR to business initiatives, while emphasizing cross-functional collaboration across any organization.
The session will begin with an overview of the different perspectives and the importance of cross-departmental engagement to strengthen the business case for HEOR (10 minutes, Chris). This will be followed by how the C-suite views the value of HEOR (10 minutes, Jaime). Contextualizing HEOR findings for executives will then be reviewed (10 minutes, Tommy). Examples of HEOR creating business value will be presented (10 minutes, ALL). The session will conclude with aligning HEOR outputs with broader strategic imperatives to ensure resonance in boardroom discussions (10 minutes, Simu).
Then questions to the panel, an audience Q&A, summary, and conclusion of the panel that focuses on actionable strategies for translating HEOR into terms that internal executives and non-HEOR external audiences understand, thereby strengthening organizational understanding of HEOR and demonstrating the function as a critical driver of business value will occur (10 minutes, Chris).
Moderator
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Christopher M. Blanchette, MA, MBA, MSc, PhD
Novo Nordisk, Doylestown, PA, United States
Speakers
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Paulo Carita, DrPH
Sanofi, CHILLY MAZARIN, France
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Jaime Rubin Cahill, BA, MA, MPH
Vertex Pharmaceuticals, Inc., boston, MA, United States
Jaime Rubin Cahill, MA, MPH is the Vice President and Head of Health Economics and Outcomes Research (HEOR) at Vertex Pharmaceuticals. With 20 years of HEOR experience, Jaime has been involved in dozens of Health Technology Appraisal (HTA) submissions, most recently to gain market access for Vertex’s portfolio of cystic fibrosis (CF) medicines and gene editing technology for sickle disease and transfusion-dependent beta thalassemia and supported many initiatives to support access to Vertex’s portfolio in the United States. She has also led research activities that span across multiple disciplines within HEOR, with particular expertise in pharmacoeconomic modeling and evidence generation in rare disease. Prior to joining Vertex in 2012, Jaime held positions of increasing responsibility in HEOR consulting.
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Tommy Bramley, PhD
Cencora, Polk City, IA, United States
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Simu Thomas, MS, PhD
Alexion, Boston, MA, United States
HEOR at U.S. Federal Agencies: State of the Science
Session Type: Forums
Topics: Organizational Practices, Epidemiology & Public Health, Real World Data & Information Systems
Track: Professional Development
Level: Introductory
ISPOR stands firmly committed to advancing rigorous, transparent, and policy-relevant health economics and outcomes research (HEOR) and to strengthening its appropriate use across U.S. federal agencies. HEOR methods—including real-world evidence (RWE), pragmatic study designs, patient-centered evidence, and applied economic analysis—have matured rapidly and are increasingly visible in regulatory, public health, and coverage and payment contexts. Yet the pace and direction of HEOR integration varies across agencies, and external narratives often obscure how HEOR science is actually evolving within US federal institutions.
This session, co-moderated by Laura Pizzi, Chief Science Officer of ISPOR, and Peter J. Neumann, Chair-Elect of ISPOR’s Health Science & Policy Council, will convene senior experts representing diverse federal perspectives. Invited panelists include Donna Rivera (former FDA; real-world evidence and regulatory science), Kakoli Roy (Centers for Disease Control and Prevention; applied health economics), and Rachael Fleurence (former NIH, science policy and evidence governance).
Panelists will share their views about 1. what aspects of HEOR within the agencies are expanding, plateauing, or contracting; 2. where the greatest opportunities exist for HEOR researchers to contribute to high-quality, decision-relevant evidence through grant funding and/or job opportunities; and 3. how ISPOR can further support HEOR methods, workforce development, and effective evidence translation in these agencies.
Speakers
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Peter Neumann, ScD
Tufts Medical Center, Boston, MA, United States
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Laura Pizzi, MPH, PharmD
ISPOR, Lawrenceville, NJ, United States
Laura Pizzi is Chief Science Officer at ISPOR.
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Donna Rivera, MSc, PharmD
Canal Row Advisors, Washington, DC, United States
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Rachael Fleurence, MSc, PhD
Apodeixis Strategies, LLC, Boston, MA, United States
Rachael L. Fleurence, PhD, MSc, is the head of Evidence and AI Solutions, at Value Analytics Lab, a life sciences consultancy. A health economist by training, she previously served as senior advisor to Dr. Francis Collins at the National Institutes of Health, where she led a national initiative to eliminate Hepatitis C in the US. She also served as an advisor to the National Institute of Biomedical Imaging and Bioengineering (NIBIB), focusing on artificial intelligence and machine learning. Previously, Dr. Fleurence was a senior health policy advisor in the Biden-Harris White House and Senior Advisor to the NIH Director. She played a key role in the federal COVID-19 response, leading the “Say Yes! COVID Test” program and serving on White House pandemic policy groups. Prior to her federal service, she led the National Evaluation System for health Technology Coordinating Center (NESTcc) and PCORnet at PCORI and spent several years in the private sector in health economics and outcomes research (HEOR) consulting. Dr. Fleurence has received multiple NIH Director’s Awards, the HHS Secretary’s Award for Distinguished Service, and the National Champion for Global Hepatitis Elimination award. She co-led the ISPOR Task Force on EHR Data for Health Technology Assessment, serves on the ISPOR Working Group on Generative AI, and is an associate editor for Value in Health. She also sits on the boards of CTTI (the Clinical Trials Transformation Initiative) and ICN (the ImproveCareNow network). She holds degrees from Cambridge University, ESSEC Business School (Paris), and the University of York (UK).
Global Value Frameworks: Aligning HEOR, Access and Policy Across Borders
Session Type: Forums
Topics: Health Policy & Regulatory, Health Technology Assessment, Economic Evaluation
Track: Expanded Value Measures
Level: Introductory
In light of recently proposed US Executive Orders on (Most Favored Nation) MFN, this session will focus on potential intended and unintended consequences of its implementation on access HTA methods in the US and abroad. Attendees will gain a deeper understanding of how MFN policies may influence patient access, evidence generation, and HTA methods in the US and abroad.
MFN approaches aim to align US prices with those in peer countries, potentially improving affordability for patients and payers. Yet these policies carry broader ripple effects: changes in industry launch strategies, shifts in evidence expectations for HTA bodies, and downstream impacts on innovation incentives and global access. As health systems respond, variations in value assessment methods, including how willingness-to-pay (WTP) thresholds are defined and how broader elements of value are incorporated, will play a critical role in shaping future access pathways.
Speakers will review the development of WTP thresholds and introduce emerging approaches to value assessment that better account for elements of value traditionally overlooked, including what these methodological shifts mean for patients, particularly when decision-making includes or excludes certain dimensions of value.
Discussion will consider NICE’s recent updates to its WTP threshold and the introduction of the EQ-5D-5L value set: the motivations behind these changes and their broader implications for HTA practice in the UK and internationally.
Industry perspective on planning for patient access in a rapidly evolving global environment will include how manufacturers balance diverse pricing and HTA requirements while striving to address patient needs and maintain predictable, sustainable access strategies.
The session will conclude with a discussion on how coordinated value frameworks and enhanced cross-border collaboration can transform global access from a fragmented process into a more flexible yet reliable path for patients worldwide. Brought to you by the ISPOR Student Network. Open to all conference attendees.
Moderator
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Albert Truong, PharmD
Virginia Commonwealth University, Richmond, VA, United States
Speakers
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Dalia Dawoud, BSc, MSc, PhD
Cytel Inc., London, United Kingdom
Dalia Dawoud, PhD, is Research Principal, HTA Policy and Strategy. She is also the Director and CEO of PEHTA Consulting Ltd. and holds a professor position at the Faculty of Pharmacy, Cairo University. She has over 15 years experience as a health economist and researcher. Her work is largely focused on the application of HEOR in HTA and clinical guideline development. She worked at leading organizations including NICE, where she led a portfolio of HORIZON Europe projects such as HTx, EDiHTA and SUSTAIN HTA, and the Royal College of Physicians, London. She is widely published in the areas of health economics and outcomes research and serves as associate editor for Value in Health and as director on ISPOR Board of Directors (2023-2026). She is also a member of the ISPOR AI Working Group and ISPOR Living HTA Working Group.
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Stacey Hickson, PhD
Janssen Inc., Raritan, NJ, United States
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Stefan Walzer, MA, PhD
MArS Market Access & Pricing Strategy GmbH, Weil am Rhein, Germany
Prioritizing Your Mental Health and Wellness: Honing Your Secret Weapon
Session Type: Forums
Topics: Organizational Practices, Epidemiology & Public Health
Level: Introductory
Purpose: The purpose of the ISPOR 2026 Women in HEOR Forum is to feature an expert speaker on mental health and wellness, highlighting a priority area for ISPOR members from different sectors.
Description: The vision of the Women in HEOR initiative is to support the contribution of women in our field by serving as a catalyst for leadership and a platform for mentorship, collaboration, and networking. This Women in HEOR Forum will highlight a topic of interest raised by members: strategies for mental health and wellness. The forum speaker will highlight strategies to support mental and emotional well-being; resilience-building tools to succeed in challenging environments; work-life balance, and tools for navigating within the world around us.
Julia Slejko will introduce the session, including the objectives of the Women in HEOR initiative (10 minutes). A keynote speaker, including ISPOR members, will present on the aforementioned topics (25 minutes). Shelby Reed will moderate a discussion with the speaker. The final 15 minutes will engage the audience in Q&A, and live polling will be used throughout to elicit perspectives on the forum topics.
Moderator
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Shelby Reed, RPh, PhD
Duke Clinical Research Institute, Durham, NC, United States
4:00 PM - 4:45 PM
Methodology Research in HEOR Poster Tour
Session Type: Research Posters
This tour will take place during Poster Session 2, Posters will be hung from 4:00 PM - 7:00 PM.
Posters featured in this tour:
PT7: IMPACT OF VARIANCE IN COHORT PHENOTYPE DEFINITIONS ON REAL-WORLD RESEARCH: AN ASSESSMENT OF ATHEROSCLEROTIC CARDIOVASCULAR DISEASE (ASCVD) DEFINITIONS ON REAL-WORLD DATA
PT8: A CAUSAL MULTISTATE FRAMEWORK FOR TREATMENT SWITCHING IN NETWORK META-ANALYSES OF TIME-TO-EVENT OUTCOMES IN ONCOLOGY
PT9: REAL WORLD EVIDENCE METHODOLOGY FOR ECONOMIC EVALUATION OF CLINICAL AI: COST EFFECTIVENESS OF AN IMAGING ALGORITHM FOR INCIDENTAL DETECTION OF HEART FAILURE WITH PRESERVED EJECTION FRACTION
PT10: SENSITIVITY OF EXTERNAL CONTROL ARM ESTIMATES TO UNMEASURED CONFOUNDING STRUCTURE: A SIMULATION STUDY
PT11: QUANTIFYING TIME-VARYING MEDICATION REGIMEN COMPLEXITY USING A MACHINE-LEARNING-BASED PIPELINE IN PATIENTS WITH TYPE 2 DIABETES
PT12: A PILOT ASSESSMENT OF LLM-GENERATED SYNTHETIC COHORTS: A FIRST STEP TOWARD ROBUST SYNTHETIC CONTROL ARMS
Rare Disease Poster Tour
Session Type: Research Posters
This tour will take place during Poster Session 2, Posters will be hung from 4:00 PM - 7:00 PM.
Posters featured in this tour:
PT13: FACTORS ASSOCIATED WITH LONGITUDINAL TRAJECTORIES OF HYDROXYUREA ADHERENCE AMONG INDIVIDUALS WITH SICKLE CELL DISEASE: A GROUP-BASED TRAJECTORY MODELING STUDY
PT14: QUANTIFYING THE ECONOMIC BURDEN OF NEONATAL-ONSET ORNITHINETRANSCARBAMYLASEDEFICIENCY IN THE UNITED STATES
PT15: THE IMPACT OF CARING FOR THEIR CHILDREN WITH RETT SYNDROME: A MULTI-METHOD STUDY
PT16: REAL-WORLD HEALTHCARE RESOURCE UTILIZATION AND ECONOMIC BURDEN OF NARCOLEPSY TYPE 1 IN THE US
PT17: AN EFFECTIVE METHODOLOGICAL FRAMEWORK FOR EXECUTING MULTINATIONAL, PATIENT-CENTRED CROSS-SECTIONAL SURVEYS IN RARE DISEASES: FACILITATING EVIDENCE GENERATION WITH GENERALISABILITY ACROSS CONDITIONS TO SUPPORT COMMERCIAL VIABILITY
PT18: USE OF REAL-WORLD EVIDENCE IN PRE-APPROVAL ASSESSMENTS FOR RARE AND ULTRA-RARE DISEASE THERAPIES IN UK, GERMANY, FRANCE, AND THE UNITED STATES
4:00 PM - 7:00 PM
Poster Session 2
Session Type: Research Posters
Poster Tours 4:00PM–4:45PM | Presenters will be with their posters from 6:00PM–7:00PM
4:45 PM - 5:45 PM
The Metrics Behind the Money: Case Studies and Insights From Bridging Health Economics and Investment
Session Type: Workshop
Topics: Economic Evaluation, Health Technology Assessment, Organizational Practices
Track: Access and Drug Pricing
Level: Introductory
Purpose:
Despite sharing a similar goal to use resources efficiently to maximize returns for patients and society, health economics and health investment have historically operated as two different sectors. As the scrutiny over market-based mechanisms for drug pricing intensifies and as we enter one of the largest patent cliffs on record, the need for coordination of health economic expertise and health investment expertise is obvious.
This workshop will share real-world case studies and lessons learned from integrating health economic approaches within health investment strategy.
Participants will learn how health economic approaches can be integrated into healthcare investment strategies and how health economic studies can better reflect real-world investment decisions.
Description:
The workshop will be moderated by Dr. Whittington who will summarize the different objectives of health economics and health investment (5 mins). Dr. Li, health economist at an investment bank, will provide examples of how she has incorporated a health economic lens into equity research (5 mins). Dr. Xie, a health economist at a multi-stage investment management company, will describe using generalized cost-effectiveness analysis to communicate the societal value for a portfolio company prior to their acquisition (5 mins). Dr. VanSickle, a health economist at a healthcare investment firm, will explain how health economic principles are considered as part of due diligence and investment strategy (5 mins). Panelists will then participate in a fireside chat (20 mins) to discuss 1) the impacts of their efforts, 2) adaptations to health economic methods to align with investor strategy, 3) how and when the need for a health economic lens arises, 4) and opportunities for the future. The fireside chat will conclude with audience polling to assess the feasibility of the adaptations to health economic methods to align with investor strategy. Twenty minutes will be reserved for audience Q&A.
Moderator
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Melanie D Whittington, MS, PhD
Leerink Center for Pharmacoeconomics, Boston, MA, United States
Melanie Whittington is the Managing Director and Head of the Leerink Center for Pharmacoeconomics where she leads pharmacoeconomic evaluations of in-development and recently approved pharmaceuticals and studies incentives for innovation. She is also a Senior Fellow at the Center for the Evaluation of Value and Risk in Health (CEVR) where she advises on CEVR projects related to value assessment, economic modeling, and CEVR databases.
Speakers
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Meng Li, MS, PhD
Tufts Medical Center; Stifel, Boston, MA, United States
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Richard Xie, PhD
RA Capital Management, Newton, MA, United States
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Sorochi Van Sickle, PhD
Patient Square Capital, Menlo Park, CA, United States
Getting Closer to the Target: Practical Strategies to Hit the Mark in Trial Emulation
Session Type: Workshop
Topics: Methodological & Statistical Research, Study Approaches, Real World Data & Information Systems
Track: Real-World Evidence (RWE)
Level: Intermediate
Purpose
As target trial emulation (TTE) frameworks gain prominence, there is increasing demand to engage with methodologically complex domains. Researchers must carefully define eligibility criteria, construct appropriate index dates, align follow-up time, control for confounding, maintain outcome masking, and ensure rigorous data quality—all while meeting rapidly evolving regulatory and HTA expectations. Even minor misalignment of design elements can introduce substantial bias and undermine the credibility of the evidence generated. Despite growing interest, practical guidance on how to operationalize TTE principles and choose between competing analytic approaches remains limited. This workshop aims to translate the conceptual framework into actionable strategies for rigorous design and evaluation of external control arm (ECA) and hybrid trials.
Description
This workshop will be chaired by Dr. Opper, who will introduce core TTE concepts (5 min).
• Dr. Van Le (academia) will synthesize real-world lessons from ECAs submitted to regulatory/HTA bodies, covering data landscaping best practices to justify data source selection, and provide a framework for applying trial eligibility criteria to a real-world population (15 min).
• Dr. Aggarwal (CRO) will compare established and emerging strategies for index date assignment, follow-up alignment, and approaches to minimize immortal time bias (10 min).
• Dr. Debray (academia) will present key design concepts of hybrid designs, comparing to single arm trials and highlighting variation in statistical methods including Bayesian borrowing, using examples from FDA/EMA approvals (10 min).
A 20-minute interactive, hands-on case exercise will demonstrate how design changes such as comparator eligibility, varying time zero, and comparator weighting can substantially affect results. Through facilitated discussion and live polling, participants will evaluate tradeoffs and apply bias-mitigation principles. This workshop will equip researchers and decision-makers with practical tools to operationalize TTE principles and choose credible, defensible analytic strategies to hit the target for trial emulation.
Moderator
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Neisha Opper, MPH, PhD
Landmark Science, La Crescenta, CA, United States
Speakers
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Hoa Le, PhD, MD
The University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
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Shivani Aggarwal, MS, PhD
Landmark Science, Inc, Los Angeles, CA, United States
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Thomas Debray, BSc, MSc, PhD
Smart Data Analysis and Statistics, Utrecht, Netherlands
Thomas P.A. Debray, PhD, is a statistician and founder of Smart Data Analysis and Statistics (SDAS), a consultancy specializing in innovative statistical methodology for the pharmaceutical and biotech sectors. He combines an academic background in real-world evidence, precision medicine, and evidence synthesis with practical implementation in clinical development and regulatory contexts.
Dr. Debray holds an academic affiliation as guest scientist at the University Medical Center Göttingen and previously served as assistant professor at Utrecht University, with honorary appointments at leading UK institutions. He has contributed to international methodological guidelines, EU-funded research initiatives, and reporting standards aimed at improving transparency and rigor in clinical research. He is co-editor of the book Comparative Effectiveness and Personalized Medicine Research Using Real-World Data (CRC Press).
Through SDAS, he advances methodological innovation in clinical trial design, comparative effectiveness research, and simulation-based decision-making, supporting industry, HTA bodies, and regulators in addressing complex scientific and regulatory challenges.
Agentic AI in Evidence Submissions: Rigor, Trust, Traceability & Compliance
Session Type: Workshop
Topics: Health Policy & Regulatory, Methodological & Statistical Research, Health Technology Assessment
Track: AI
Level: Intermediate
Purpose
Generative and agentic AI can substantially accelerate evidence generation and synthesis. Yet the development and adoption of Agentic AI-driven workflows for evidence submissions raises critical questions: what are the methodological and implementation considerations when automating documentation and evidence packages using agentic AI frameworks? How should industry redesign workflows to preserve trust, traceability, and compliance when AI becomes an active contributor to evidence development? How can organizations ensure transparency and methodological rigor? And what documentation pathways will payers and regulators expect as AI-generated evidence becomes more prevalent? This workshop brings together leaders from biopharma, regulatory science, and AI research to offer a practical, multidisciplinary view of this rapidly evolving landscape.
Description
The session will open with an overview of the evolving role of agentic AI in HEOR. Dr. Wang (Tulane/NouStarX) will present an implementation framework for agentic AI in evidence submissions, focusing on knowledge-base generation, documentation automation, and quality controls. Ms. Ozer-Stillman (Takeda) will share real-world experience applying AI-enabled processes to GVD, adaptations for local HTA submissions and value communications tools, highlighting practical considerations for auditability, traceability, and cross-functional alignment. Dr. Huo (Johnson & Johnson) will discuss opportunities and constraints for AI-supported FDA engagements, including experiences related to programs such as Breakthrough Therapy Designation and Post-Marketing Requirements/Commitments, and will address the evidential standards and validation requirements necessary for AI-assisted evidence to be credible in regulatory interactions. Finally, Dr. Innes (FDA) will offer a forward-looking regulatory perspective on the transparency, robustness, and provenance expectations that may guide future acceptance of AI-generated evidence as organizations adopt agentic AI–driven workflows. The session will be followed by a moderated panel discussion focused on practical adoption guidance, governance considerations, and an open Q&A.
Moderator
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Xiaoyan Wang, PhD
Tulane University, New Orleans, LA, United States
Speakers
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Ipek Ozer Stillman, MBA, MSc
Takeda, Cambridge, MA, United States
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Jinghai Stephen Huo
Janssen Pharmaceuticals (Johnson and Johnson), United States
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Gabriel Innes, VMD PhD
US Food and Drug Administration, Silver Spring, MD, United States
Beyond Claims and EHRs: Social Media as Real-World Evidence to Uncover Patient Experiences and Unmet Needs
Session Type: Workshop
Topics: Real World Data & Information Systems, Health Technology Assessment, Health Service Delivery & Process of Care
Track: Real-World Evidence (RWE)
Level: Introductory
PURPOSE: Patients increasingly share experiences, treatment feedback, and concerns on social media and online health communities, creating a rich, real-time data source now recognized by the FDA in its Patient-Focused Drug Development: Methods to Identify What Is Important to Patients (2022). Advances in natural language processing (NLP), particularly large language models (LLMs) such as ChatGPT, enable scalable analysis of this unstructured content, uncovering insights into patient experiences and unmet needs often missed by traditional methods.
This 60-minute workshop aims to build awareness and practical competence in social media listening (SML) and equip participants with strategies to leverage digital patient narratives. By the end of the session, attendees will understand the strengths and limitations of SML, and what state-of-the-art NLP and LLM technologies offer. Participants will also learn how and when to apply these approaches to transform patient voices into actionable insights that inform drug discovery, development, and value assessment.
DESCRIPTION: Grounded in the FDA’s 2022 guidance, which explicitly recognizes social media as a valid source of qualitative and quantitative patient experience data, this session will provide an overview of SML methods and applications, addressing key considerations such as study design, data quality, and privacy through real-world examples.
Dr. Jen will introduce the topic in the context of patient-centered drug development and traditional evidence sources (5 min). Dr. Song will discuss how SML addresses evidence gaps in rare diseases from a HEOR perspective (10 min). Dr. Sarker will present state-of-the-art NLP/LLM techniques for SML (15 min). Dr. Yao will share two real-world applications involving vaccines and chronic autoimmune disease (15 min). The session concludes with an interactive panel, enabling audience engagement through QR code-based polling and discussion (15 min).
By combining regulatory context, technological innovation, and practical case studies, this workshop offers a roadmap for integrating SML into patient-focused drug development programs.
Moderator
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Min-Hua Jen, PhD
Eli Lilly, Uxbridge, United Kingdom
Dr Min-Hua Jen is currently Executive Director - Advanced Analytics and Access Capabilities at Eli Lilly, leading the International Business team on Market Access/HEOR/Medical affairs statistical support. She has extensive experience applying statistics to clinical research, epidemiology and health economics and outcomes research in academia and industry settings. She is an active member in the PSI/EFSPI HTA Special Interest Group (SIG) and the chair-elect of the ISPOR Oncology SIG. She was trained in Epidemiology and Statistics and obtained her PhD at University of Bristol. Her research interests including indirect treatment comparisons and network meta-analysis; particularly incorporate external data for time to event outcomes, surrogacy analyses, survival extrapolation, multilevel modelling and health economic modelling.
Speakers
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Chao Song
UCB, Duluth, GA, United States
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Abeed Sarker, PhD
Emory University, Decatur, GA, United States
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Lixia Yao, PhD
Temple University, Chalfont, PA, United States
The NextGen of Clinical Trials: Patient-Driven or Tech-Driven?
Session Type: Workshop
Topics: Patient-Centered Research, Medical Technologies, Clinical Outcomes
Track: AI
Level: Intermediate
Purpose:
With new advances in technology, how does the future of patient-centricity look? Emerging technologies like artificial intelligence, virtual reality, and digital platforms are integrating with traditional methods, such as qualitative interviews, surveys, and clinical outcome assessments (COAs), to personalize and improve patient care. These innovations create new opportunities to evolve care models (e.g., trials catered to individual needs, decentralized trials) and to inform decisions by regulators and payers. This session will examine how these tools and technologies can be used to systematically collect and/or generate high quality, data-driven, insightful patient experience data (PED) for decision-making and integration into the design and delivery of care.
Description:
Danny Yeh (AESARA) will open the session with a brief presentation that introduces core concepts, emerging technologies, and current use cases. He will then moderate the discussion on the integration of these technologies in clinical trials, drawing on insights from payers and HTA decision-makers. In response to this, the panel will provide perspectives from patient advocacy (Tracey Sikora; NORD), industry (Ebony Dashiell Aje; BioMarin), and regulatory (Selena Daniels; FDA).
The panel will explore:
• Why are we entering a new era in how we approach patient partnership and empowerment in clinical trials?
• How can technology be integrated with traditional methods to ensure clinical trials are shaped by what matters most to each individual patient?
• How does the rise of artificial intelligence and machine learning may influence the collection and use of PED?
• How is the integration of PED collected in routine care (real world evidence) with traditional clinical trial data in decision-making? What standards need to be in place?
• What to expect in the coming years and what issues warrant close attention
The session will include interactive polling questions and time for audience questions and open dialogue.
Moderator
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Danny Yeh, PhD
Aesara, Burlingame, CA, United States
Speakers
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Tracey Sikora, BSc
National Organization for Rare Disorders, Washington, DC, United States
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Ebony Dashiell-Aje, PhD
BioMarin Pharmaceutical Inc., Washington, DC, United States
Ebony Dashiell-Aje, PhD is a leading expert in patient-centered outcomes research, including clinical outcome assessment (COA) and digital health technology development and optimization, measurement science strategy, and patient engagement across the medical product lifecycle. Currently, she serves as the Executive Director & Head of Patient-Centered Outcomes Science at BioMarin. Dr. Dashiell-Aje and has also served within the Division of Clinical Outcome Assessment (DCOA) in the Office of New Drugs at FDA as a scientific lead and consultant to CDER, CBER, and CDRH; she was a key player in shaping patient-focused drug development (PFDD) policy efforts. In addition, she has served as expert consultant to both pharmaceutical industry and federal government clients. As a health outcomes researcher and methodologist, Dr. Dashiell-Aje is driven by her passion for public health and promoting patient-centered medical product development, commercialization, and clinical care. Her research expertise has significantly contributed to evidence-based solutions and has helped shape health policy in multi-stakeholder environments.
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Selena Daniels, PharmD, PhD
US Food and Drug Administration, Silver Spring, MD, United States
Dr. Selena Daniels serves as the Deputy Division Director in the Division of Clinical Outcome Assessment at the FDA. She provides direction, oversight, and leadership to a team of expert analysts who provide consultation and advice on clinical outcome assessment (COA) endpoint development and validation, including considerations for clinical trial design, conduct, analysis, interpretation, and reporting for regulatory determinations of medical product benefit.
Prior to joining the FDA in 2015, Dr. Daniels worked in the Health Economic and Outcomes Research (HEOR) group at Allergan, Inc (now Abbvie), where she developed and executed HEOR strategies, as well as developed and implemented innovative COA strategies and endpoints for clinical trials.
Dr. Daniels received her Doctor of Philosophy degree in Education at Nova Southeastern University and Doctor of Pharmacy degree at Loma Linda University.
New Frontiers in Large Language Models
Session Type: Research Podiums
Large language models (LLM) are are increasingly being used to expedite systematic literature reviews but questions remain regarding their value beyond this use. Presentations included in this session provides examples of how they perform when used to extract data from other types of documents spanning from health technology assessment reports to social media.
Moderator
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Yinan Wang
Houston, TX, United States
A COMPREHENSIVE EVALUATION FRAMEWORK FOR ARTIFICIAL INTELLIGENCE IN CLINICAL DATA EXTRACTION AND NORMALIZATION FOR HEALTH DATA SPACES
OBJECTIVES: To develop and validate a robust framework for the verification and validation of Artificial Intelligence (AI) outputs, specifically Natural Language Processing (NLP) and Automated Terminology Mapping (ATM), in real-world clinical data integration across European Health Data Spaces.
METHODS: We applied a two-tiered evaluation framework to 10 distinct cohorts across 10 European hospitals, analyzing 550 variables. The methodology comprised:
1) A physician-led verification process using Remote Source Data Verification (rSDV) to assess inference accuracy (Precision, Recall, F1-Score) on samples determined by Bayesian statistics ; and 2) A clinical data scientist-led validation phase evaluating six data quality dimensions based on the Kahn Framework.
We assessed consistency across centers using Intraclass Correlation Coefficients (ICC) and mixed-effects models, and evaluated inter-rater reliability using Fleiss’ Kappa. The AI capabilities utilized NLP for unstructured notes and ATM for structured data to map local identifiers or ICD9/ICD10/SNOMED to the OMOP Common Data Model.
RESULTS: The AI capabilities achieved a pooled F1-score of 0.88 (95% CI: 0.84-0.92) across centers. Inter-rater reliability analysis yielded a Fleiss’ Kappa of 0.81, indicating substantial agreement among physician annotators , with 91% agreement against golden annotators. The ICC for F1-scores was 0.0014, demonstrating minimal between-center variability and high generalizability. Integration of AI-generated data increased unique data points by 40% (1.2M to 1.68M) and significantly improved data diversity (Margalef’s Index increased from 3.5 to 5.8). Clinical outcome analysis showed significant effect sizes (Cohen’s d: 0.75-0.95) across cohorts.
CONCLUSIONS: The implementation of a rigorous verification and validation framework confirms the reliability of AI-generated clinical data. While NLP and ATM significantly enhance data volume and diversity, a systematic physician-led verification process ensures high-fidelity representation in the OMOP CDM, enabling robust secondary use of real-world data.
FROM TEXT TO STRUCTURE: EVALUATING LLMS FOR THE EXTRACTION OF COMPLEX EVIDENCE AND UNCERTAINTY VARIABLES FROM HEALTH TECHNOLOGY ASSESSMENT REPORTS
OBJECTIVES: This study evaluated a hybrid framework employing LLMs for the extraction of these structured clinical and economic variables from Health Technology Assessment reports and investigated the use of an "LLM-as-a-Judge" as a novel, scalable method to assess extraction accuracy.
METHODS: A sample of 150 HTA reports from multiple agencies (e.g., NICE, CADTH, TLV) was processed. The target schema included core identifiers, population criteria, and detailed evidence/uncertainty variables (categorising clinical/economic evidence, model uncertainties, real-world evidence role, and social value judgments). A hybrid extraction pipeline was implemented, using rule-based patterns for high-confidence fields and zero/few-shot prompting of a state-of-the-art LLM (e.g., GPT-5) for complex, free-text variables. To evaluate accuracy, a separate LLM-as-a-Judge was prompted to assess the congruence between source text and extracted output for each variable. These automated scores were validated against a subset of 30 human-annotated gold-standard reports.
RESULTS: The hybrid pipeline successfully populated the complex schema, with performance varying significantly by variable type. High accuracy (F1 >0.85) was achieved for structured fields (e.g., molecule, recommendation). Extraction of nuanced evidence and uncertainty variables (e.g., "type of economic model uncertainty") proved more challenging, with F1 scores ranging from 0.65 to 0.80. The LLM-as-a-Judge's accuracy assessments showed strong correlation (r > 0.75) with human judgment for factual variables but lower agreement for subjective classifications. Error analysis revealed that ambiguity in source text phrasing and the synthesis of scattered information were primary failure modes.
CONCLUSIONS: LLMs present a powerful but imperfect tool for structuring complex HTA data. A hybrid rules/LLM approach can effectively build comprehensive databases, with the LLM-as-a-Judge offering a scalable first-pass quality check. The findings provide a framework for prioritising human-in-the-loop review, focusing expert effort on the most semantically challenging evidence and uncertainty variables. This methodology enables the systematic analysis of HTA rationales and evidentiary requirements across jurisdictions.
IDENTIFYING SEXUAL BEHAVIOR FACTORS FOR INDIVIDUALS WITH HEPATITIS C VIRUS USING A LARGE LANGUAGE MODEL-BASED NATURAL LANGUAGE PROCESSING
OBJECTIVES: Hepatitis C virus (HCV) infection remains a public health concern in the U.S., with sexual behaviors reported as potential transmission routes in about one in four cases. Structured medical records often provide incomplete information on these behaviors. We aimed to evaluate the use of natural language processing to extract sexual behavior factors from unstructured clinical narratives.
METHODS: We analyzed unstructured clinical notes from the University of Florida Health electronic health records including individuals ≥18 years tested at least once for HCV between January 2016 and July 2023. We developed a list of keywords to identify sexual behavior factors including sexual orientation/gender identity (e.g., men who have sex with men [MSM], same-sex relationships not MSM, transgender people) and high-risk sexual behaviors (e.g., anal sex, sex for compensation). Sentences containing these keywords were extracted for annotation. Annotation guidelines were developed and iteratively refined during training sessions, resulting in inter-annotator agreement improvement from 66.1% to 90.4%. A GatorTron-based Large Language Model (LLM) was trained on 70% of the annotated sentences, validated on 10% and tested on 20% of the sentences. Performance of concept extraction was evaluated using precision (accuracy), recall (sensitivity), and F1-scores (the harmonic mean of precision and recall; a high F1-score indicates a well-balanced model between precision and recall).
RESULTS: There were 6,092,972 clinical notes from 15,048 individuals tested for HCV. After annotation, we identified 76 sentences containing at least one concept for MSM, 231 sentences for transgender, 50 sentences for same-sex and 314 sentences for high-risk sexual behaviors. Our model achieved robust performance for MSM (Precision=0.722, Recall=0.867, F1 score=0.788), transgender (Precision=0.915, Recall=0.915, F1 score=0.915), same-sex (Precision=0.800, Recall=1.00, F1 score=0.889) and high-risk sexual behaviors (Precision=0.844, Recall=0.794, F1 score=0.818).
CONCLUSIONS: Our findings suggest that the LLM demonstrated high accuracy in extracting concepts related to sexual behavior factors from clinical narratives of individuals tested for HCV.
LISTENING AT SCALE: AI-POWERED INSIGHTS INTO SYSTEMIC LUPUS ERYTHEMATOSUS PATIENT NEEDS FROM SOCIAL MEDIA
OBJECTIVES: Understanding patient experiences and unmet needs is critical for patient-focused drug development. Traditional qualitative methods (e.g., interviews, focus groups) are resource-intensive, particularly for complex conditions like systemic lupus erythematosus (SLE). Social media offers a rich, real-world source of patient perspectives. This study evaluated the feasibility of using large language models (LLMs) to analyze social media data and identify unmet needs among SLE patients.
METHODS: We collected 4,633 posts from ten Reddit subforums using lupus-related queries. After removing duplicates, promotional content, and incomplete posts, 2,603 posts remained, primarily published since 2020. A thematic codebook was developed through manual review of 300 posts, identifying six major themes and 40 subthemes. Two state-of-the-art LLMs, namely Google Gemini 3.0 Pro and OpenAI GPT-5.2 were applied for automated thematic labeling with prompt engineering. Model performance was assessed via inter-rater agreement and human review.
RESULTS: Both LLMs achieved high performance, comparable to human evaluators. Average percent agreement was 94.4%, with Cohen’s kappa of 0.67 for Gemini 3.0 Pro and GPT-5.2. Thematic analysis revealed advice-seeking (84.7%) and emotional coping (53.8%) as dominant discussion topics, alongside frequent mentions of pain (40.9%), other systemic symptoms (49.6%), and flares (28.4%). Medication concerns centered on effectiveness (27.5%) and side effects (19.2%). Diagnostic uncertainty (26.3%) and emotional impact of diagnosis (27.8%) were common. Reported barriers included provider dismissal (18.2%) and access issues (10%). Lifestyle adjustments such as daily living changes (25.1%) and workplace accommodations (10.8%) also noted.
CONCLUSIONS: LLMs can efficiently process large volumes of unstructured social media data, providing scalable insights into patient experiences and unmet needs. This approach complements traditional qualitative research and aligns with the 2022 FDA guidance recognizing social media as a valid source of patient experience data. Integrating AI-driven social listening into drug development may accelerate identification of patient priorities and inform innovation in SLE care.
Novel Real-World Evidence Applications
Session Type: Research Podiums
As real-world evidence (RWE) increasingly informs HTA and policy decisions, ensuring data integrity, reproducibility, transportability and validity is critical. This session brings together innovative approaches such as virtual data pooling, Bayesian transportability of trial data, literature mining through Natural Language Processing (NLP), research-ready hospital data networks, and cross-cohort phenotype harmonization. The presentations highlight innovative solutions for integration of heterogeneous datasets and scaling evidence beyond a single setting to support generalizable and decision-relevant outcomes.
POST-MARKETING PHARMACOVIGILANCE ANALYSIS OF UBLITUXIMAB USING FAERS DATABASE AND LITERATURE MINING
OBJECTIVES: Ublituximab was approved in late 2022 to treat relapsing-multiple sclerosis. To date, the drug has limited real-world safety data. This study aimed to evaluate the post-marketing adverse events (AEs) associated with ublituximab utilizing the FDA Adverse Event Reporting System (FAERS) database and natural language processing (NLP) analysis with published literatures and reports.
METHODS: This study utilized AE data from 2022Q4 to 2025Q3. Disproportionality analyses were performed using Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN) and Multi-Item Gamma Poisson Shrinker (MGPS). A MedDRA preferred term (PT) was classified as a strong safety signal only if it met all four criteria for ROR, PRR, BCPNN and MGPS. A natural-language-processing (NLP) pipeline was applied to ublituximab clinical trials, case reports, reviews, and prescribing information to identify mentions of FAERS strong-signal PTs and summarize their document frequency.
RESULTS: Several strongly flagged AEs from FAERS, including infusion-related reactions (n = 1007, ROR = 182.45, 95% CI 167.91-198.26), upper respiratory tract infection (n = 22, ROR = 3.88, 95% CI 2.55, 5.91) were also reported in the NLP-screened published literature appearing in 87% and 50% of included publications, respectively. In contrast, other FAERS detected signals with high disproportionality such as peroneal nerve palsy (n= 4, ROR=8.23 95%CI 3.08, 22.00), ocular icterus (n=3, ROR=9.50 95% CI 3.05,29.55) were not reported in the published literature.
CONCLUSIONS: The study highlighted potential under-reported safety concerns emerging from post-marketing surveillance, underscoring the importance of continued real-world safety monitoring, especially using newer methods such as NLP.
VIRTUAL POOLING IS ACCURATE AND LIGHTWEIGHT FOR MULTI-INSTITUTION CAUSAL INFERENCE WITHOUT CENTRALIZED DATA SHARING
OBJECTIVES: Multicenter retrospective studies often require pooling of patient-level data, creating significant regulatory and operational barriers. Federated analytics offers a privacy-preserving alternative, but evidence of real-world deployability and fidelity for causal inference remains limited. We evaluated whether virtual pooling (VP), a novel federated analysis system, can be deployed across institutions to reproduce a published causal inference study without centralizing data.
METHODS: We extended VP to support core components of EHR-based retrospective clinical studies, including data harmonization, feature engineering, imputation, propensity score estimation, patient matching, and model estimation. Using this enhanced system, we replicated a recently published study on diabetic eye disease screening practices at UCSF and UC Irvine (N=8,240). Descriptive statistics and causal estimates generated via VP were compared with those from the original centralized analysis.
RESULTS: VP was deployed at UCSF and UCI without infrastructure modifications or new or non-standard governance agreements, with site-specific security approvals completed within 32 days. Descriptive statistics across all 30 baseline covariates were numerically identical between VP and the original study. Univariate analyses likewise reproduced the original effect sizes across all covariates; in both VP and the original study, prior eye clinic referral within the past year (OR = 56.7; 95% CI: 42.1-76.4) and history of eye disease (OR = 6.4; 95% CI: 5.6-7.4) were the strongest predictors. Causal inference analyses estimating the effect of an automated referral system on screening adherence also matched, with screening rates increasing from 21% to 36% at UCSF and from 13% to 34% at UCI.
CONCLUSIONS: VP is an accurate, feasible, and secure platform for multicenter clinical research without requiring patient-level data sharing. VP's successful deployment and our findings validate its practical potential to expand real-world evidence generation to diverse healthcare systems, when data sharing is time-consuming, administratively burdensome, or restricted.
TRANSPORTABILITY-INFORMED CLINICAL AND ECONOMIC EVALUATION OF TIRZEPATIDE FOR LOCAL HTA DECISION-MAKING
OBJECTIVES: Randomized clinical trials (RCTs) are central to health technology assessment (HTA), yet their applicability to local decision-making may be limited when trial populations do not represent the target jurisdiction. Pivotal tirzepatide trials demonstrated substantial weight-loss efficacy but lacked Canadian sites, raising uncertainty about external validity. This study aimed to estimate the clinical short-term cost-effectiveness of tirzepatide in Canada by transporting trial evidence to the population.
METHODS: We conducted Bayesian transportability analysis using patient-level data from the SURPASS-3 trial and the Canadian Community Health Survey (CCHS), a nationally representative survey. Trial eligibility criteria were emulated in the CCHS to define the target population. Transportability was assessed by adjusting trial-based treatment effects for differences in pre-specified effect modifiers (baseline bodyweight, age, sex, and race) between the trial and Canadian populations using a Bayesian g-computation with survey-weighted re-sampling. The transported estimand was the mean difference in bodyweight change (kg) at 52 weeks for tirzepatide (15 mg) versus insulin degludec. Transported treatment effects were estimated nationally and by province/territory. National transported estimates were incorporated into a short-term, payer-perspective cost-effectiveness analysis using a decision-tree model and compared with trial-based efficacy.
RESULTS: In the SURPASS-3 trial, tirzepatide (15 mg) was associated with a mean weight-loss difference of −13.1 kg (95% credible interval CrI: [−14.2, −12.0]) compared with insulin degludec. After the transport to the Canadian population, the effect was attenuated to −12.2 kg (95% CrI: [−13.3, −10.9]), with similar benefits across provinces/territories. While incremental costs were comparable, the reduced incremental benefit under the transported scenario resulted in a higher incremental cost-effectiveness ratio ($599.40 per kilogram lost) compared with the trial scenario ($577.40 per kilogram lost).
CONCLUSIONS: Our study demonstrates the feasibility of generating locally relevant evidence using a transportability analysis. Transported effect estimates can then be used throughout value assessment to generate cost-effectiveness estimates that better reflect local contexts.
HOSPITAL CLINICAL DATA NETWORK AND RESEARCH ORGANIZATION COLLABORATION FOR ANALYSIS OF INFECTION BURDEN IN IMMUNOCOMPROMISED PATIENTS IN FRANCE USING REAL-WORLD ELECTRONIC MEDICAL RECORD DATA
OBJECTIVES: Although medical institutions collect real-world data during routine clinical practice, this data is not research-ready and typically unavailable to external research partners. Graticule collaborated with the network of the clinical data warehouses (CDWs) of the west region of France (HUGO) to develop a network of research-ready electronic medical record (EMR) data and study real-world infection burden among immunocompromised (IC) patients.
METHODS: The HUGO network deployed CDWs using the eHOP® data model to provide interoperable and quality EMR data across hospitals. A protocol that met research needs, data minimization policies, and ethics requirements was developed for creating a cohort of IC patients from four hospitals. The lead CDW developed a data extraction script, including quality controls and data availability checks, and distributed this script to the network. Following validation, the deidentified cohort from each hospital was securely transferred to the project workspace on the Ouest Data Hub, where the consolidated dataset was converted to the OMOP® Common Data Model for Graticule access and analyses within a secure compute environment.
Patients ≥12 years old were indexed on their first visit between December 2021 and October 2023 in which there was prior or current documentation of an IC condition. Rates of viral respiratory infections during follow-up were described.
RESULTS: A total of 30,150 IC patients qualified for the study, including those with immunosuppressive therapy (56%), hematologic malignancy (27%), organ transplantation (21%), solid tumor (17%), and primary immunodeficiency (6%). Rates of infection were 107.8 cases per 1,000 person-years for SARS-CoV-2, 12.4 for influenza, 9.3 for hMPV, and 5.4 for RSV.
CONCLUSIONS: This IC cohort of 30,150 patients demonstrates that collaborative and flexible partnerships allow for inclusion of EMR data in medical research at a large scale, providing an innovative framework for real-world studies. Benchmarking analyses rank the HUGO network among the most operational infrastructures for real-world research.
Forks in the Road: Critical Decision Points and FDA Insights from Six Years of Physical Function COA Development
Session Type: Workshop
Topics: Patient-Centered Research, Clinical Outcomes, Health Policy & Regulatory
Level: Intermediate
Purpose
To equip attendees with tools to engage FDA in developing and validating clinical outcome assessments (COAs). Drawing on a six-year FDA collaboration, we share insights and strategies for sponsors navigating the regulatory landscape of patient-reported and performance outcome measures.
Description
Developing COAs for regulatory purposes requires strategic decision-making throughout the research lifecycle. Disease-specific COA development demands substantial investment and multi-year timelines, creating barriers for rare diseases and small populations. While FDA guidance provides frameworks, sponsors face practical questions: What evidence demonstrates cross-disease utility? How should rigor be balanced with regulatory pragmatism? How can sponsors optimize limited FDA interactions?
This interactive workshop draws on NUCOAT's (Northwestern University Clinical Outcome Assessment Team) position as an FDA-funded collaborative grant (PI: David Cella, PhD), enabling six years of near-monthly FDA consultation while developing physical function measures across rare diseases and sarcopenia of aging. This offered opportunities to test assumptions, refine methods, and understand which evidence most influenced FDA discussions.
Attendees will navigate key "forks in the road"—decision points where methodological or strategic choices shaped NUCOAT's trajectory and FDA input proved pivotal, spanning: concept elicitation and content validity, measurement properties and validation, meaningful change determination, and qualification pathway planning.
For each fork, speakers present real-world challenges. Attendees vote on preferred approaches via live polling, discuss with neighbors, then learn what pathway NUCOAT selected and how FDA engagement informed the decision. Each section concludes with practical "pearls" on anticipating regulatory concerns, prioritizing evidence, and preparing Drug Development Tool submissions.
The workshop features study leadership and an FDA representative offering complementary perspectives to help attendees prepare for their own FDA engagements.
Moderator
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Maja Kuharic, PhD
Northwestern University Feinberg School of Medicine, CHICAGO, IL, United States
Maja Kuharic, MPharm, MSc, PhD, is an Assistant Professor in the Department of Medical Social Sciences at Northwestern University Feinberg School of Medicine. Her research focuses on patient-reported outcomes (PROs), health-related quality of life, and economic evaluation. She specializes in the development, validation, and application of PROMIS measures and preference-based instruments such as the EQ-5D and EQ-HWB.
Speakers
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David Cella, PhD
Northwestern University, Chicago, IL, United States
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Robyn Bent, MS, RN
US Food and Drug Administration, Silver Spring, MD, United States
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Courtney Hurt
Northwestern University, Chicago, IL, United States
Courtney Hurt, MSW, is a Senior Project Manager and measurement scientist in the Department of Medical Social Sciences at Northwestern University Feinberg School of Medicine, where she specializes in the development and validation of fit-for-purpose Clinical Outcome Assessments (COAs) using qualitative and mixed methods. Her work spans federally funded research and pharmaceutical consulting, supporting FDA submissions and COA strategies that meet standards for content validity and measurement rigor across diverse therapeutic areas.
The Alphabet Soup of Drug Pricing: Understanding Interactions of ASP, MFP, MFN, 340B, and MDRP
Session Type: Workshop
Topics: Health Policy & Regulatory, Health Service Delivery & Process of Care, Organizational Practices
Track: Access and Drug Pricing
Level: Intermediate
Purpose: This year marks the launch of the negotiated prices in the Medicare Drug Price Negotiation Program and introduces another pricing benchmark, the Maximum Fair Price (MFP). There are several other programs in the drug pricing landscape with significant policy changes – such as the 340B rebate model, the most favored nation (MFN) pricing models, and the Medicaid best price guarantee – setting the stage for a complex interplay between these programs and the MFP. These policy changes have the potential to bring more confusion to an already complex and opaque pricing system for manufacturers, health plans, healthcare providers, policymakers, patients, and researchers. Workshop participants will learn the fundamentals of the programmatic updates in the federal drug pricing landscape, identify critical points of interaction between programs, and learn how best to monitor these policies as they unfold.
Description: Ramachandran will provide basics of the drug pricing programs with a brief history of the issue in Medicare, Medicaid, and commercial insurance (10 mins). Martin will summarize the most recent legislative and regulatory updates to these programs – effectuation of MFP, MFN models, 340B rebate model, and the Medicaid best price guarantee (15 mins). Coster will identify points of interactions between programs and identify challenges facing patients, providers, and manufacturers in navigating the new landscape and preview the next year of drug pricing policy including identifying areas for potential reform. (15 mins). Participants will engage with panelists in small group discussions for a series of three case-based simulations in oncology, injectable medication, and a long-acting oral medication. In each case, participants will be make pricing and access decisions using real-time polling as if they were a manufacturer, payer, or provider navigating current policy. (15 mins) Panelists will engage with audience to address questions on the impacts of these policies for patients, providers, and payers. (5 mins)
Moderator
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Sujith Ramachandran, PhD
University of Mississippi, University, MS, United States
Sujith Ramachandran, PhD, is an Associate Professor of Pharmacy Administration and Assistant Director for the Center for Pharmaceutical Marketing & Management at the University of Mississippi School of Pharmacy. His research focuses on building a high-quality, equitable healthcare system that improves patient outcomes and delivers value. His experience includes health policy, pharmacoepidemiology, healthcare quality, and research methods to advance health equity. He has worked closely with the Mississippi Division of Medicaid on quality monitoring and care delivery reforms and has collaborated with the Pharmacy Quality Alliance, co-chairing national multidisciplinary workgroups on quality measures. In 2024, he was selected as the Robert Wood Johnson Foundation health policy fellow, subsequently serving on the US Senate Committee on Finance where he contributed to issues on drug policy. He was part of the National Minority Quality Forum’s 2025 class of 40 under 40 Leaders in Health, and has previously received new investigator awards from the University of Mississippi and the American Association of Colleges of Pharmacy. His research has been funded by the National Institute on Drug Abuse, the Mississippi Department of Health, Substance Use and Mental Health Services Administration, and other organizations. He earned his MS and PhD from the University of Mississippi.
Speakers
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Kristi Martin
Camber Collective, Washington, DC, United States
Kristi Martin provides policy expertise and strategic counsel to advance meaningful health policy that focuses on improving the health and wellbeing of people while delivering practical policy solutions. She draws on more than 20 years of experience working in the public sector, with private sector clients, and in philanthropy. Most recently, Kristi served as the chief of staff and senior advisor to the deputy administrator in the Center for Medicare at the Centers for Medicare & Medicaid Services (CMS). While serving at CMS, she played a significant role advancing regulatory policy in Medicare and implementing the Inflation Reduction Act -- the most significant changes to Medicare Part D since its inception. Kristi facilitated and coordinated the implementation of the Medicare Drug Price Negotiation Program, which successfully negotiated the first set of drug prices under the Medicare Drug Price Negotiation Program that will save people with Medicare and the program billions of dollars on prescription drug costs as well as contributed to a wide range of other policy and operational initiatives that have made Medicare better than ever. Kristi previously was the Vice President for Health Care at Arnold Ventures where she led the philanthropy's prescription drug pricing portfolio and was the Managing Director of Waxman Strategies' health practice where she worked alongside Congressman Henry Waxman to drive outcomes in health policy. She has previously served several years in the U.S. Department of Health and Human Services, Office of Personnel Management, and Government Accountability Office. As a senior advisor in the Obama administration's Office of Health Reform, she had primary oversight responsibility for the coordinated and timely implementation of cross-cutting departmental public health and prevention initiatives under the Affordable Care Act, including addressing the rising cost of drugs and setting up the women's preventive services initiative. She received her bachelor's and master's degrees in health communication from the University of Kentucky and a Master of Public Administration from George Washington University.
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John M Coster, PhD, RPh
Centers for Medicare and Medicaid Services (CMS), Baltimore, MD, United States
Live, Interactive Workshop of Generative AI for Real-World Market Access Challenges
Session Type: Workshop
Topics: Health Technology Assessment, Health Policy & Regulatory
Track: Access and Drug Pricing
Level: Introductory
PURPOSE:
This workshop aims to provide a highly practical, scenario-driven exploration of generative AI (GenAI’s) capabilities and limitations for addressing real-world market access challenges—including evidence generation, payer communication, HTA submission development, and value story creation. Participants will learn how GenAI tools can be used responsibly, where human expertise remains indispensable, and how to evaluate readiness for adoption within their own organizations.
DESCRIPTION:
The workshop uses a problem-first, interactive format. Dr. Chhatwal will introduce the session and outline the increasing operational pressures facing market access teams. Market access expert Narin Yasar will present a series of realistic, high-impact scenarios drawn from global product launches, payer negotiations, and HTA submissions—such as generating rapid evidence summaries, developing alternative value messages, preparing country-specific HTA dossiers, addressing last-minute payer queries, and aligning cross-functional teams around a value narrative.
GenAI expert Dr. Turgay Ayer will evaluate the feasibility and risks of applying GenAI to each scenario, emphasizing methodological guardrails, data-quality considerations, and governance best practices. He will also provide live demonstrations of GenAI applications that perform tasks such as summarizing clinical evidence, drafting payer-facing language, generating full landscape assessment reports in hours, and adapting global value materials for local contexts.
The final segment consists of audience-driven scenario testing: participants will propose real challenges they face, and the panel will collaboratively assess how GenAI could—or could not—address them. This workshop provides actionable insights for HEOR and market access professionals seeking responsible, real-world integration of GenAI into their daily workflows.
Moderator
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Jag Chhatwal, PhD
Harvard Medical School / Massachusetts General Hospital, Boston, MA, United States
Jag Chhatwal, PhD, is the director of the Institute for Technology Assessment at Massachusetts General Hospital and an associate professor at Harvard Medical School. He also serves as core faculty at the Center for Health Decision Science, Harvard T.H. Chan School of Public Health. Dr. Chhatwal has co-authored more than 125 original research articles and editorials in leading peer-reviewed journals. His research has informed health policy decisions at prominent organizations including the White House, the World Health Organization, and the CDC, and has been featured in major media outlets such as CNN, Forbes, National Public Radio, The New York Times, and The Wall Street Journal. Dr. Chhatwal serves as an associate editor of Value in Health and as guest editor for its special issue on artificial intelligence. He is also a member of the ISPOR Generative AI Working Group.
Speakers
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Narin Yasar, MBA
Merck & Co. Inc, Rahway, NJ, United States
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Turgay Ayer, PhD
Value Analytics Labs, Boston, MA, United States
Turgay Ayer, PhD, holds the Virginia C. and Joseph C. Mello Chair and serves as the research director for Healthcare Analytics and Business Intelligence at the Center for Health & Humanitarian Systems at Georgia Tech. He is also the chief technology officer at Value Analytics Labs. Dr. Ayer holds a courtesy appointment at Emory Medical School where he teaches Big Data Analytics courses and serves as a Senior Scientist at the Centers for Disease Control and Prevention (CDC). Dr. Ayer’s research focuses on health economics modeling (HEOR), real-world evidence, data science, machine learning, econometric modeling, and healthcare analytics. He has published over 80 peer-reviewed journal papers and more than 300 conference abstracts, with his work featured in top-tier business, engineering, medical, and health policy journals. His research has attracted substantial attention from major media outlets, including The Wall Street Journal, The Washington Post, US News, and NPR. A recognized expert in HEOR, Dr. Ayer has been at the forefront of applying generative AI to navigate healthcare systems and support better decision-making. He has contributed significantly to the development of advanced models for predicting healthcare outcomes and designing innovative cost-effectiveness analysis frameworks. Under his leadership, Value Analytics Labs has focused on the development of cutting-edge technologies, including ValueGen.AI, to enhance healthcare analytics and improve the efficiency of healthcare decision-making processes.
6:00 PM - 7:00 PM
ISPOR Women in HEOR Reception
Session Type: General Meeting
Welcome Reception
Session Type: General Meeting
Join us for the Welcome Reception, supported by Corporate Partners. A perfect kick-off to connect, unwind, and gear up for what's ahead.
Tue May 19
7:00 AM - 8:30 AM
Morning Coffee Service
Session Type: General Meeting
Don't miss the start of the day with the Plenary Session. Enjoy your morning coffee as you listen to dynamic presentations intended to inspire and empower.
7:00 AM - 5:00 PM
Registration Hours
Session Type: General Meeting
8:30 AM - 10:00 AM
Plenary Session: Presidential Addresses, Special Address, and Awards
Session Type: Plenary
Start Day 2 of ISPOR 2026 with inspiring insights from the Society’s leadership and a distinguished scientific perspective. This session will feature remarks from the ISPOR President and President-Elect, followed by a special address from Dr Dawn Hershman, recipient of the Karnofsky Award—ASCO’s highest scientific honor.
Immediately following the opening presentations, the scientific plenary panel will take the stage.
Speakers
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Uwe Siebert, MPH, MSc, ScD, MD
UMIT TIROL - University for Health Sciences and Technology; Harvard Chan School of Public Health, Hall in Tirol, Austria
Uwe Siebert, MD, MPH, MSc, ScD, is a professor of Public Health, Medical Decision Making and Health Technology Assessment (HTA), chair of the Department of Public Health, Health Services Research and HTA at UMIT TIROL-University for Health Sciences and Technology in Austria and director of the Division for HTA in the ONCOTYROL–Center for Personalized Cancer Medicine in Austria. He is also adjunct professor of Epidemiology and Health Policy & Management at the Harvard T.H. Chan School of Public Health and Affiliated Researcher in the Program on Cardiovascular Research at the Institute for Technology Assessment and Department of Radiology at the Massachusetts General Hospital, Harvard Medical School, Boston.
After medical school, he worked for several years as a physician in international public health projects in West Africa, Brazil, and Germany. He then earned an MPH at the Munich School of Public Health and completed an MSc in Epidemiology and a ScD in Health Policy and Management with a concentration in decision sciences at the Harvard School of Public Health.
His research interests include applying real-world evidence-based quantitative, causal and translational methods from public health, epidemiology, artificial intelligence, comparative effectiveness research, health services and outcomes research, economic evaluation, modeling, and health data a d decision science in the framework of health care policy advice and HTA as well as in the clinical context of routine health care, clinical guideline development, public health policies and patient guidance. His research focuses on cancer, infectious disease, cardiovascular disease, neurological disorders, and others.
He has been leading projects/work packages in several EU FP7, H2020 and Horizon Europe projects (eg, ELSA-GEN, BiomarCaRE, MedTecHTA, DEXHELPP, EUthyroid, FORECEE, MDS-RIGHT, RECETAS, CORE-MD, EUREGIO-EFH, CIDS, OnCoVID, 4D PICTURE, CATALYSE). He teaches HTA, health economics, modeling, epidemiology, causal inference and target trial emulation, and data and decision science for academia, industry, and health authorities in Europe, North and South America, and Asia. He directs the Continuing Education Program on Health Technology Assessment & Decision Sciences (htads.org).
He has served as member of the ISPOR Directors Board and as president of the Society for Medical Decision Making (SMDM). He is a leadership member of the ISPOR Personalized/Precision Medicine SIG, a member of the Latin America Consortium Advisory Committee of ISPOR, and co-chair of the ISPOR-SMDM Modeling Good Research Practices Task Force. He is a member of the Oncology Advisory Council and the National Committee for Cancer Screening of the Austrian Federal Ministry of Health.
He has authored more than 400 publications (> 30,000 citations, H index > 80), and is editor of the European Journal of Epidemiology. Further information Internet: http://htads.org, umit-tirol.at/dph, hsph.harvard.edu/uwe-siebert, Twitter: @UweSiebert9, LinkedIn: uwe-siebert9.
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Beth Devine, PhD, PharmD, MBA, MSc
University of Washington, Seattle, WA, United States
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Dawn Hershman, MD, MS, FASCO
Columbia University Medical Center, New York, NY, United States
Plenary Session: The True Cost of Cancer: Aligning Innovation, Access, and Affordability
Session Type: Plenary
Topics: Economic Evaluation, Health Service Delivery & Process of Care, Patient-Centered Research
Track: Expanded Value Measures
Level: Advanced
Cancer imposes a profound economic burden on patients, families, health systems, and insurers—often extending well beyond clinical outcomes. This plenary session will examine strategies to reduce the financial impact of cancer while preserving high-quality, equitable care. Speakers will explore the concept of financial toxicity as a critical and measurable outcome of cancer treatment, highlighting its effects on treatment adherence, quality of life, and long-term survivorship.
This session will spotlight advances in cancer care delivery research that identify cost drivers across the care continuum and evaluate interventions that improve efficiency, coordination, and patient-centered value. Panelists will also examine private sector solutions, including innovative benefit design, value-based payment models, data-driven care management, and partnerships between payers, providers, and life sciences companies.
A final focus will be the role of comprehensive cancer centers as engines of innovation—leveraging research, multidisciplinary care models, community outreach, and policy leadership to reduce costs and disparities at scale. Together, these perspectives will frame a forward-looking discussion on aligning incentives, accelerating evidence-based solutions, and building sustainable cancer care systems that minimize economic harm while maximizing outcomes for all stakeholders.
Moderator
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Scott Ramsey, PhD, MD
Fred Hutchinson Cancer Research Center, Seattle, WA, United States
Dr. Ramsey is a general internist and health economist. He is a Professor and Director of the Hutchinson Institute for Cancer Outcomes Research, a multidisciplinary team devoted to cancer outcomes research. Dr. Ramsey is also a Professor in the Schools of Medicine and Pharmacy at the University of Washington.
Trained in Medicine and economics, Dr. Ramsey’s research focuses on outcomes research and cancer care delivery. His studies on financial toxicity issues faced by cancer patients are widely cited. He leads the Value in Cancer Care initiative, a statewide quality and cost reporting program aimed at improving oncology care. His other research interest includes cancer care delivery research, pragmatic trial design, cost-effectiveness analysis, and stakeholder engagement.
Dr. Ramsey is co-Chair National Cancer Institute’s Cancer Care Delivery Research Steering Committee and a co-chair of SWOG’s Cancer Care Delivery Committee. He is past President of the International Society of Pharmacoeconomics and Outcomes Research (ISPOR) and has served on the National Academy of Science’s Cancer Policy Forum. He is Co-Principal Investigator for the Coordination and Communications Center of the National Cancer Institute’s Cancer Screening Research Network.
Speakers
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Dawn Hershman, MD, MS, FASCO
Columbia University Medical Center, New York, NY, United States
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Stacie Dusetzina, PhD
Vanderbilt University Medical Center, Nashville, TN, United States
Dr. Dusetzina is a professor of Health Policy and an Ingram professor of cancer research at Vanderbilt University School of Medicine, Department of Health Policy. She is a health services researcher focusing on the intersection between health policy, epidemiology, and economics related to prescription drugs. She has been recognized for her work at a national level, advising Congressional committees and multiple government agencies on prescription drug legislation. She is currently serving as a member of the Medicare Payment Advisory Commission and was recently elected to the National Academy of Medicine for her work related to prescription drug pricing and access.
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Bobby Green, MD
ThymeCare, Nashville, TN, United States
Co-Founder, Chief Medical Officer & President
Dr. Bobby Green, MD, is a medical oncologist and Thyme Care’s co-founder, president and chief medical officer. Thyme Care is the leading value-based cancer care partner, collaborating with payers and providers to transform the experience and outcomes for individuals living with cancer. Prior to joining Thyme Care, Bobby was the chief medical officer at Flatiron Health. He practiced medical oncology in West Palm Beach, Fl at Palm Beach Cancer Institute (which became part of Florida Cancer Specialists) from 1999-2021. Bobby received his undergraduate and MD degrees at Duke University and a masters of science in clinical epidemiology and biostatistics at the University of Pennsylvania where he also completed his internal medicine residency and medical oncology fellowship.
9:30 AM - 7:00 PM
Exhibit Hall Hours
Session Type: General Meeting
10:00 AM - 10:30 AM
Coffee and Connect
Session Type: General Meeting
Head to the exhibit hall to connect with fellow attendees and exhibitors over a steaming cup of coffee.
10:30 AM - 11:30 AM
Health-Related Quality of Life and Utility Estimation
Session Type: Research Podiums
Measuring and comparing health-related quality of life (HRQoL) within and across conditions is essential for cost-utility analyses within the QALY framework. International health technology assessment (HTA) may also require converting health utilities between country-specific tariffs. This session examines methodological approaches to HRQoL measurement and utility estimation, including cross-country EQ-5D utility conversion, mapping pediatric quality-of-life measures to EQ-5D-Y-3L, validation of health utilities derived from the Veterans RAND 12-Item Health Survey (VR-12), and comparisons of HRQoL impacts across levels of liver disease severity using EQ-5D.
APPLICATION OF MAPPING ALGORITHMS FOR THE PEDIATRIC QUALITY OF LIFE INVENTORY GENERIC CORE SCALES (PEDSQL GCS) TO THE EUROQOL 5 DIMENSIONS (EQ-5D) UTILITIES IN CHILDHOOD CANCER SURVIVORS IN JAPAN
OBJECTIVES: To assess the applicability of the mapping algorithms by Khan et al. (2014) to generate EQ-5D utilities based on the EQ-5D Three-Level, Youth Version (EQ-5D-Y-3L) from the PedsQL GCS total score in childhood cancer survivors in Japan, and explore its extension to the EQ-5D Five-Level (EQ-5D-5L), which is administered to younger adults than EQ-5D-Y-3L.
METHODS: We used existing mapping algorithms in which the PedsQL GCS total score was mapped to the EQ-5D-Y-3L utility. To assess prediction errors, the Mean Squared Error (MSE) and Mean Absolute Error (MAE) between the predicted and original utilities were calculated for EQ-5D-Y-3L and the EQ-5D-5L, respectively. All analyses were conducted separately for both EQ-5D-Y-3L and PedsQL GCS complete respondents and both EQ-5D-5L and PedsQL GCS complete respondents.
RESULTS: In the EQ-5D-Y-3L and PedsQL GCS complete respondents (N=36), the means (standard deviations, SD) of the original and predicted utilities across existing algorithms were 0.92 (0.09) and 0.91-0.93 (0.09 for all algorithms), respectively. The MSE and MAE were approximately 0.01 and 0.07, respectively, with no significant differences among the algorithms, and they were similar to the original study results. In addition, in the EQ-5D-5L and PedsQL GCS complete respondents (N=75), the means (SD) of the original and predicted utilities across existing algorithms were 0.92 (0.12), and 0.87-0.90 (0.11 for all algorithms), respectively. The MSE and MAE were approximately 0.01 and 0.08-0.09, respectively. These results were similar to those of the EQ-5D-Y-3L and PedsQL GCS complete respondents.
CONCLUSIONS: The prediction errors for both the EQ-5D-Y-3L and EQ-5D-5L were as small as those in the original study that developed the algorithms and considered acceptable. Our study is the first to show that the mapping algorithms proposed by Khan et al. (2014) are applicable to childhood cancer survivors in Japan.
EMPIRICAL VALIDITY OF CANADIAN-WEIGHTED HEALTH UTILITIES FOR THE VR-12 IN PATIENTS WITH LIFE-LIMITING ILLNESS AND THEIR FAMILY CAREGIVERS
OBJECTIVES: The Veterans RAND 12-Item Health Survey (VR-12) is a generic patient-reported outcome measure designed to assess health-related quality-of-life. Since 2023, VR-12 responses can also be used to derive health utilities reflecting Canadian population preferences. This study examines convergent validity, discriminant validity, and sensitivity-to-change of VR-12 health utilities in the context of older Canadians with life-limiting illnesses and their family caregivers.
METHODS: Data come from a randomized controlled trial comprising patients (n=331) receiving home-based care and their caregivers (n=111), with outcomes collected at two-month intervals over a year. Pertinent data include the VR-12 and sociodemographics, the McGill Quality of Life and Edmonton Symptom Assessment System (patients), and the Quality of Life in Life-Threatening Illness (caregivers). Analyses-conducted separately for patients and caregivers-explored: (i) convergent validity (Spearman’s rank correlation); (ii) discriminant validity, based on 21 ‘strong’ and 11 ‘exploratory’ hypothesized constructs; and (iii) sensitivity-to-change, using distributional methods to categorise participants as improved, stable, or declined based on two quality-of-life anchors.
RESULTS: Mean baseline health utility scores were 0.42 (SD 0.27) for patients and 0.62 (SD 0.28) for caregivers. Observed associations followed theoretically expected patterns in direction and relative strength, with strongest correlations for physical, existential, and psychological domains in patients, and for caregivers’ own condition. Seventeen (of 21) and seven (of 11) constructs were confirmed for patients and caregivers, respectively. Sensitivity-to-change analyses showed significant differences in mean change scores across the three categories (improved, stable, or declined). Preliminary effect-size metrics (Cohen’s d and standardized response mean) and AUC-ROC analyses indicate moderate discriminative ability.
CONCLUSIONS: Validity evidence indicates that the VR-12 provides sufficient support for measuring health utility values for older Canadians with life-limiting illnesses and their caregivers. These findings add to the body of evidence to support the suitability of VR-12 health utilities - and wider VR-12 use - in economic evaluations.
HEALTH RELATED QUALITY OF LIFE (HRQOL) REPORTING IN ADULTS WITH METABOLIC DYSFUNCTION-ASSOCIATED STEATOTIC LIVER DISEASE (MASLD) RISK STRATIFIED BY MULTIPARAMETRIC MRI (MPMRI)
OBJECTIVES: The prevalence of Metabolic dysfunction-associated steatotic liver disease (MASLD) is increasing worldwide and expected to have a prevalence of 55% by 2040. Metabolic dysfunction-associated steatohepatitis (MASH), a more serious form of MASLD, is expected to have a US prevalence of 5% by 2040. While the clinical outcomes are well understood, there is limited data on Health-Related Quality of Life (HRQoL) in MASH. Such data is important for evaluating disease burden and guiding clinical decision-making. This research aimed to identify the characteristics of HRQoL among MASH patients. The comparison was based on liver disease activity, assessed through multiparametric MRI (mpMRI), using corrected T1 (cT1) to characterise liver disease activity and Proton Density Fat Fraction (PDFF) for liver fat.
METHODS: 802 (female: 349, male: 453) patients with MASLD/MASH were recruited from specialist centres in Germany, the Netherlands, Portugal and the UK. Each participant completed EQ-5D-5L and VAS questionnaires across four time-points (baseline, 2-months, 6-months and 12-months). In this study, MASH was defined as cT1 and PDFF greater than or equal to 800ms and 10% respectively.
RESULTS: Compared to those with MASLD, MASH patients showed worse self-reported scores across all dimensions of the EQ-5D-5L and VAS and were 15% more likely to report issues with pain/discomfort. After adjusting for comorbidities (obesity, age, diabetes and hyperlipidaemia) MASH patients still showed poorer scores across all EQ-5D dimensions. Among patients with obesity, those with MASH were 35% more likely to report pain/discomfort compared to those with MASLD. Females reported lower scores across all dimensions with the biggest discrepancy in pain/discomfort, where females were 21% more likely to report problems than males.
CONCLUSIONS: Abnormal mpMRI metrics were an indicator of poorer Health-Related Quality of Life in MASH patients, especially for pain/discomfort. MASLD/MASH management should consider integrating both patient-reported outcomes and mpMRI alongside current tools in standard-of-care to inform clinical decisions.
DEVELOPMENT AND EXTERNAL VALIDATION OF A NOVEL COPULA-BASED METHOD FOR CROSS-COUNTRY EQ-5D UTILITY VALUE CONVERSION
OBJECTIVES: International health technology assessments frequently require conversion of EQ-5D utility values between country-specific tariffs, yet no standardized methodology exists. Therefore, this study aimed to develop and validate a novel method for converting UK EQ-5D-3L values to country-specific equivalents by repurposing the NICE-recommended 3L/5L mapping copula model's (Hernandez-Alava [2020]) intermediate caliper-matching algorithm.
METHODS: The conversion method utilized the Hernandez-Alava model's mechanism for identifying EQ-5D health states falling within an empirically specified caliper width (0.100) of target UK values. For each UK utility input, caliper-matched health states were identified, alternative country tariffs applied, and mean values calculated to derive country-specific equivalents. External validation employed the Van Wilder (2019) systematic review catalogue containing paired observations of UK and local EQ-5D values across diseased populations. Predicted local values were compared to observed values using Pearson and Spearman correlations, mean absolute error (MAE), root mean squared error (RMSE), and Bland-Altman analysis to assess agreement and systematic bias.
RESULTS: Validation included 389 paired observations across 13 target countries. Overall performance showed moderate correlation (Spearman ρ=0.556; Pearson r=0.391) with MAE=0.051 and RMSE=0.091. Bland-Altman analysis revealed slight systematic underprediction (mean bias=-0.034; 95% CI: -0.200 to 0.132). Performance varied substantially by country: USA demonstrated strong correlation (n=278; ρ=0.769; MAE=0.026), along with Sweden (6; 0.909; 0.035) and Brazil (6; 0.842; 0.094) while Singapore showed poorer correlation and larger errors (27; 0.266; 0.226) along with Korea (34; 0.379; 0.092) and Denmark (14; 0.356; 0.050).
CONCLUSIONS: This novel conversion method provides a theoretically grounded approach for cross-country EQ-5D utility transformation. While overall validation demonstrates acceptable accuracy, country-specific performance varies considerably, possibly due to unmeasured between-cohort confounding. The method performs well for US conversions and offers a standardized alternative to ad-hoc approaches currently employed in international health economic evaluations. Future work will optimize caliper selection and address validation cohort confounding.
Bridging the Gap or Respecting the Divide? Discussing the Integration of Clinical Outcome Assessments and Patient Preference Data
Session Type: Issue Panel
Topics: Patient-Centered Research, Clinical Outcomes
Track: Expanded Value Measures
Level: Intermediate
There is growing recognition that integrating COAs with PPI can enrich our understanding of patient well-being. However, meaningful integration remains challenging due to differences in assumptions, measurement paradigms, and intended uses. Although these approaches stem from distinct traditions, combining them offers unique insights that neither can provide alone.
Opportunities span clinical care, regulatory review, and HTA. For instance, clinicians can align treatment decisions with patient concerns by comparing expected outcomes and stated concerns. PPI also can help identify relevant domains for COA development and guide COA selection when multiple options exist. In regulatory reviews, COA-based benefits can be interpreted alongside patient tradeoffs, informing what constitutes a meaningful benefit. In HTA, incorporating preference heterogeneity into COA interpretations can inform anticipated treatment uptake, usage intensity, and real coverage costs.
Despite these opportunities, substantial challenges persist. Key barriers include limited cross-disciplinary understanding, differing objectives for COA and PPI instruments, and lack of guidance on how COA and PPI data could be combined to maximize their impact. A candid discussion about when full integration adds value, and when coordinated but parallel use is more practical, is critical for advancing patient-centered evidence generation.
Panelists will reflect on methodological considerations, potential value, and practical strategies for leveraging these complementary approaches to support more holistic and equitable decision making in clinical, regulatory, and coverage contexts. The panel will also consider when such integration provides insights that justify added complexity and investments, and which areas of complementarity, such as defining clinical care, contextualizing benefit-risk assessments, or supporting health technology assessments, should be prioritized.
Each panelist will offer a 10-minute perspective, followed by moderated discussion and audience engagement.
Moderator
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Shelby Reed, RPh, PhD
Duke Clinical Research Institute, Durham, NC, United States
Speakers
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Karen V. MacDonald, BSc, MPH
IQVIA Canada, Calgary, Canada
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Juan M Gonzalez, PhD
Duke Clinical Research Institute, Cary, NC, United States
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Mo Zhou, PhD
Novartis, East Hanover, NJ, United States
Rare Hope for Even Rarer Diseases: Innovation, Evidence, and Regulatory Perspectives
Session Type: Workshop
Topics: Methodological & Statistical Research, Health Policy & Regulatory, Clinical Outcomes
Track: AI
Level: Intermediate
Purpose
Recent advances in natural language processing (NLP) and large language models (LLMs) offer promising pathways to accelerate research, enhance phenotyping, and strengthen evidence packages for regulatory and HTA submissions. Yet the rapid adoption of AI technologies raises critical methodological, operational, and regulatory questions for rare disease drug development. This workshop aims to (1) clarify how emerging AI capabilities can support small-population evidence generation; (2) showcase real-world applications across academia, industry, and regulatory science; and (3) identify transparency, quality, and compliance considerations essential for integrating AI-generated evidence into regulatory and HTA decision-making.
Description
Rare diseases face persistent evidence gaps due to small patient populations, heterogeneous clinical presentations, and fragmented data sources. Advances in NLP and generative/agentic AI offer new opportunities to uncover real-world insights, automate evidence synthesis, and support more agile development pathways.
The session will begin with context on the current AI landscape and the evolving methodological needs specific to small-population research. Dr. Wang (Tulane/NouStarX) will present her research on how NLP and LLMs support underserved and small population research, highlighting how large-scale clinical text analysis and federated learning can strengthen cohort identification and study readiness. Dr. Weng (Columbia) will present the use of fine-tuned LLMs for early diagnosis of rare diseases and genetic testing recommendations using RAG models and human phenotype ontology. Mr. Su (Jazz Pharmaceuticals) will provide an industry perspective, including opportunities and constraints when integrating AI enabled workflows into value and market access strategies. Finally, Dr. Liu (FDA) will share a regulatory viewpoint on expectations for transparency, robustness, and methodological rigor when AI contributes to evidence packages in rare disease programs. The session concludes with a Q&A and digital polling designed to encourage audience interaction.
Moderator
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Xiaoyan Wang, PhD
Tulane University, New Orleans, LA, United States
Speakers
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Chunhua Weng
Columbia University, New York, NY, United States
Dr. Chunhua Weng is a tenured Professor of Biomedical Informatics at Columbia University and an elected fellow of American College of Medical Informatics (ACMI) and International Academy of Health Sciences and Informatics (IAHSI). She is also a Deputy Editor for Journal of Biomedical Informatics. Dr. Weng holds a Ph.D. in Biomedical and Health Informatics from University of Washington at Seattle. Dr. Weng’s long-term research focus is to improve the rigor, efficiency, patient centeredness, and generalizability of clinical research by developing novel informatics and data science methods to address stakeholder needs throughout the life cycle of clinical evidence, from evidence generation to evidence retrieval, appraisal, summarization and dissemination. As an active researcher in the field of Clinical Research Informatics since 2000, Dr. Weng has published extensively on data-driven optimization of clinical research eligibility criteria, deep phenotyping for genetic rare disorders, rare disease diagnostic decision support, electronic health records data quality assessment and data analytics, and text knowledge engineering using a variety of text (e.g., EHR narratives, PubMed and ClinicalTrials.gov summaries).
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Wayne Su, MSc
Jazz Pharmaceuticals, Philadelphia, PA, United States
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Qi Liu, PhD, MStat, FCP
US Food and Drug Administration, Silver Spring, MD, United States
Mental Health: Preferences, Outcomes, and Equity
Session Type: Research Podiums
Mental health is an important aspect of life, and addressing mental health challenges is essential for health systems and the measurement of this is critical for HEOR. Ensuring that this measurement captures outcomes and preferences across different groups is also essential. This session presents real-world data demonstrating the benefit of phenotyping based on patient questionnaire data for identifying patients at risk of negative clinical outcomes (presentation #1), an assessment of ethnic and racial heterogeneity in preferences for dementia therapies (presentation #2), the impact of seizures among patients with early onset dementia (presentation #3), and the validation of a culturally adapted short tool for depression screening in maternal care (presentation #4).
APPETITE DYSREGULATION AND BODY MASS INDEX AMONG ADULTS WITH DEPRESSION AND ANXIETY IN THE REAL-WORLD SETTING
OBJECTIVES: To evaluate the relationship between appetite dysregulation severity, captured by Patient Health Questionnaire-9 (PHQ-9) item 5, and body mass index (BMI) outcomes among adults with depression and/or anxiety in real-world clinical practice.
METHODS: This retrospective cross-sectional study used electronic health records from the OMNY Health real-world data platform (2017-2025). Adult patient encounters for depression and/or anxiety with a recorded BMI and documented response to the PHQ-9 item 5 (“poor appetite or overeating”) on the same date were selected. Appetite dysregulation severity was defined as the response to PHQ-9 item 5. BMI outcomes comprised underweight (BMI < 18.5) and obese (BMI ≥ 30) with the obesity further subcategorized as class I (30 ≤ BMI < 35) and class II-III (BMI ≥ 35). The percentage of patients with each BMI outcome was computed across appetite dysregulation severity levels. Encounter-level analyses were conducted separately for depression only, anxiety only, and comorbid depression/anxiety.
RESULTS: Among 1.93 million encounters (995,382 unique patients) with depression and/or anxiety diagnosis codes, 38.7% were depression only, 28.6% were anxiety only, and 32.7% were both. Across all diagnostic groups, the proportion of underweight patients increased monotonically with greater appetite dysregulation severity (1.3-3.0% in depression; 1.7-3.4% in anxiety; 1.5-3.1% in comorbid depression/anxiety). Similarly, the proportion of patients with obesity (class I-III) increased with higher PHQ-9 item 5 scores (40.2-54.9% across diagnoses). Notably, obesity class I prevalence remained relatively stable across appetite dysregulation categories, whereas obesity class II-III exhibited a clear monotonic increase (23.6-33.2% in depression; 19.3-28.0% in anxiety; 22.5-30.8% in comorbid depression/anxiety).
CONCLUSIONS: Appetite dysregulation severity was associated with a shift toward extreme BMI phenotypes, characterized by higher prevalence of both underweight and severe obesity, independent of psychiatric diagnosis. These findings suggest that symptom-level phenotyping using routinely collected PHQ-9 data may improve identification of patients at elevated metabolic risk beyond diagnosis alone.
RACIAL AND ETHNIC DIFFERENCES IN DEMAND FOR NOVEL DEMENTIA THERAPIES: EVIDENCE FROM A NATIONAL SURVEY OF OLDER ADULTS' PREFERENCES ACROSS DEMENTIA DRUG ATTRIBUTES
OBJECTIVES: To elicit preferences for dementia drug attributes and examine racial/ethnic variation to inform demand for current and future therapies.
METHODS: We conducted a survey of U.S. adults aged 50+ using the Understanding America Study in 2025. Respondents answered vignette-based questions rating hypothetical dementia therapies. A between-subject experiment randomized respondents to consider treatment for themselves or for a loved one. The primary outcome was a binary indicator of being "very likely" to use the treatment. Key covariates were administration mode (daily pill, self-injection, or intravenous infusion [IV]), presence of mild side effects, efficacy level (1- vs. 5-year symptom delay) and their interactions. We conducted survey-weighted logistic regression stratified by race/ethnicity and examined heterogeneity in effects of drug attributes by respondents’ characteristics.
RESULTS: Among 1,529 respondents (mean age 64; 63.4% female), 26.2% were Hispanic, 36.6% non-Hispanic Black, and 37.2% non-Hispanic White. Compared with daily pills, respondents were less likely to choose self-injection (average marginal effect: −2.1 percentage points [pp]) or IV therapy (−7.9 pp). Mild side effects substantially reduced use likelihood by 35.2 pp, while high efficacy increased it by 15.2 pp. Injection and IV attenuated the impact of side effects and low efficacy. While the likelihood of taking a daily pill was similar across racial/ethnic groups, non-Hispanic Black adults were less likely to choose injection or IV. The predicted probability of using an IV with side effects and 1-year symptom delay was 22% among non-Hispanic Black versus 40% among non-Hispanic White adults. Preferences did not differ by treatment recipient (self vs. loved one). Older adults and those with family dementia experience showed greater sensitivity to side effects and efficacy.
CONCLUSIONS: Demand for infusion-based dementia therapies is low, particularly among non-Hispanic Black persons, which may contribute to low uptake of current treatments. Injection or pill-based options may support higher use and reduce disease burden.
DEVELOPING AND VALIDATING A CULTURALLY-ADAPTED OPTIMAL SHORT-FORM OF THE EDINBURGH POSTNATAL DEPRESSION SCALE (EPDS) USING RISKSLIM
OBJECTIVES: Routine depression screening in maternal healthcare can aid in preventing and controlling perinatal depression which is linked to adverse obstetric outcomes. However, the effectiveness of the 10-item Edinburgh Postnatal Depression Scale (EPDS) for screening could be limited in contexts that require large-scale, rapid administration, and particularly when used across multi-ethnic populations. Therefore, this study aims to equip healthcare workers at primary level with a brief, practical tool to improve screening efficiency.
METHODS: In May 2022, EPDS was used to screen 1,191 women from pregnancy to one year postpartum in an ethnic-minority autonomous county of Yunnan Province. Data were randomly divided into training set and test set in a ratio of 7:3. Risk-Calibrated Supersparse Linear Integer Model (RiskSLIM) was utilized for developing short-form EPDS models on the training set with Python 3.13. Models performance were assessed with the Area Under the Receiver Operative Characteristic Curve (AUC) and R-squared (R2). The cultural adaption of models were validated across the datasets of Han majority, Zhuang, Miao, Yao, and other minorities. The optimal cut-off value was determined by Restricted Cubic Splines.
RESULTS: Short-form models of EPDS from 1 to 9 items were constructed with RiskSLIM. Item 2 (can not look forward with enjoyment to things), Item 5 (scared or panicky), item 7 (sleep difficulties), and item 8 (sad or miserable) were selected into the 4-item version EPDS (EPDS-R4), which exhibited consistently high and stable AUC (0.980-0.998) and R² values (0.721-0.921) across multi-ethnic population. The cut-off score of ≥ 10 was recommended.
CONCLUSIONS: EPDS-R4 (cut-off value ≥10) is an efficient and practical screening tool for perinatal depression, which might be adopted in population-based screening program.
SEIZURES AND OVERALL SURVIVAL IN EARLY-ONSET DEMENTIA: A RETROSPECTIVE EHR-BASED COHORT STUDY
OBJECTIVES: Seizures are a recognized complication of dementia in older adults, but seizure conditions are understudied among patients with early-onset dementia (EOD; onset before age 65 years).
METHODS: We conducted a retrospective longitudinal cohort study using data from the University of California, San Francisco Clinical Data Warehouse (UCSF CDW) from 2015 to 2025. Adult individuals with a documented diagnosis of dementia who were younger than 65 years during the study period were included in the analytic cohort. Patients were followed from cohort entry until death or the last date of cohort entry (Jun. 30, 2025), with censoring at the time of loss to follow-up. Descriptive analyses were used to estimate the prevalence of seizures. Multivariable Cox proportional hazard models were applied to examine the association between seizures and overall survival (OS).
RESULTS: A total of 2,633 patients with EOD were identified. The cohort was predominately aged 55-64 years (68.8%), male (53%), non-Hispanic White (53%), publicly insured (53.6%), and with a Charlson Comorbidity Index (CCI) of 1 to 2 (63.3%). Overall, 765 (29.1%) patients had seizure diagnosis at baseline. Seizure prevalence was significantly higher among patients without Alzheimer or Parkinson’s disease (32.4% vs. 18.5%) compared with their respective counterparts. In multivariable Cox models, seizures were independently associated with reduced OS after adjustment for covariates (hazard ratio [HR], 1.22; 95% CI, 1.02-1.46; p = 0.029). In subgroup analyses, seizures remained significantly associated with worse OS among patients with non-Alzheimer’s and non-Parkinson’s disease etiologies, whereas no significant association was observed among patients with Alzheimer’s or Parkinson’s disease.
CONCLUSIONS: Seizures were common among patients with EOD and were independently associated with reduced OS. The adverse prognostic impact of seizures varied by dementia etiology, with significant associations observed in non-Alzheimer’s and non-Parkinson’s disease subgroups. These findings highlight the importance of seizure management and risk stratification in EOD patients.
Beyond the Bots: How AI-Enabled Literature Reviews Are Maturing, and What HEOR Needs Next
Session Type: Issue Panel
Topics: Study Approaches, Methodological & Statistical Research, Health Technology Assessment
Track: AI
Level: Intermediate
Issue
AI-enabled literature review platforms have rapidly expanded across HEOR, regulatory, and medical affairs workflows. The first wave of pilots demonstrated substantial gains in screening speed and reviewer efficiency, but also revealed variability in accuracy, transparency, and reproducibility across review types and organizational settings. Now, as multiple teams have completed successive reviews with the same platforms, the field is entering a second phase, one where outputs can be compared across projects, procurement expectations are more structured, and human, AI workflows are stabilizing.
Overview
The panel will not compare product features. Instead, it will synthesize cross-platform learnings and debate what the HEOR community should expect—and require—from AI-enabled evidence synthesis in its next phase of adoption.
Attendees will leave with: (1) a data-informed understanding of AI SLR maturity, (2) practical evaluation considerations for real-world implementation, and (3) a clearer view of how automation and human judgment must align to preserve scientific integrity.
Panelists will examine how platform capabilities have evolved since 2025 and where divergence persists in real practice. Discussion topics will include:
• How human–AI integration has changed across repeated projects
• Which elements of transparency, version control, and auditability have proven essential
• What patterns are emerging in validation, error tolerance, and sensitivity trade-offs
• Where AI-enabled tools still face methodological gaps
• What “good” should look like as the field moves toward standardization
Moderator
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Ramiro E Gilardino, MSc, MD
R-Impact, Dubendorf, Switzerland
Impact-driven healthcare executive with 15+ years of leadership in Global Market Access, Health Policy, and HEOR. Successfully led strategies that improved patient access, drove reimbursement success, and shaped health policy in pharma, biotech, and global organizations. Expert in advancing HTA frameworks and forging stakeholder partnerships to promote health equity and deliver value-based healthcare solutions globally.
Speakers
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Angeline B Dhas
MadeAi, Littleton, MA, United States
Angeline Babitha Dhas is the Product Manager for MadeAi Solutions, with over 12 years of experience at the intersection of healthcare, technology, and evidence generation. She specializes in identifying time- and resource-intensive tasks within HEOR processes and designing AI-driven solutions to improve efficiency and scalability. Angeline led the development and launch of MadeAi-LR, an AI-aided systematic literature review platform and is now expanding its capabilities to address challenges in Joint Clinical Assessments (JCA), Global Value Dossiers (GVD), drug repurposing, and social media analysis for patient-reported outcomes. Her work focuses on enabling smarter, faster evidence strategies through AI innovation.
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Ranita M Tarchand, BA, MS
Nested Knowledge, St Paul, MN, United States
Ranita is trained as a health economist and epidemiologist. In her role as Vice President of Scientific Strategy and Client Success at Nested Knowledge, she works with private and public institutions on implementing AI methodology and digital transformation at all stages of the product lifecycle. Her research focuses on living HTA methods and artificial intelligence in evidence synthesis and RWE.
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Mark Priatel
DistillerSR, Ottawa, ON, Canada
Data and Approaches to Measuring Affordability and Access to Healthcare Services
Session Type: Issue Panel
Topics: Health Service Delivery & Process of Care, Health Policy & Regulatory, Methodological & Statistical Research
Track: Access and Drug Pricing
Level: Intermediate
ISSUE: ISPOR’s Strategic Plan 2030 identified affordability and its impact on the long-term sustainability of healthcare systems as a central challenge. Growing patient cost sharing, evolving health plan options, and complex benefit design underscore a need to improve our understanding of affordability from a patient’s perspective.
There is limited information about domains of cost-related management strategies (CrMS) and their association with satisfaction and health status among Medicare beneficiaries. Relatedly, beneficiaries may experience substantial changes in their out-of-pocket cost burden and access to providers following selection into Medicare Advantage compared to Traditional Medicare. These perspectives on affordability have different policy implications.
OVERVIEW: This session will address affordability, access, and policy through evaluations and critical discussions of data sources, measurement, and methodological implications on estimates of the effect of affordability on access. Specifically, the session will focus on the Medicare population in the US using two survey data sources – The Medicare Current Beneficiary Survey (MCBS) and Medical Expenditure Panel Survey (MEPS). Using the MCBS, the associations of the domains of CrMS with satisfaction and health status among beneficiaries will be quantified using fixed effects logistic regression. The effect of changes in out-of-pocket burdens and cost barriers associated with plan enrollment choices will be assessed using a fuzzy regression discontinuity design with MEPS data. Following each presentation, another panelist will critically discuss the assumptions, data, methods, and what it implies for their conclusions.
Presenters will introduce the MCBS and MEPS studies (15 minutes each). Discussants will critique the studies with time for presenters to respond (10 minutes each). The session will conclude with audience Q&A (10 min). Session attendees, e.g., researchers, will gain a better understanding of the tradeoffs among frameworks, datasets, and modeling strategies needed to study patient affordability and generate policy-relevant findings.
Moderator
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Eric Barrette, MA, PhD
Medtronic, Minneapolis, MN, United States
Eric Barrette, M.A., Ph.D. is Vice President, HEOR & Market Access Analytics at Medtronic. In this role he supports the development of evidence needed for coverage, payment, and access to Medtronic's therapies. Prior to joining Medtronic he was Director of Research at the Health Care Cost Institute and he has worked as an economic consultant focused on health care and life sciences topics. He is also an instructor in the University of Minnesota, Carlson School of Management Medical Industry MBA program. Dr. Barrette research interests include medical technology outcomes research, Medicare payment policy, geographic variation in medical resource use and prices. He received his M.A. in Economics from the University of Arizona and a Ph.D. in Health Services Research, Policy, and Administration from the University of Minnesota.
Speakers
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Eberechukwu Onukwugha, MSc, PhD
University of Maryland, Baltimore School of Pharmacy, Baltimore, MD, United States
Eberechukwu Onukwugha, PhD is a Professor in the Department of Practice, Sciences, and Health Outcomes Research and Executive Director of Pharmaceutical Research Computing at the University of Maryland School of Pharmacy. She received a Doctor of Philosophy in economics (concentration: econometrics) from Virginia Polytechnic Institute and State University (Virginia Tech). Dr. Onukwugha completed a two-year postdoctoral fellowship in pharmacoeconomics and health outcomes research at the University of Maryland School of Pharmacy. She was a recipient of the PhRMA Foundation’s Post-Doctoral Fellowship in health economics and outcomes research. Dr. Onukwugha’s research interests are in cost analysis, health disparities, and medical decision-making by individuals and institutions. She has approximately 20 years of experience conducting health economics and outcomes research using administrative medical and pharmacy claims, hospital discharge, and prospectively-collected data. Dr. Onukwugha has authored or co-authored over 140 peer-reviewed articles in health economics and outcomes research. She is an Editorial Board member for PharmacoEconomics and an Associate Editor for Ethnicity & Disease. Dr. Onukwugha serves as President, ISPOR Board of Directors, 2024-2025, and serves on the Maryland Prescription Drug Affordability Board.
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Wendy Xu, PhD
The Ohio State University, Columbus, OH, United States
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Junling Wang, PhD
University of Tennessee College of Pharmacy, Memphis, TN, United States
Can the Estimand Framework Strengthen Patient-Centered Cancer Research Throughout the Evidence Generation Lifecycle Beyond Approval: Opportunities and Challenges Ahead?
Session Type: Issue Panel
Topics: Patient-Centered Research, Clinical Outcomes, Study Approaches
Track: Expanded Value Measures
Level: Intermediate
Issue: Despite adoption of the ICH E9(R1) addendum and the estimand framework by the FDA and other regulatory bodies, its role in shaping patient-centered objectives in cancer research remains unclear throughout the continuous evidence lifecycle from clinical development through post-approval research.
Overview: This session will reinforce how the estimand framework can facilitate generation of meaningful patient-centered evidence and will identify current opportunities and challenges for cancer research. Dr. Park will provide an overview of the estimand framework and discuss the role of the estimand framework for both clinical trial and real-world evidence (RWE) studies (8-minutes). Dr. Sharaz will discuss how regulators and health technology assessment (HTA) bodies view patient-reported outcomes (PROs) with a focus on the role of data collection post-treatment and post-progression to supplement traditional survival and progression endpoints (10-minutes). Dr. Skaltsa will discuss the methodological challenges as well as the current advancements with regard to analyzing PROs collected in oncology trials in line with the estimand framework, during the treatment period and beyond (10-minutes). Dr. Roydhouse will discuss considerations for comparing patient-reported tolerability of different therapies, and how comparative tolerability endpoints can supplement other PRO and non-PRO endpoints in oncology (10-minutes). The session will reflect on future directions of methodological research based on the estimand framework for patient-centered research including the communication of estimands to patients, regulators, HTA bodies, and other diverse stakeholders (5-minutes). The session will conclude with an interactive discussion with audience participation to explore current challenges and opportunities ahead for patient-centered research and the estimand framework (17-minutes).
Moderator
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Jay J Park, PhD
Core Clinical Sciences, Vancouver, BC, Canada
Speakers
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SAEID SHAHRAZ
Gilead Sciences, Mountain View, CA, United States
Saeid Shahraz, MD, PhD, is a physician and measurement scientist with over 20 years of experience in health outcomes research. He leads clinical outcome assessment strategy and analytics as Director of Health Economics and Outcomes Research. With expertise in psychometrics, COA validation, and real-world data analysis, Dr. Shahraz supports evidence generation for clinical trials and regulatory submissions. His work bridges scientific rigor and patient-centered measurement to enhance the value and reliability of health outcomes data.
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Konstantina Skaltsa, BSc, PhD
IQVIA, Barcelona, Spain
Konstantina provides scientific oversight for the Patient-Centered Solutions team, ensuring alignment with best practices while driving thought leadership in cutting-edge areas. A statistician by training with over 15 years of academic and industry experience, she is a subject-matter expert in psychometrics and statistical analysis of clinical outcome assessment (COA) data.
Her advisory work spans the full COA endpoint strategy lifecycle, including defining meaningful COA objectives, aligning study design and endpoints, leading estimand discussions, and proposing statistical methodologies aligned with selected estimands. She has supported FDA and EMA interactions for COA-based label claims and contributed to payer dossiers across Europe, Canada and Australia.
Konstantina has extensive experience across oncology, dermatology, rheumatology, and respiratory diseases. She has a strong interest in the implementation of the estimand framework and co-chairs the PSI Patient-Focused Drug Development (PFDD) Special Interest Group, promoting best practices in estimands and estimators for COA endpoints. Additional interests include the analysis and interpretation of tolerability data in oncology trials.
Her market access expertise includes utility estimation, mapping methods, survival analysis, treatment-switching adjustment techniques, and network meta-analysis. She has co-authored multiple peer-reviewed publications and is an active member of PSI, ISPOR, and ISOQoL.
Konstantina holds a PhD in Biostatistics from the University of Barcelona and a BSc in Applied Mathematics from the University of Crete.
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Jessica Roydhouse, PhD
Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia
Dr Jessica Roydhouse is a Senior Research Fellow at the Menzies Institute for Medical Research, the Director of the Tasmanian Cancer Registry and the Academic Lead for the Prostate Cancer Outcomes Registry - Tasmania. Her research focuses on patient-reported outcomes, proxy reporting, cancer clinical trials and treatment tolerability. She was recently awarded the Prostate Cancer Foundation of Australia Priority Impact Research Award (2024). Jessica was recently Past Chair of the ISPOR Patient-Centered Special Interest Group and is an Editor-in-Chief of Quality of Life Research.
Including Equity in Health Technology Assessment: DCEA, Social Welfare Functions, and Inequality-Aversion Approaches
Session Type: Workshop
Topics: Economic Evaluation, Health Technology Assessment, Health Policy & Regulatory
Track: Expanded Value Measures
Level: Introductory
PURPOSE: Health technology assessments (HTAs) continue to grapple with methodologically-based methods to incorporate equity considerations. Current research (e.g., distributional cost-effectiveness analysis (DCEA)) provides clear descriptions of how interventions’ benefits and costs affect identified sub-populations. Social welfare functions (SWFs) provide formal and generalized ways to combine benefits accruing to various population members into a single weighted index of societal well-being. Atkinson’s inequality-aversion measure has been separately applied to consumption and health, but not to both simultaneously. This workshop will review methods at the frontiers of each of these approaches.
DESCRIPTION: Workshop will provide state-of-the-art reviews of various approaches to introducing equity considerations into Health Technology Assessments (HTAs). Professor Griffin, a leading researcher of and advocate for DCEA, will begin with an overview of current DCEA methods as a basis for subsequent discussion. Professor Phelps will provide the foundational basis for valid social welfare functions, showing how the GRACE method for valuing healthcare gains enters such functions. This will include approaches to use these methods in fixed-budget settings. An application to understanding programs to accelerate treatment of rare diseases follows. Mr. Davis will then introduce, based on his in-progress doctoral dissertation, a new and important way to combine Atkinson’s (1970) Inequality Aversion both in the domains of wealth (consumption) and health. An example shows how introduction of new weight-loss drugs does not always compress inequality due to incomplete access by lower-income persons, and provides (for the first time) a monetized measure of the cost of reducing inequality. Audience participation will include an extensive audience Q&A session led by Professor Garrison (20 minutes). This workshop will provide attendees with a cutting-edge view into modern methods for incorporating equity considerations into HTAs.
Moderator
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Lou Garrison, PhD
The Comparative Health Outcomes, Policy, and Economics (CHOICE) Institute, Seattle, WA, United States
Lou Garrison, PhD, is professor emeritus in The Comparative Health Outcomes, Policy, and Economics Institute in the School of Pharmacy at the University of Washington, where he joined the faculty in 2004.
For the first 13 years of his career, Dr. Garrison worked in non-profit health policy at Battelle and then the Project HOPE Center for Health Affairs, where he was the Director from 1989-1992. Following this, he worked as an economist in the pharmaceutical industry for 12 years. From 2002-2004, he was vice president and head of Health Economics & Strategic Pricing in Roche Pharmaceuticals, based in Basel, Switzerland.
Dr. Garrison received a BA in Economics from Indiana University, and a PhD in Economics from Stanford University. He has more than 150 publications in peer-reviewed journals. His research interests include national and international health policy issues related to personalized medicine, benefit-risk analysis, and other topics, as well as the economic evaluation of pharmaceuticals, diagnostics, and other technologies.
Dr. Garrison was elected as ISPOR President for July 2016-June 2017, following other leadership roles since 2005. He recently co-chaired the ISPOR Special Task Force on US Value Frameworks. He was selected in 2017 by PharmaVOICE as being among “100 of the Most Inspiring People” in the industry. He recently received the PhRMA Foundation and Personalized Medicine Coalition 2018 Value Assessment Challenge First-Prize Award as lead author on a paper on “A Strategy to Support the Efficient Development and Use of Innovations in Personalized and Precision Medicine.”
Speakers
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Susan Griffin, PhD
University of York, York, United Kingdom
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Charles E Phelps, MBA, PhD
University of Rochester, Pittsford, NY, United States
Charles Phelps, PhD is professor and provost emeritus at the University of Rochester. He previously held appointments in the departments of economics and political science and served as the director of the Public Policy Analysis Program and chair of the Department of Community and Preventive Medicine in the School of Medicine and Dentistry. Earlier, Dr. Phelps served as a senior staff economist and the director of the Program on Regulatory Policies and Institutions at the RAND Corporation. Dr. Phelps’s research cuts across the fields of health economics, health policy, health technology assessment, and related topics, and he is the author of Health Economics (now in its sixth edition), among other books. He has testified before US congressional committees on health policy and intellectual property issues. He is a fellow of the National Bureau of Economic Research and serves on the board of directors of the Health Care Cost Institute. He has served as the chair of the Board of Directors of VirtualScopics, Inc., and as a consultant to Gilead Sciences, Inc., CardioDx, and Kaiser Permanente of Northern California. He received his BA in mathematics from Pomona College, an MBA in hospital administration, and a PhD in business economics from the University of Chicago. He is a member of the National Academy of Medicine.
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Ian J Davis, MA
University of Southern California, Los Angeles, CA, United States
Are Drug Prices Rising Too Fast? Rethinking Inflation Benchmarks Through the Lens of Value, Access, and Innovation
Session Type: Issue Panel
Topics: Health Technology Assessment, Economic Evaluation, Medical Technologies
Track: Access and Drug Pricing
Level: Introductory
Purpose: Concerns about rising drug prices routinely dominate headlines, with many reports concluding that launch prices outpace inflation. These findings have fueled recent government interventions, including Prescription Drug Affordability Boards (PDABs), that aim to curb price growth and protect affordability for patients and payers. Yet inflation-based benchmarking may overlook a more fundamental question: How does price growth compare to the growth in value delivered by new therapies?
Overview: This issue panel will examine the appropriateness of inflation-based drug price benchmarks versus value-based assessment approaches through a structured, multi-perspective debate. Dr. William Padula (University of Southern California) will moderate the session and open with a brief overview (10 minutes) framing the economic tension between affordability, innovation, and value, drawing on recent analyses comparing drug price trajectories with corresponding health gains. Dr. Jonathan Campbell (National Pharmaceutical Council) will argue that inflation benchmarks obscure value creation and risk undermining incentives for high-impact innovation, emphasizing the role of value-based frameworks in contextualizing price growth. Dr. Laura Pizzi (ISPOR) will examine inflation-based benchmarks as a pragmatic policy tool for addressing affordability, budget predictability, and patient financial exposure, which align with the ISPOR mission. Dr. Andrew York (Maryland Prescription Drug Affordability Board) will focus on policy implementation, discussing how inflation- and value-based approaches are operationalized in real-world settings, including PDAB processes and payer decision-making. Each panelist will have 10 minutes to establish their position, and the presentations will be followed by a moderated exchange and audience discussion (20 minutes). This session will benefit HTA researchers, policymakers, payers, manufacturers, and patient advocates seeking to understand how price, value, and access considerations can be better aligned in pharmaceutical policy debates.
Moderator
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William V Padula, PhD
University of Southern California, Rancho Palos Verdes, CA, United States
Speakers
Unlocking the Power of Real-World Evidence: The CFL-SASS Expert Consensus
Session Type: Issue Panel
Topics: Health Policy & Regulatory, Study Approaches, Methodological & Statistical Research
Track: Real-World Evidence (RWE)
Level: Intermediate
ISSUE: Real-world evidence (RWE) is now central to demonstrating the value of medicines, yet one of the field’s greatest challenges remains: how to communicate RWE compliantly, transparently, and impactfully to the decision makers who rely on it. FDA’s Consistent with FDA-Required Labeling (CFL) pathway offers a mechanism to do this, but uncertainty around what constitutes “scientifically appropriate and statistically sound” (SASS) evidence has limited its use.
OVERVIEW: This panel session will introduce the CFL-SASS Principles by Expert Consensus for RWE, the first multi-sponsor, expert-driven effort to clarify methodological and regulatory expectations for generating and communicating RWE under the CFL pathway. Speakers will each take 10 minutes to present the perspectives noted above, followed by questions for discussion and audience interaction. Attendees will learn about:
a) Why dissemination—not generation—is now the critical bottleneck for RWE impact
b) The opportunities and challenges of applying CFL-SASS evidence standards for RWE
c) The expert consensus recommendations addressing methodological and regulatory issues
d) How this work can strengthen internal review, improve evidence transparency, and elevate HEOR’s role in informing access and reimbursement decisions
The session will feature leading RWE, regulatory, and HEOR experts in a lively, interactive discussion on how this initiative can help the field unlock the full value of RWE
Moderator
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Paul Stang
Independent Consultant, Wyndmoor, PA, United States
Paul Stang, PhD is an independent consultant. He retired as Vice-President of Global Epidemiology at J&J after many years in academia, consulting, and the pharmaceutical industry where he held a number of positions of increasing responsibility. He has also held leadership positions in several public-private partnerships, guideline development efforts, and research collaborations. Dr. Stang has published widely in epidemiology, health outcomes, productivity, and communications. He continues to serve as a mentor to students and colleagues in several countries and serves as a reviewer for a number of clinical journals. He was elected a Fellow in 2004 to the International Society for Pharmacoepidemiology and still retains an adjunct faculty appointment at the University of North Carolina-Chapel Hill.
Speakers
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Daniel Malone, BS, RPh, PhD
University of Utah, Salt Lake City, UT, United States
Dr. Malone was trained as a pharmacist then attended graduate school to obtain his PhD. His career has been in academia (over 30 years) conducting research to improve the health and safety of patients requiring medication therapy. He is currently a Research Professor with the Department of Pharmacotherapy at the University of Utah College of Pharmacy. Dr. Malone has published over 300 articles, and his extramural research funding exceeds $12 million as Principal or co-Principal Investigator, with over $34 million in total funding. He was President of the International Society for Pharmacoeconomics and Outcomes Research from 2015 to 2016. Dr. Malone is a Fellow of the Academy of Managed Care Pharmacy and an American Foundation for Pharmaceutical Education fellow.
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Sissi Pham, PharmD
AESARA, Chapel Hill, NC, United States
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Richard Willke, PhD
Scintegral Health Economics, Soddy Daisy, TN, United States
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Denise Sánchez Palomo, MA, MS, JD
Opus Regulatory, New York, NY, United States
10:30 AM - 1:30 PM
Poster Session 3
Session Type: Research Posters
Poster Tours 11:45AM–12:30PM | Presenters will be with their posters from 12:30PM–1:30PM
11:30 AM - 12:00 PM
Closing the Clinical Impact Evidence Gap: Practical RWE Strategies for Medical Devices and Diagnostics Using Registries, Research Partners, and Regulatory Data
Session Type: Fast Facts
Topics: Medical Technologies, Health Technology Assessment, Real World Data & Information Systems
Track: Real-World Evidence (RWE)
Level: Intermediate
Purpose: This workshop explores pragmatic strategies for generating decision-grade real-world evidence to demonstrate clinical impact of medical devices and diagnostics when randomized controlled trials are impractical.
Description:
Medical devices and diagnostics typically reach market with less clinical evidence than pharmaceuticals, as regulatory pathways emphasize analytical performance rather than patient-relevant outcomes. This creates critical evidence gaps for HEOR and market access teams at launch. The cost, timelines, and feasibility constraints make pharmaceutical-style RCTs unrealistic for most device and diagnostic manufacturers, creating uncertainty for payers and delaying reimbursement despite promising clinical potential.
A central question is: what level and type of real-world evidence constitutes 'decision-grade' evidence for HTA and payer evaluations when RCTs are impractical?
This workshop explores scalable approaches using real-world data, hospital collaborations, national registries, and regulatory datasets to demonstrate clinical impact. Supporting ISPOR 2030 priorities on RWE readiness and modernizing HTA processes, the session presents three complementary perspectives:
Diagnostics HEOR perspective discusses leveraging regulatory, real-world, and post-market datasets to demonstrate clinical utility, and how structured collaborations with research partners accelerate evidence development.
Medical device HEOR perspective outlines best practices for designing clinically credible yet resource-efficient clinical impact studies supporting payer decision-making.
National registries perspective demonstrates how Scandinavian-style registry infrastructures enable low-cost, high-impact studies on utilization patterns, outcomes, device performance, and comparative effectiveness.
Panelists will present practical frameworks for early-lifecycle evidence generation, methodological considerations in non-randomized studies, and real-world examples of successful clinical impact assessments without RCTs.
Speakers
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Artem T Boltyenkov, MBA, PhD
Siemens Healthcare Diagnostics Inc., Lexington, SC, United States
Artem Boltyenkov is the Global Head of Health Economics and Outcomes Research (HEOR) at Siemens Healthineers Diagnostics. In this role, he leads international collaborations with leading hospitals to demonstrate how in-vitro diagnostic tests transform care pathways and improve patient outcomes.
He has more than 21 years of experience at Siemens Healthineers in Germany and the United States, holding a range of HEOR-focused roles in medical devices and diagnostics. His work includes multiple books and peer-reviewed publications in medical journals on HEOR topics.
Artem’s research focuses on the health economic evaluation of diagnostics, digital health applications, and medical devices. He earned his PhD in Health Economics (Dr. rer. oec.) from HHL Leipzig Graduate School of Management and an MBA from NYU Stern School of Business.
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Colleen F Longacre, MPH, PhD
Medtronic, Mounds View, MN, United States
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Mattias Kyhlstedt
ATHAGORAS Holding GmbH, Akersberga, Sweden
Mattias leads European Market Access and Real-World Evidence (RWE) at athagoras Medtech, a company delivering market access services across Western Europe and conducting RWE studies using some of the world’s most robust healthcare datasets.
He brings deep expertise in European reimbursement pathways for medical devices and digital health, and a strong understanding of the evidence requirements set by national health authorities. Drawing on extensive experience with Nordic RWE data, Mattias helps generate decision-grade evidence that supports regulatory and reimbursement discussions.
11:30 AM - 12:15 PM
Access and Policy Poster Tour
Session Type: Research Posters
This tour will take place during Poster Session 3, Posters will be hung from 10:30 AM - 1:30 PM.
Posters featured in this tour:
PT19: DOES BRAND-TO-BRAND COMPETITION REDUCE PRICES OF PRESCRIPTION DRUGS?
PT20: CHARACTERIZING THE U.S. MEDICAID POPULATION BY FEDERAL POVERTY LEVEL: DEMOGRAPHICS, REGIONAL PATTERNS, AND AFFORDABLE CARE ACT (ACA) EXPANSION STATUS TO ASSESS POLICY SHIFTS UNDER THE ONE BIG BEAUTIFUL BILL ACT (H.R.1)
PT21: INTERNATIONAL REFERENCE PRICING CAPS ARE HIGHLY DESIGN-SENSITIVE: CAP-SETTING COUNTRIES AND ACCESS SIGNALS FOR INCRETIN THERAPIES
PT22: ACCESS TO INNOVATIVE AUTOIMMUNE THERAPIES IN LATIN AMERICA: CROSS-COUNTRY EVIDENCE TO INFORM VALUE-BASED DECISION-MAKING
PT23: HOW THE EU JOINT CLINICAL ASSESSMENT UNCERTAINTIES IMPACT US PHARMACEUTICAL MARKET ACCESS
PT24: EVALUATING THE IMPACT OF THE INFLATION REDUCTION ACT OUT-OF-POCKET CAPS ON PATIENT ASSISTANCE FUNDS EFFICIENCY AND COVERAGE EXPANSION
Student Poster Tour
Session Type: Research Posters
This tour will take place during Poster Session 3, Posters will be hung from 10:30 AM - 1:30 PM.
Posters featured in this tour:
PT25: TRENDS IN PCSK9 INHIBITOR COSTS, COST SHARING, AND ADHERENCE AMONG MEDICARE BENEFICIARIES FOLLOWING 2018 PRICE REDUCTIONS
PT26: WHEN ADHERENCE ESTIMATES DIFFER: THE IMPACT OF DATA SOURCE AND GAP HANDLING IN REAL-WORLD MEDICATION USE ASSESSMENT
PT27: TRENDS IN INPATIENT COSTS AND DRIVERS OF HIGH-COST HOSPITALIZATIONS AMONG INDIVIDUALS WITH OPIOID USE DISORDER
PT28: REAL-WORLD SURVIVAL AND PREDICTORS OF MORTALITY IN HEMATOLOGIC MALIGNANCIES DURING AN ERA OF THERAPEUTIC ADVANCEMENT AND HEALTHCARE DISRUPTION: A POPULATION-BASED SEER STUDY
PT29: ECONOMIC EVALUATION OF BLINATUMOMAB PLUS CHEMOTHERAPY IN CHILDREN WITH STANDARD RISK B CELL ACUTE LYMPHOBLASTIC LEUKEMIA AT AVERAGE RISK OF RELAPSE IN HONG KONG
PT30: COST-EFFECTIVENESS ANALYSIS OF DPYD-GUIDED FOLFOX IN UNRESECTABLE METASTATIC COLORECTAL CANCER IN THE US: A PATIENT-LEVEL MICROSIMULATION MODEL
11:30 AM - 1:15 PM
Lunch Service (Exhibit Hall)
Session Type: General Meeting
As you enjoy your lunch in the Poster and Exhibit Hall, seize the opportunity to engage in meaningful conversations with fellow attendees. Take this time to exchange ideas, forge new partnerships, or simply enjoy casual conversations.
12:15 PM - 1:15 PM
A New Gold Standard for Valuing Health-Related Quality of Life? The Impact of the New UK EQ-5D-5L Utilities for HEOR and Decision Makers. A Value in Health Forum
Session Type: Forums
Topics: Methodological & Statistical Research, Health Service Delivery & Process of Care, Economic Evaluation
Track: Expanded Value Measures
Level: Intermediate
An important new source of UK utilities (‘value sets’) for health-related quality of life (HRQoL), as measured by EQ-5D-5L, was recently published in Value in Health (Rowen et al, 2026). Currently the subject of a NICE public consultation, this value set is likely to become the recommended source of utilities in submissions to NICE and, in effect, to become the new “gold standard.”
In this Forum, the key characteristics of this new value set and the methods used to generate it will be presented by Yemi Oluboyede on behalf of the UK research team. Our second speaker, Allan Wailoo, will present the results from an analysis of the effect of applying the new values in economic evaluation, compared to previous values endorsed by NICE. What impact will this new value set have on estimates of incremental quality-adjusted life years (QALYs) and incremental cost-effectiveness ratios—and for healthcare decisions? Our third speaker, Feng Xie will consider the wider implications of this work and the approaches taken by the UK research team for future research on HRQoL utilities worldwide. Does its use of time trade off signal a move away from online, self-completed discrete choice experiments, and a return to personal interviews? If US decision makers shift away from QALYs—toward Generalized Risk-Adjusted Cost-Effectiveness Analysis (GRACE), Equal Value of Life Years (evLY), or some other approach—what would the implications be for the HRQoL utilities that are needed?
This session will be moderated by Dan Ollendorf who will offer reflections on these presentations and highlight their relevance for reimbursement decisions and evidence to support pricing in the United States and elsewhere.
Moderator
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Dan Ollendorf, MPH, PhD
Institute for Clinical & Economic Review, Boston, MA, United States
Speakers
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Yemi Oluboyede, MSc, PhD
Putnam, Newcastle Upon Tyne, United Kingdom
Yemi leads the Patient-Reported Outcomes and Preference Elicitation team, where she plays a pivotal role in advancing health valuation research and utility measurement. She brings specialised expertise in the psychometric assessment and measurement properties of patient-reported outcome measures (PROMs).
Yemi’s research spans across numerous Health Technology Assessment (HTA) studies, including extensive work in rare disease areas. Her technical knowledge and leadership have made significant contributions to understanding patient perspectives and improving healthcare outcomes.
During her PhD, she developed one of the first patient-reported outcome measures designed specifically for adolescents in weight management. She also led the creation of an interactive digital tool that allowed young people with limited literacy, to self-report, how their condition affected them. Working in close collaboration with computer scientists, this approach was ahead of its time, bringing together digital innovation and health outcomes research to open new ways of engaging under-served populations. This work shows her ability to use digital technology to transform how PROs can be integrated into how patients’ voices can be captured.
In addition to her academic work, Yemi has successfully led the health economics component of numerous large, multidisciplinary randomised controlled trials, ensuring the robust integration of economic insights into trial outcomes.
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Allan Wailoo, BSc, MA, MSc, PhD
ScHARR, The University of Sheffield, Sheffield, United Kingdom
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Feng Xie, PhD
McMaster University, Hamilton, ON, ON, Canada
Recent Reforms in HTA, Pricing, and Public Procurement Across Latin America: Implications for Access and Sustainability
Session Type: Forums
Topics: Health Policy & Regulatory, Health Technology Assessment
Track: Access and Drug Pricing
Level: Intermediate
Latin American countries are implementing significant reforms in Health Technology Assessment (HTA), pricing, and public procurement to improve access to medicines while ensuring the sustainability of their health systems. These policy changes have direct implications for how evidence is generated, assessed, and applied in healthcare decision-making.
This Forum will explore recent and emerging policy reforms across the region, complemented by a regional perspective from the Pan American Health Organization (PAHO) on joint procurement mechanisms for high-cost medicines. The session will highlight how evolving HTA, pricing, and procurement approaches are reshaping access pathways and creating new opportunities for regional collaboration.
Moderator
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Diego Guarin, MPH, MSc, MD
Merck, Rahway, NJ, United States
Speakers
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Juliana Vallini, MPH, MSc
PAHO, Washington, DC, United States
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Marcos Santos, MSc, PhD
ISPOR Brazil Chapter, Sao Paulo, Brazil
Making Preferences Count: Patient-Engaged Values Clarification for Individual-Level Decision Making
Session Type: Forums
Topics: Patient-Centered Research, Methodological & Statistical Research
Level: Intermediate
Purpose: This joint Health Preference Research & Patient Centered Special Interest Group forum will showcase the integration of health preference research and patient engagement approaches to support patient and patient/provider shared decision making. This session will provide experience and evidence for using preference methods to inform individual treatment decisions while also following best practices in developing patient-focused decision support tools. Research shows that using structured, explicit activities (i.e., quantitative values clarification methods, or VCMs) to help patients clarify what matters most to them can:
• improve patient understanding
• reduce uncertainty, stress, and regret about decisions
• help patients choose treatments that better match their personal values
Health preference research (HPR) methods are appealing for use as individual-level VCMs in tools like patient decision aids. A systematic literature review conducted by the Health Preference SIG found limited guidance for developing, testing, and aligning HPR methods within patient decision support tools. Further, the patient-centeredness of HPR as VCMs has not been well established. This forum addresses that gap by offering practical guidance that integrates best practices from patient engagement, medical decision-making, communication science, and psychology.
Dr. van Bemden will introduce decision support tools, explain how patients should be engaged in their development, and summarize evidence of benefits. She will focus on what makes decision support tools patient-centered. Dr. Peay will moderate and explain how established methods and evidence from other disciplines apply to quantitative, preference-based tools, and when health preference–based VCM are (and are not) appropriate and patient-centered. Dr. Poulos will discuss how to develop, test, and evaluate HPR methods for use in individual-level decision support. Dr. Van Til will review prior research on HPR methods as VCM, articulate gaps and research priorities, and discuss challenges that arise when developing patient-engaged decision support tools in both academic and industry settings.
Moderator
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Holly Peay, MS, PhD
Faegre Drinker Biddle & Reath, Washington, DC, United States
Speakers
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Angie Botto-van Bemden, PhD
Musculoskeletal Research International, Holiday, FL, United States
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Christine Poulos, PhD
RTI- Health Solutions, Research Triangle Park, NC, United States
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Janine van Til, MSc, PhD
University of Twente, Enschede, Netherlands
Aligning HEOR With Global Policy Shifts: How Should We Lead and Influence?
Session Type: Forums
Topics: Health Policy & Regulatory, Organizational Practices, Health Technology Assessment
Track: Professional Development
Level: Intermediate
Purpose: To examine the role of HEOR evidence in shaping health policy across geographic regions and to assess how convergence between US and ex-US markets through mechanisms such as Most Favored Nation (MFN) and International Reference Pricing (IRP) is influencing global pricing and access decisions. The session will highlight how diverse stakeholders across the healthcare ecosystem can collaborate to advance policies informed by HEOR, ensuring that emerging pricing and access frameworks support sustainable, equitable, and evidence-based decision making.
Description: The session will open by setting up the global policy context, including how MFN and IRP mechanisms are reshaping pricing and access across regions (10 minutes, Sulabha). This will be followed by discussion on the evidence base that informs policy, with emphasis on the critical role of HEOR in drug pricing reforms and HTA frameworks (10 minutes, Ravinder). Perspectives on multistakeholder partnerships and shared goals across the ecosystem will be presented next (10 minutes, Bruce). A viewpoint on how HEOR can complement and collaborate with other internal functions within pharmaceutical and medical device organizations will follow (10 minutes, Arturo). The session will conclude with practical translation of policy into access strategy, including real-world examples where HEOR insights should be central to addressing access challenges (10 minutes, Malinda). The session will end with panel questions, audience Q&A, and a summary that encourages reflection on regional nuances and strategies for strengthening evidence-driven health policy through collaborative engagement (10 minutes, Sulabha).
Moderator
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Sulabha Ramachandran, PhD
GlaxoSmithKline, West Chester, PA, United States
Speakers
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Arturo Cabra, BS, MSc
GE HealthCare, Miami, FL, United States
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Ravinder Dhawan, PhD
Pfizer, Watchung, NJ, United States
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Bruce Feinberg
Cardinal Health, Dublin, OH, United States
Dr. Feinberg is a nationally recognized expert in oncology, specialty medicine and the business of healthcare. His research has spanned 4 decades encompassing novel therapeutics, clinical pathways, evidence-based medicine, and fit for purpose real world data (RWD) methods enabling external controls for regulatory approvals. A sought-after researcher and speaker on healthcare policy, value-based care and RWD research, Dr. Feinberg has over 200 publications in peer-review; is the author of Breast Cancer Answers and Colon Cancer Answers and host of the Weekly Check-Up podcast and radio show.
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Priya Jain, MBA, MSc
Thermo Fisher Scientific, Belmont, CA, United States
Priya Jain, is a seasoned life sciences leader with 18+ years of global biotech and pharmaceutical experience. She specializes in commercial strategy, market access, and new product launches, helping organizations define value, shape go-to-market approaches, and drive successful launches across diverse therapeutic areas.
Advancements in Real-World Evidence (RWE) to Accelerate Access in Rare Cancers: Challenges, Methods, and Decision-Making
Session Type: Forums
Topics: Real World Data & Information Systems, Health Technology Assessment, Study Approaches
Track: Real-World Evidence (RWE)
Level: Intermediate
Advances in the development and real-world use of therapies for rare cancers are occurring rapidly. Real-world evidence (RWE) is increasingly important for market-access (MA) decisions because clinical development programs for rare cancers are often constrained by small sample sizes, single-arm trials, and immature endpoints. Despite greater availability of real-world data (RWD), payers and health-technology assessment bodies (HTAbs) remain cautious about the credibility, generalizability, and decision relevance of RWE generated in rare cancer settings. Equally important, yet seldom discussed, are the practical and methodological challenges of generating high-quality RWE in rare cancers with respect to MA decisions.
The ISPOR RWE- and Oncology-SIGs jointly propose a multidisciplinary panel to close this gap by bringing together perspectives from academia, industry, HTAbs, and payers. The session will pinpoint common barriers, methodological challenges, and discuss potential evidence frameworks to enhance confidence in RWE for MA decisions.
Moderator (Shilpi Swami) will set the stage with access challenges in rare cancer, why conventional evidence paradigms often fall short, and introduce the role of RWE across the evidence lifecycle.
• The first panelist, Jagadeswara Rao Earla, will focus on practical realities and challenges of generating RWE in rare cancers (example: data sources, small sample size).
• The second panelist, Sandipan Bhattacharjee (bringing perspectives of an academic rigor alongside industry applications), will focus on methods for how RWE advancements (example: external control arms, target trial emulation, artificial intelligence application) can improve the credibility of evidence generated in rare cancer settings.
• The third panelist, Diana Brixner will discuss how RWE is interpreted and used by HTAbs and payers in MA decisions for rare cancers.
The panel (40-45 minutes of total presentation and remaining time for Q&A) will provide MA, evidence generation, and policy stakeholders with a potential practical framework for evaluating the strengths and limitations of RWE in rare cancers.
Moderator
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Shilpi Swami
ConnectHEOR, London, United Kingdom
As Vice President of Consulting and Strategy at ConnectHEOR, Shilpi Swami provides both scientific and strategic leadership, guiding evidence generation and market access initiatives across the globe. She also serves as Chair-Elect of the ISPOR Oncology Special Interest Group and is a frequent speaker at leading scientific and policy forums, where she brings clarity and authority to complex healthcare access challenges. Shilpi is an internationally recognized leader in consulting, named among the World’s Top 25 Women Leaders in Consulting 2025 – a distinction that spans the entire consulting industry. Her multidimensional career – spanning academia, consulting, and biopharma equips her with a rare ability to bridge perspectives across research, policy, and industry. She has led numerous high-stakes HTA submissions and access strategies, combining methodological rigor with practical solutions that resonate with regulators, payers, and biopharma stakeholders. Shilpi is widely respected not only for her expertise but also for her people-first approach. She embodies the belief that Kindness is Cost-Effective™, demonstrating that strength in leadership comes from pairing scientific excellence with empathy, collaboration, and impact.
Speakers
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Jagadeswara Rao Earla, MBA, PharmD, PhD
Merck & Co. Inc, Rahway, NJ, United States
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Sandipan Bhattacharjee, MS, PhD
Bayer U.S. LLC, Belle Mead, NJ, United States
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Diana Brixner, RPh, PhD
University of Utah, Salt Lake City, UT, United States
The Evolving RWE Executive: Navigating AI Disruption and Changing Data Preferences
Session Type: Forums
Topics: Organizational Practices, Health Technology Assessment, Real World Data & Information Systems
Track: Real-World Evidence (RWE)
Level: Introductory
This breakout session examines how the role of the real-world evidence (RWE) executive is evolving in response to rapid advances in artificial intelligence (AI) and continued skepticism from payers and health technology assessment (HTA) bodies. As AI-enabled tools increasingly automate core evidence-generation activities, RWE leaders must shift from primarily technical execution toward strategic interpretation, governance, and stakeholder engagement. At the same time, coverage, pricing, and appraisal decisions continue to prioritize randomized controlled trial evidence, limiting the influence of RWE. This session will define the emerging RWE executive profile, identify key leadership competencies, and frame practical considerations for ensuring AI-enabled RWE remains credible, decision-relevant, and fit for payer and HTA decision-making contexts.
Moderator Doug Foster will introduce how artificial intelligence (AI) is transforming real-world evidence (RWE) generation and why payer and health technology assessment (HTA) skepticism toward observational evidence persists. He will frame the strategic challenge for RWE leaders as AI accelerates evidence production while decision-makers remain cautious about its use.
The first panelist, Shuvayu Sen, will discuss the pharmaceutical executive perspective on how RWE leadership roles and priorities are evolving as AI automates traditional analytical work. The second panelist, Rachele Hendricks-Sturrup, will provide an academic and policy perspective on credibility expectations of regulators, HTA bodies, and payers, and whether AI-enabled methods can address concerns around rigor and transparency. The third panelist, Stephanie Reisinger, will present the technology perspective on operationalizing AI-enabled RWE at scale and its implications for evidence quality and trust.
This panel (40–45 minutes of discussion with remaining time for Q&A) will offer RWE, HEOR, and market-access stakeholders practical insight into how the RWE executive role must evolve to remain relevant in payer and HTA decision-making.
Moderator
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Doug Foster, MBA
Advanced Data Sciences LLC, San Francisco, CA, United States
Speakers
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Shuvayu Sen, PhD
Merck & Co., Rahway, NJ, United States
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Rachele Hendricks-Sturrup, MA, MSc
Duke-Margolis Center for Health Policy, Washington, DC, United States
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Stephanie Reisinger, MBA
Flatiron Health, Etters, PA, United States
12:45 PM - 1:15 PM
Hidden In Plain Sight: How Social Value Modeling Can Assess The Whole Health Value Of Innovative Medicines
Session Type: Fast Facts
Topics: Economic Evaluation, Health Technology Assessment, Patient-Centered Research
Track: Expanded Value Measures
Level: Intermediate
To deliver on ISPOR’s Strategic Plan 2030, HEOR must move beyond cost/QALY to a whole health–oriented, productivity-based social value framework that captures both paid labor and unpaid household and caregiving contributions through social value modelling (SVM). Demonstrating medicines’ social value via SVM enables decision-makers to weigh access, equity, affordability, sustainability, wellbeing, and economic resilience alongside traditional cost-effectiveness when making coverage, pricing, payment, and non-medical investment decisions. In this session, Dr. Biskupiak reviews current treatment of social value in drug evaluation, Prof. Ostwald shows how SVM quantifies macroeconomic impacts of health investments on prosperity, and Dr. Steuten explains how social value supports more explicit and defensible trade-offs in public-health and coverage priorities.
Moderator
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Joseph Biskupiak, MBA, PhD
University of Utah, Salt Lake City, UT, United States
Speakers
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Dennis A Ostwald, PhD
WifOR Institute, Darmstadt, Germany
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Lotte Steuten, MSc, PhD
Office of Health Economics, London, United Kingdom
Lotte Steuten, PhD Deputy Chief Executive of the Office of Health Economics; former Member, Board of Directors, ISPOR
Prof Lotte Steuten is deputy chief executive of the Office of Health Economics (OHE), the world’s oldest independent health economics research organization, based in London, UK, and a globally recognized expert in health economics and outcomes research (HEOR).
Her research addresses challenges in valuing and paying for innovative therapies, with the aim of achieving effective, accessible, affordable, and efficient healthcare for all. She has published over 150 peer-reviewed papers on topics including the value of novel treatments, diagnostics and prevention for a wide range of non-communicable and infectious diseases.
With 2 decades of experience across Europe, the United States, and Asia Pacific, she advises governments, industry, and other organizations worldwide. She is frequently sought by media and international stakeholders for expert commentary on HEOR, value assessment, health policy innovation, and evolution of health technology assessment globally.
Alongside her position at OHE, Prof Steuten is a visiting honorary professor at City St George’s, University of London. Prior to joining OHE, she held academic faculty positions at the Fred Hutch Cancer Research Center and the University of Washington in the United States. She earned her PhD (with honors) from Maastricht University in the Netherlands.
1:45 PM - 2:45 PM
Making Caregiver Impact Count: Bridging the Evidence-to-Policy Gap in Value Assessment and Decision-Making
Session Type: Workshop
Topics: Health Technology Assessment, Patient-Centered Research, Real World Data & Information Systems
Track: Expanded Value Measures
Level: Intermediate
Despite contributing an estimated $600 billion in unpaid labor annually, caregivers remain underrepresented in health technology assessments (HTAs) and health policy frameworks. This workshop aims to describe key gaps and propose actionable solutions to systematically integrate caregiver impacts into HTA and policy decisions, based on results from a landscape review and the outputs from a recent, iterative, multi-stakeholder deliberation process.
R. Brett McQueen will summarize the outputs from the multi-stakeholder deliberation, revealing stakeholder-prioritized caregiving data and voting results, highlighting economic and longitudinal evidence most useful for current decision-making contexts (10 mins). Stacey Kowal will present how validated tools, such as the Zarit Burden Interview, Caregiver Reaction Assessment, Work Limitations Questionnaire, and Short-Form Health Survey, can produce relevant evidence across disease severity stages that is fit for purpose for health policy and HTA (10 mins). Yadira Montoya will outline the opportunities and challenges for collecting caregiver impact data through patient advocacy organizations along with feasible options for broadening collection of these data (10 mins). Audience participation will include live polling to understand experiences with collecting caregiver impact data and priorities for future evidence generation. This workshop will be valuable for a broad coalition of stakeholders interested or currently using caregiver impact data including but not limited to: policymakers strengthening caregiver support and guiding funding; Prescription Drug Affordability Boards and HTA bodies incorporating caregiver evidence into deliberations; employers and advocacy groups enhancing workplace policies and protections in support of caregivers; and researchers embedding caregiver outcomes in economic models.
Moderator
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Robert B McQueen, BA, MA, PhD
University of Colorado Skaggs School of Pharmacy and Pharmaceutical Science, Aurora, CO, United States
R. Brett McQueen is the director for the Center for Pharmaceutical Value (pValue) at the University of Colorado Skaggs School of Pharmacy and Pharmaceutical Sciences, where he is an associate professor in the Department of Clinical Pharmacy. Brett’s work includes comparative effectiveness research, cost-effectiveness applications and methods development, multi-criteria decision analysis, outcomes-based contracting, and patient preferences research. He is active in ISPOR through contributions to short courses, workshops, issue panels, and research presentations.
Speakers
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Stacey Kowal, BS, MSc
Genentech, Alameda, CA, United States
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Yadira Montoya, MS
National Alliance for Caregiving, Washington, DC, United States
The GenAI Paradox for Qualitative Evidence Summarization: Exploring Real-World Use Cases and Validation Frameworks for Understudied but Impactful Use Cases
Session Type: Workshop
Topics: Patient-Centered Research, Real World Data & Information Systems, Study Approaches
Track: AI
Level: Intermediate
PURPOSE: As HEOR embraces generative AI (GenAI) to improve efficiency, an important paradox has emerged. GenAI adoption overwhelmingly targets structured computational tasks (modeling, network meta-analysis, systematic literature reviews), with supporting ISPOR guidance: ELEVATE-AI and CHEERS-AI. However, tasks using largely unstructured qualitative data remain underexplored despite GenAI's potential to excel in critical HEOR workflows: synthesizing evidence repositories, analyzing patient experience data (PED), including patient interviews or social media data sources, and informing study design. This workshop shares validation approaches for GenAI applications in qualitative evidence generation and summarization.
DESCRIPTION: Katelyn Keyloun (Arysana) will provide a 5-minute overview describing emerging validation approaches for probabilistic Large Language Models (LLMs) using largely qualitative unstructured data. The audience will explore new approaches from Panelists representing multidisciplinary perspectives, who will present real-world applications (30 minutes total) describing how AI processes, analyzes, and summarizes unstructured qualitative data, emphasizing validation approaches:
1. Conversational AI for Data Collection (Bill Byrom, Signant Health): LLM-powered chatbots conducting qualitative in-trial patient interviews, including validation of interview technique quality, transcript generation, and reporting capabilities versus traditional human approaches.
2. Generate Early Patient Insights from Social Media (Catherine Foley, AbbVie): Leveraging GenAI to extract and synthesize patient perspectives from digital communities, addressing validation challenges for patient-generated content and early signal detection.
3. LLMs for Study Design (Justyna Amelio, AbbVie): Applying GenAI to inform study design decisions and protocol development by synthesizing evidence across multiple sources, and validating AI-generated recommendations.
Interactive audience participation (20 minutes) includes polls and moderated discussion exploring opportunities in adopting GenAI, including validation, implementation barriers, and organizational readiness.
Moderator
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Katelyn Keyloun, BS, MS, PharmD
Arysana, Carson City, NV, United States
Speakers
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Bill Byrom, PhD
Signant Health, Nottingham, United Kingdom
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Catherine Foley, MA, MPH
AbbVie, Milton, MA, United States
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Justyna Amelio, PhD
AbbVie, Maidenhead, United Kingdom
Incorporating Patient, Family, and Public Perspectives to Advance Novel and Societal Elements of Value in Value Assessment
Session Type: Workshop
Topics: Methodological & Statistical Research, Patient-Centered Research, Economic Evaluation
Track: Expanded Value Measures
Level: Intermediate
PURPOSE:
Interest in expanding value and health technology assessments (V/HTAs) to incorporate novel elements of value in the broader societal perspective (e.g., option value, family/caregiver spillover) has grown rapidly. However, theoretical and methodological progress has outpaced the generation of patient-, family-, and stakeholder-informed evidence to support the integration of these elements of value in V/HTAs. This workshop will feature proof-of-concept applications to illustrate how incorporating diverse stakeholder perspectives can strengthen the development, prioritization, and application of novel value elements in V/HTAs.
DESCRIPTION:
Workshop attendees will gain practical insight into approaches for integrating diverse stakeholder perspectives in operationalizing broader value elements. Dr. Yang will present how stakeholder inputs—spanning families, school personnel, and community members —informed the development and implementation of a societal value framework for pediatric vaccination, using COVID and flu as examples (10 minutes). Dr. Li will present results from a national survey of cancer patients and caregivers assessing preferences related to preserving access to future innovations, demonstrating how stakeholder-derived evidence can inform the use of option value in V/HTAs (10 minutes). Dr. Slejko will present research on U.S. public preferences related to equity and findings from a multistakeholder eDelphi study that can guide recommendations on methods and needs for patient-centered V/HTAs (15 minutes). Finally, Dr. Xie will synthesize and discuss the practical strategies of incorporating stakeholder input in operationalizing novel elements of value in V/HTAs, and potential implications for patient welfare.
Audience participation will include live polling, Q&A, and facilitated brainstorming on where patient and stakeholder input is most valuable and how these perspectives can be incorporated into the development and quantification of broader value elements (20 minutes).
Moderator
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Richard Xie, PhD
RA Capital Management, Newton, MA, United States
Speakers
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Meng Li, MS, PhD
Tufts Medical Center; Stifel, Boston, MA, United States
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Julia F. Slejko, PhD
University of Maryland Baltimore, Baltimore, MD, United States
Dr Julia F. Slejko is associate professor in the Department of Practice, Sciences, and Health Outcomes Research at the University of Maryland School of Pharmacy. She serves as co-director of the Patient-Driven Values in Healthcare Evaluation Center and as director of the Pharmaceutical Health Services Research Graduate Program.
Dr Slejko earned her BA in molecular, cellular, and developmental biology from the University of Colorado Boulder and her PhD with a focus on pharmacoeconomics from the University of Colorado School of Pharmacy Center for Pharmaceutical Outcomes Research. She completed postdoctoral training at the University of Washington School of Pharmacy. Prior to her doctoral training, she spent 7 years in drug discovery at Array BioPharma in Boulder, Colorado.
Her research focuses on real-world health economics and outcomes research, economic modeling applications, and patient-informed value assessment. Her recent projects included multistakeholder consensus on patient-centered value assessment and US public preference elicitation of health inequality aversion.
Dr Slejko is active in ISPOR, serving as co-lead of the Women in HEOR initiative, associate editor at Value in Health, and member of the Health Science Policy Council. She was co-chair of the Faculty Advisor Council 2023-2025.
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Jingyan Yang, DrPH
Pfizer Inc., New York, NY, United States
Coordinating the Quagmire: Real World Evidence in Value Assessment in Later Stages of the Product Lifecycle
Session Type: Issue Panel
Topics: Real World Data & Information Systems, Health Policy & Regulatory, Health Technology Assessment
Track: Real-World Evidence (RWE)
Level: Intermediate
ISSUE: Value assessment of a medicine at the middle or end of its lifecycle could benefit from much richer evidence base compared to launch and should be heavily informed by real-world evidence (RWE) on the patients who actually used the treatment in practice. Yet, there remains significant variability in how RWE is used to inform the value of pharmaceuticals post-launch. In the US, IRA negotiations involve submission of comparative RWE, with the extent of its use in CMS pricing decisions remaining unclear. In ex-U.S. markets, use of RWE in HTA reassessments and “living HTA” are increasingly of interest, with experience so far revealing the potential for these extensions of HTA to significantly change from value assessment at launch. This panel will propose a roadmap outlining how innovators can strategically plan post-launch RWE generation to meet long term evidence needs across the product lifecycle in US and key ex-US markets.
OVERVIEW: Moderator will begin with presentation on the overview of the Issue.
Panelist 1 will discuss US IRA experience on comparative RWE evaluation within the context of Price Negotiations.
Panelist 2 will discuss role of RWE in HTA reassessments and as a component of living HTA.
Panelist 3 will provide ISPOR and HEOR community perspective in the convergence of RWE and HTA activities.
All Panelists will present their perspectives on the critical elements of a roadmap to anticipate post-launch RWE needs and how to streamline this process.
Moderator
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Ambarish J. Ambegaonkar, PhD
APPERTURE LLC, Marlboro, NJ, United States
Speakers
Heterogeneity and Uncertainty in Economic Modeling
Session Type: Research Podiums
Characterizing the impact of heterogeneity and uncertainty in economic evaluations must be planned for in the model development stage. This session explores methodological considerations related to heterogeneity as a deciding factor between cohort and individual-level modeling approaches, structural uncertainty in model health state selection, and the quantification and visualization of parameter uncertainty.
Moderator
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William L Herring, PhD
RTI- Health Solutions, Research Triangle Park, NC, United States
Will Herring, PhD, is an Executive Director in the Health Economics group at RTI Health Solutions with expertise in cost-effectiveness and value-based pricing modeling. His primary research focus is economic modeling and value assessment for chronic progressive diseases (e.g., Alzheimer’s disease [AD], chronic liver diseases, chronic lung diseases, multiple sclerosis, sickle cell disease, diabetic retinopathy, transthyretin amyloidosis), with a special interest in the use of patient-level simulation methods for these conditions. He is Affiliated to Research at the Karolinska Institutet and is a member of the steering committee for the International Pharmaco-Economic Collaboration for Alzheimer's Disease (IPECAD) Modelling Group.
UNCERTAINTY PROBABILITY THRESHOLDS AND INSUFFICIENT ITERATIONS OF PROBABILISTIC SENSITIVITY ANALYSIS IN ECONOMIC EVALUATION
OBJECTIVES: This cross-sectional study investigated the application and reporting of probabilistic sensitivity analysis (PSA) in recent economic evaluations, with a focus on the consistency between reported probability thresholds and stated cost-effectiveness conclusions.
METHODS: We searched PubMed for full economic evaluations published between January 1, 2023, to March 18, 2025, in journals ranked within the top 5% by Journal Impact Factor across 51 Clinical Medicine subcategories according to the Journal Citation Reports. Two independent reviewers extracted data on study design, perspective, research domain, outcome type, specific PSA methods, iteration details, and corresponding conclusions.
RESULTS: From 591 initially retrieved studies, 363 met the inclusion criteria. Of these, 302 studies (83.20%) employed PSA. However, over 30% did not specify the PSA method used, and approximately 15% did not report the probability. The majority of studies performed 1,000 (35.10%, 106/302) or 10,000 (33.77%, 102/302) iterations, though nearly 3% used fewer than 1,000 iterations with 80% of these preliminarily confirmed as insufficient. Among studies using health-adjusted life years (HALYs) with a predefined cost-effectiveness threshold, 80.53% of studies concluded the intervention was “cost-effective,” while 19.91% deemed it “not cost-effective.” Importantly, the median minimum probability in “cost-effective” studies was 86.95% (IQR: 66.40%-99.00%), whereas the median maximum probability in “not cost-effective” studies was 20.00% (IQR: 4.30%-37.00%). However, notable inconsistencies were observed: 38.45% of “cost-effective” studies reported probabilities below 75%, 13.72% below 60%, and 6.04% below 50%. Conversely, 11.11% of “not cost-effective” studies reported probabilities above 50%.
CONCLUSIONS: This study demonstrated that similar reported probability can lead to divergent interpretations of economic conclusions due to the absence of a consensus on PSA probability cutoffs. Furthermore, insufficient iteration numbers may compromise the methodological rigor and reliability of economic evaluations.
COMPARING THREE- AND FOUR-HEALTH-STATE SEMI-MARKOV MODELS DERIVED FROM A COMMON DISCRETE-EVENT SIMULATION IN EARLY-STAGE ONCOLOGY
OBJECTIVES: Cohort-based semi-Markov models in oncology often differ in structural complexity, particularly in how post-progression disease states are represented. This study compared outcomes from three-health-state (3HS) and four-health-state (4HS) semi-Markov models derived from the same underlying patient-level data, using a discrete-event simulation (DES) as a common ground-truth generator.
METHODS: A lifetime DES generated patient-level event histories across event-free (EF), locoregional recurrence (LR), distant metastasis (DM), and death for two treatments. These data were used to parameterize a 3HS semi-Markov model (EF, progressed disease [PD], death) and a 4HS model (EF, LR, DM, death). One-off treatment costs were applied using DES-derived mean time on treatment. Outcomes included life-years, state occupancy, costs, and incremental effects.
RESULTS: In the base case analysis, the models showed close agreement. The model estimates of lifetime incremental LYs, QALYs, and costs were 0.99, 0.88, and $25,316 for the 4HS model and 0.99, 0.88, and $25,304 for the 3HS model. These compared closely with DES estimates of 1.00, 0.88, and $26,433. One-way sensitivity analysis revealed deviations between the 3HS and 4HS models of less than 5% across all parameters. Scenario analysis tested progression patterns in which the split between LR and DM following EF varied substantially over time (e.g., early-slow and late-fast EF to LR with the opposite for EF to DM). These scenarios showed larger differences between the two models, with the 3HS model tracking DES outputs more closely. Additional scenarios showed limited impact on outcomes, including a functional cure component in EF and use of median rather than mean time on treatment.
CONCLUSIONS: When derived from a common data source, 3HS and 4HS semi-Markov models rarely yielded meaningfully different results due structural choice. However, differences may emerge under alternative progression schemes (particular to the underlying disease), underscoring the importance of evaluating structural uncertainty when selecting model structure.
MODELLING HETEROGENEITY WITHOUT INDIVIDUAL SIMULATION: STRUCTURAL CHOICES AND SAMPLING STRATEGIES
OBJECTIVES: Heterogeneity in patient characteristics is frequently cited as justification for individual patient simulation (IPS) models. This conflates heterogeneity with stochastic simulation and obscures situations in which cohort-based models, applied to individuals or subgroups, are preferable. We examine when heterogeneity necessitates IPS, when cohort models remain sufficient, and how heterogeneous cohorts should be sampled and results presented to support transparent decision-making.
METHODS: We distinguish three modelling dimensions: (i) representation of heterogeneity (observed covariates and their joint distribution), (ii) simulation architecture (cohort vs individual), and (iii) stochasticity. We compare cohort models applied at the individual level, stratified cohort models, and IPS models against policy-relevant criteria: preservation of correlated covariates; computational burden; and interpretability of results. We examine approaches to sampling heterogeneous cohorts to maintain correlation between risk factors. Findings are illustrated using a recently presented Scottish Cardiovascular Policy Model.
RESULTS: Heterogeneity alone does not require IPS. When outcomes are deterministic conditional on baseline covariates and transitions depend only on current state and time, cohort models evaluated across individuals or finely defined strata recover identical expected values with greater transparency and lower computational cost. IPS becomes necessary when path dependence, risk factor-based treatment choice, or endogenous events introduce within-individual stochasticity that cannot be represented analytically. Naïve independent sampling of covariates materially distorts risk distributions and outcomes; preserving correlation is essential regardless of simulation type. Presenting results solely as population means conceals distributional consequences of heterogeneity; reporting of outcome distributions and subgroup effects materially improves interpretability and policy relevance.
CONCLUSIONS: The choice between cohort and individual simulation models should be driven by structural requirements, not the mere presence of heterogeneity. Clear separation of heterogeneity, correlation, and stochastic simulation can prevent unnecessary model complexity while improving transparency. Policy models should justify simulation architecture explicitly, preserve correlated risk structures, and report distributional outcomes alongside means.
THE CE STAR: A NEW FIGURE TO ENHANCE ONE-WAY SENSITIVITY ANALYSES
OBJECTIVES: Uncertainty in the cost-effectiveness of a new intervention is often evaluated in a one-way sensitivity analysis (OWSA) and displayed with a tornado diagram. This approach, however, does not work well when the resulting ICER bounds for at least one parameter (1) are both lower (or greater) than the base case ICER and/or (2) include both a positive and negative value. In these situations, interpretation of the tornado diagram can be difficult, and identification of the most influential parameters may be misleading. We propose a new graphical display - the CE Star - to supplement the traditional tornado diagram in the OWSA.
METHODS: The CE Star is formed by plotting the (ΔQALYs, ΔCost) points to the upper and lower bound values for each parameter in the standard OWSA and then connecting each pair of points from the same parameter. The relative importance of a parameter is determined by the Euclidean distance between these two points, with greater distance associated with greater importance. We compare the CE Star to the tornado diagram in a hypothetical example and from a published cost-effectiveness model.
RESULTS: In the hypothetical case, the tornado diagram and CE Star produced different rank orders of influential parameters. The CE Star was uniquely able to identify the importance of those parameters whose lower and upper bounds led to opposite ICER interpretations (e.g., cost-effective versus not cost-effective intervention). Further, the CE Star preserved the rank ordering of influential parameters under fixed relative changes to the parameter variability, while the tornado diagram did not. Application of the CE Star and tornado diagram in a published model revealed differences in the list of influential parameters.
CONCLUSIONS: When conducting an OWSA, the CE Star should be created to supplement the traditional tornado diagram to ensure appropriate identification and interpretation of influential parameters.
Expanding the Societal Perspective in Economic Evaluation
Session Type: Research Podiums
This podium session brings together four timely studies that advance the measurement and application of the societal perspective in health economic evaluation. Collectively, the presentations address how broader costs and consequences—productivity impacts, health system disruptions, and climate-related health losses—can be rigorously quantified and incorporated into decision-making.
The session begins with a practical framework for estimating productivity loss using U.S. public-use data, offering applied guidance for researchers seeking to operationalize societal cost components. It then presents real-world evidence on the economic burden of maternal health service disruptions in conflict-affected Sahelian Nigeria, highlighting the intersection of instability, access to care, and health outcomes. A third presentation examines a critical gap in the social cost of carbon by valuing health losses attributable to climate change, underscoring the importance of integrating health impacts into climate policy analyses. The session concludes with a systematic analysis of how the “societal perspective” is defined and implemented in ICER assessments of ultra-rare diseases.
Together, these studies demonstrate methodological innovation and practical insights for strengthening comprehensive, policy-relevant economic evaluation across diverse contexts.
Moderator
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Eberechukwu Onukwugha, MSc, PhD
University of Maryland, Baltimore School of Pharmacy, Baltimore, MD, United States
Eberechukwu Onukwugha, PhD is a Professor in the Department of Practice, Sciences, and Health Outcomes Research and Executive Director of Pharmaceutical Research Computing at the University of Maryland School of Pharmacy. She received a Doctor of Philosophy in economics (concentration: econometrics) from Virginia Polytechnic Institute and State University (Virginia Tech). Dr. Onukwugha completed a two-year postdoctoral fellowship in pharmacoeconomics and health outcomes research at the University of Maryland School of Pharmacy. She was a recipient of the PhRMA Foundation’s Post-Doctoral Fellowship in health economics and outcomes research. Dr. Onukwugha’s research interests are in cost analysis, health disparities, and medical decision-making by individuals and institutions. She has approximately 20 years of experience conducting health economics and outcomes research using administrative medical and pharmacy claims, hospital discharge, and prospectively-collected data. Dr. Onukwugha has authored or co-authored over 140 peer-reviewed articles in health economics and outcomes research. She is an Editorial Board member for PharmacoEconomics and an Associate Editor for Ethnicity & Disease. Dr. Onukwugha serves as President, ISPOR Board of Directors, 2024-2025, and serves on the Maryland Prescription Drug Affordability Board.
ECONOMIC BURDEN AND REAL-WORLD EVIDENCE OF MATERNAL HEALTH SERVICE DISRUPTIONS IN CONFLICT-AFFECTED SAHELIAN NIGERIA
OBJECTIVES: Health service disruptions driven by armed conflict remain a major barrier to maternal health in Nigeria’s Sahel region. Understanding these pathways is essential to guide resource allocation and policy in fragile settings. The study aims to quantify the economic burden associated with conflict-related maternal health service disruptions and assess real-world utilization patterns among women of reproductive age in conflict-affected Sahelian LGAs in Borno, Yobe, and northern Adamawa States.
METHODS: A cross-sectional study using real-world data from 18 primary healthcare facilities and 1,247 women (15-49 years) was conducted from January to September 2025. Facility-level metrics were linked with household cost data obtained through two-stage cluster sampling. Direct medical costs, direct nonmedical costs, and productivity losses were estimated using a microcosting approach from the societal perspective. Insecurity intensity was measured using a monthly incident index derived from ACLED event classifications. Service disruption scores were constructed using modified WHO Service Availability and Readiness indicators. Multivariable logistic regression evaluated associations between insecurity and facility-based maternal service utilization.
RESULTS: Sixty-four percent of facilities reported conflict-related disruptions, resulting in a 23% decline in ANC attendance and a 31% reduction in skilled birth deliveries. The mean cost per pregnancy episode in high-conflict LGAs was US$118 compared with US$44 in low-conflict areas, with productivity losses comprising 41% of total costs. Transportation, out-of-pocket fees, and informal payments accounted for 63% of nonmedical expenditures. Women residing ≥5 km from disrupted facilities had significantly lower odds of facility delivery (aOR 0.48; 95% CI: 0.36-0.64). Facilities experiencing ≥3 insecurity incidents monthly were more likely to report stockouts of essential maternal commodities (p < 0.01).
CONCLUSIONS: Conflict markedly increases maternal healthcare costs and reduces facility utilization across Sahelian Nigeria. These findings provide critical HEOR evidence to inform conflict-sensitive financing models, strengthen service delivery, and guide resource allocation for maternal health resilience in fragile settings.
WHAT DOES A “SOCIETAL PERSPECTIVE” INCLUDE IN PRACTICE? A SYSTEMATIC ANALYSIS OF ICER ASSESSMENTS IN ULTRA-RARE DISEASES
OBJECTIVES: To address limitations of a health system perspective in evaluating the cost effectiveness (CE) of therapies for ultra-rare diseases (defined as US prevalence <10,000; no trials in populations >10,000), ICER employs a modified value framework that presents base-case CE results (health system perspective) alongside the societal perspective scenario analyses when societal costs are considered substantial relative to health care costs. The objective of this study was to assess which societal cost components are included in these ICER ultra-rare disease assessments in practice and how their inclusion influences CE outcomes.
METHODS: ICER Final Evidence Reports published between 2017-2025 using the ultra-rare disease framework were identified and included if they presented results from ≥1 assessment incorporating a societal perspective. Included societal cost components and CE results from the healthcare system and modified societal perspectives were collected. Analyses assessed the frequency of societal cost component inclusion and compared CE results across perspectives.
RESULTS: Six reports used the ultra-rare framework to assess CE of treatments for neuromuscular (n=2), retinal (n=2), and hematologic (n=2) conditions. The most frequently included societal cost components were labor market earnings lost (n=5), cost of unpaid lost productivity due to illness (n=5), unpaid caregiver-time costs (n=4), cost of patients’ time spent receiving care (n=4), and impact on caregiver health-related quality of life (n=3). No assessments included consumption, legal/criminal justice, housing, or environmental costs. Five assessments (83.3%) showed a decrease in the cost per quality-adjusted life year gained when societal costs were included.
CONCLUSIONS: In practice, ICER ultra-rare disease assessments incorporated a limited range of societal costs, largely focused on productivity and caregiving. The inclusion of any societal costs generally improved CE results, underscoring the importance of generating comprehensive evidence on societal cost impacts to support value narratives, economic evaluations, and launch planning for therapies targeting ultra-rare conditions.
A BREATHTAKING GAP IN THE SOCIAL COST OF CARBON: VALUING HEALTH LOSSES FROM CLIMATE CHANGE
OBJECTIVES: Integrated assessment models (IAMs) translate climate change into monetary damages and are used to compute the social cost of carbon (SCC). Two gaps are particularly salient for health economics. First, most SCC-health modules emphasize mortality, thereby omitting climate-related welfare losses from non-fatal morbidity. Second, climate change is not only a shift in mean temperature; emissions may also affect the variability of climate conditions, which can independently influence health but is rarely captured in SCC accounting. This paper develops a modular health-damage component that can be compared with, and integrated into, incumbent SCC frameworks.
METHODS: In a baseline two-stage approach, I estimate temperature-health relationships using disability-adjusted life years (DALYs, collected in the Global Burden of Disease Database) for climate-sensitive disease groups and map DALY losses to emissions via an emissions-temperature linkage. As a robustness check, I estimate the climate linkage using a simultaneous mean-variance (SMV) specification that jointly models how global carbon conditions shift both the drift (mean) and diffusion (variance) of temperature, and I propagate these changes into DALY outcomes. I then translate DALY impacts into monetary values under multiple valuation rules and discuss sensitivity and equity pitfalls that arise when applying country-specific valuation tools rather than globally standardized welfare weights.
RESULTS: Evaluated at the 2019 baseline burdens and valued at $100,000 per DALY-year, the implied annualized health SCC for the total non-fatal component of 4 critical disease groups (vector-borne, mental, cardiovascular, and chronic respiratory) is about $7.82 per ton CO2 emission with a 6.7% variability premium with the SMV model.
CONCLUSIONS: The goal is not to replace IAMs, but to provide a transparent health module that expands SCC accounting beyond mortality-only endpoints and clarifies the role of climate variability in health damages. My approach covers untapped features valued at approximately 15% of incumbent SCC standards, thereby bridging both morbidity and variability gaps.
A MULTI-COUNTRY LIFETIME COST ANALYSIS OF HIV IN 10 LATIN AMERICA COUNTRIES: ARGENTINA, CHILE, COSTA RICA, ECUADOR, EL SALVADOR, GUATEMALA, PANAMA, PERU, URUGUAY, PARAGUAY
OBJECTIVES: HIV remains a critical public health challenge across Latin America, with heterogeneity in both epidemiological patterns and healthcare infrastructure among nations. While treatment costs vary substantially, traditional cost analyses focusing only on antiretroviral therapy expenditures provide an incomplete picture of HIV's true economic impact. This multi-country study quantifies comprehensive lifetime and annual per-person costs across 10 Latin American countries, capturing both direct medical expenses and broader societal burden to inform regional prevention strategies.
METHODS: This study used a standardized cost-of-illness framework across all countries using dual perspectives. The healthcare system perspective included antiretroviral procurement and administration, clinical monitoring stratified by immunological status, and management of opportunistic infections. The societal perspective incorporated productivity losses, years of life lost due to premature mortality, and informal caregiving burden. Country-specific survival estimates post-diagnosis informed lifetime calculations. Costs were standardized to 2024 USD. All information used in the analysis was sourced from public and open-access sources.
RESULTS: Estimated direct lifetime costs per PLWH and corresponding annual costs vary by country: Argentina $521,100 and $11,328; Chile $237,985 and $4,958; Costa Rica $568,736 and $11,375; Ecuador $90,620 and $2,014; El Salvador $58,499 and $1,393; Guatemala $363,918 and $9,836; Panama $41,550 and $923; Peru $22,811 and $507; Uruguay $339,790 and $8,288; Paraguay $112,273 and $2,673. Additional indirect costs, including productivity losses, premature mortality, and informal care, further increase the financial burden.
CONCLUSIONS: This regional analysis displayed that despite ten-fold variation in treatment costs across Latin American countries, the economic burden of HIV extends far beyond medical care. Whether in high-cost or low-cost treatment environments, indirect costs dominate. These findings emphasize that sustainable HIV economic control requires robust prevention programs to reduce new infections, not only treatment cost optimization. Regional policymakers should prioritize comprehensive prevention strategies such as targeted testing, pre-exposure prophylaxis scale-up, and community interventions; tailored to each country's epidemic profile.
Beyond Cronbach’s Alpha: Modern Reliability Assessment for COA Research and Regulatory Decision-Making
Session Type: Other Breakout Session
Topics: Patient-Centered Research, Methodological & Statistical Research, Study Approaches
Track: Real-World Evidence (RWE)
Level: Intermediate
Purpose: This session is to advance COA measurement practice by addressing whether Cronbach’s alpha is fit for purpose and by equipping researchers with modern methods for evaluating reliability. As regulators increasingly request evidence beyond alpha to support an outcome measure’s fit-for-purpose, COA teams need clear guidance on when alpha is appropriate, when it is misleading, and how alternatives such as omega, ICC, split-half reliability, and IRT-based conditional reliability can strengthen COA submissions. This session will provide foundational understanding, practical analytic demonstrations, and regulatory context to help attendees improve reliability evaluation in clinical trials, qualification programs, and labeling claims. Real-time polling on current use of methods will have facilitate discussion.
Description:
Cronbach’s alpha remains the dominant measure of reliability in COA research, yet it is often applied under conditions that may violate its central assumptions or is used to support incorrect inferences. The session begins by clarifying the assumptions and properties of alpha, such as tau-equivalence, including unidimensionality and equal item contributions, and scale length dependence. The second presentation introduces contemporary alternatives, including McDonald’s omega, ICCs, split-half permutation methods, and IRT-based conditional reliability, explaining how each aligns with COA conceptual frameworks and different instrument designs. A third presentation compares alpha against these modern indices, using empirical examples, to demonstrate how reliability conclusions may change when multidimensionality, item information, or temporal stability are considered. The final presentation connects these methodological insights to regulatory expectations, highlighting how FDA and EMA increasingly critically evaluate internal consistency evidence, request domain-level reliability, caution against inflated alpha values, and rely on structural validity assessments.
Moderator
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R. J. Wirth, PhD
Vector Psychometric Group, Chapel Hill, NC, United States
R.J. Wirth is CEO & co-Founder at VPG. Dr. Wirth received his PhD in Quantitative Psychology from the historic LL Thurstone Psychometric Laboratory at University of North Carolina – Chapel Hill. For nearly two decades, Dr. Wirth has collaborated widely within the pharmaceutical and medical device industries to develop and/or evaluate the measurement properties of clinical outcome assessments and was awarded (as co-PI) one of the first FDA-funded CDER pilot program grants: Standard core clinical outcome assessments and their related endpoints. Dr. Wirth has authored numerous peer-reviewed publications on such topics as item factor analysis, structural equation modeling, validity, as well as various aspects of scale development appearing in outlets such as Headache, Health Psychology, Medical Care, Psychological Assessment, Psychological Methods, and Quality of Life Research. He has participated as an invited expert speaker on multiple FDA panels and industry advisory boards focused on COA development and support.
Speakers
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Stephen Maher, PhD
Sharon, MA, United States
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Danielle Rodriguez, PhD
Thermo Fisher Scientific, Snohomish, WA, United States
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Patrick Daniele, MSc
Thermo Fisher Scientific, Vancouver, BC, Canada
Rural-Urban Disparities in Cancer Care: Risk Factors, Treatment Access, and Survival Outcomes
Session Type: Issue Panel
Topics: Health Service Delivery & Process of Care, Health Policy & Regulatory, Clinical Outcomes
Track: Expanded Value Measures
Level: Introductory
Disparities in cancer survival outcomes between urban and rural populations are particularly pertinent in Canada, the world’s second largest country by land area. Rural populations consistently experience poorer cancer survival outcomes that could be influenced by differences in risk factors for cancer, socioeconomic status, and access to public healthcare services associated with diagnosis, treatment and palliative care.
We conducted a targeted literature review using MEDLINE and Embase to identify real-world evidence studies published in Canada, Australia and the US between 2010 and 2025. We identified studies that report on differences between urban and rural populations in the prevalence of various risk factors (such as obesity and smoking), disease stage at diagnosis, access to treatment (e.g., time from diagnosis to start of treatment), socioeconomic status, and overall survival from diagnosis. Inclusion criteria included lung, breast, prostate and colorectal cancer types (which represent the four most prevalent cancers in Canada), adult age, and English language.
Understanding the extent to which rural populations are underserved in cancer care is a critical public health priority. We are proposing to bring together a panel of multidisciplinary experts with perspectives of the patient, clinician, researcher to discuss both the findings of this research and engage with policy makers to develop targeted strategies to promote health equity based on geographical location in cancer care across Canada.
Moderator
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Cal Shephard, MSc
AstraZeneca, Toronto, ON, Canada
Speakers
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Julie Stakiw, MD
Saskatchewan Cancer Agency, Saskatoon, SK, Canada
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Robert Bick
CanCertainty Coalition, Markham, Canada
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Soo Jin Seung, BSc
Sunnybrook Health Sciences Centre, Toronto, ON, Canada
HEOR as a Compass, Not a Roadblock: How and When Development-Stage Biotech Companies Should Leverage HEOR
Session Type: Workshop
Topics: Health Technology Assessment, Health Policy & Regulatory, Economic Evaluation
Track: Access and Drug Pricing
Level: Introductory
Purpose:
Development-stage biotechnology companies are primarily focused on advancing a safe, effective drug and securing the capital necessary by fundraising through private capital investments to sustain innovation. As health policy uncertainty accelerates and price scrutiny intensifies, development-stage companies can no longer focus solely on evidence for regulatory approval; they also need to consider evidence to demonstrate potential commercial success. Evidence and approaches central to health economics and outcomes research can be leveraged to address this need.
This workshop will highlight how and when health economic and outcomes research (HEOR) evidence and methodologies can be leveraged by development-stage biotechnology companies and when each approach could be implemented to support their fundraising, acquisition, and/or commercialization success.
Participants will learn which health economic and outcomes research methodologies are most aligned with the goals of development-stage biotechnology companies and when each could be implemented.
Description:
The workshop will be introduced by Dr. Canestaro, who will briefly summarize the different phases of pre-clinical and clinical research, the goals for drug development, and the rapidly evolving policy landscape that impacts drug development (5 mins). Then, Dr. Canestaro will moderate a fireside chat with three panelists (Fine, Hepp, Masia) with experience implementing HEOR within the operations of development-stage biotechnology companies. Each panelist will provide real-world examples of how they have applied specific HEOR approaches within the development stage and will discuss 1) when the need for HEOR arises, 2) the impacts of their efforts, 3) adaptations to align with the goals of development-stage companies, and 4) missed opportunities.
The session will conclude with audience polling to assess the relative strength of various health economic and outcomes research methods (e.g., budget impact, cost-effectiveness analysis, evidence synthesis, patient preference data) for development-stage companies. The session will reserve twenty minutes for audience Q&A.
Moderator
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William J Canestaro, MS, PhD
University of Washington, Seattle, WA, United States
Speakers
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Jen Fine, MS, ScD
Abivax, San Francisco, CA, United States
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Zsolt Hepp, MS, PharmD
SEATTLE GENETICS, Kirkland, WA, United States
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Neal Masia, PhD
EntityRisk, Inc., Princeton, NJ, United States
Pursuing Affordability Decision Rules: Towards Transparent, Evidence-Informed Budget Impact Thresholds
Session Type: Issue Panel
Topics: Health Technology Assessment, Economic Evaluation, Health Policy & Regulatory
Track: Access and Drug Pricing
Level: Intermediate
Issue Description
Health systems worldwide increasingly face technologies that are clinically valuable yet financially burdensome. While cost-effectiveness thresholds are well studied, affordability—how much health systems can realistically pay, over what time horizon, and under what constraints—remains one of the most unresolved and contested issues in Health Techonology Assessment (HTA). Countries and organizations apply divergent approaches: some rely on implicit political judgements, others use explicit budget-impact triggers, and global agencies emphasize fiscal space and opportunity costs.
This Issue Panel brings together three different perspectives to debate how affordability should be defined, measured, and incorporated into evidence-based decision making. The debate will explore tensions between value for money and short-term budgets, the relationship between affordability and equity, and the feasibility of global or standardized frameworks. We will include polling and audience interaction.
Relevance & Importance
Affordability is central to pricing and access decisions for oncology therapies, gene and cell therapies, vaccines, and high-cost chronic treatments. Yet payers, HTA agencies, and global health institutions lack consistent rules or guidance. This panel addresses a crucial gap by contrasting US, European, and Canadian perspectives, highlighting practical, economic, and political challenges in operationalizing affordability.
Moderator
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Lotte Steuten, MSc, PhD
Office of Health Economics, London, United Kingdom
Lotte Steuten, PhD Deputy Chief Executive of the Office of Health Economics; former Member, Board of Directors, ISPOR
Prof Lotte Steuten is deputy chief executive of the Office of Health Economics (OHE), the world’s oldest independent health economics research organization, based in London, UK, and a globally recognized expert in health economics and outcomes research (HEOR).
Her research addresses challenges in valuing and paying for innovative therapies, with the aim of achieving effective, accessible, affordable, and efficient healthcare for all. She has published over 150 peer-reviewed papers on topics including the value of novel treatments, diagnostics and prevention for a wide range of non-communicable and infectious diseases.
With 2 decades of experience across Europe, the United States, and Asia Pacific, she advises governments, industry, and other organizations worldwide. She is frequently sought by media and international stakeholders for expert commentary on HEOR, value assessment, health policy innovation, and evolution of health technology assessment globally.
Alongside her position at OHE, Prof Steuten is a visiting honorary professor at City St George’s, University of London. Prior to joining OHE, she held academic faculty positions at the Fred Hutch Cancer Research Center and the University of Washington in the United States. She earned her PhD (with honors) from Maastricht University in the Netherlands.
Speakers
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Scott Ramsey, PhD, MD
Fred Hutchinson Cancer Research Center, Seattle, WA, United States
Dr. Ramsey is a general internist and health economist. He is a Professor and Director of the Hutchinson Institute for Cancer Outcomes Research, a multidisciplinary team devoted to cancer outcomes research. Dr. Ramsey is also a Professor in the Schools of Medicine and Pharmacy at the University of Washington.
Trained in Medicine and economics, Dr. Ramsey’s research focuses on outcomes research and cancer care delivery. His studies on financial toxicity issues faced by cancer patients are widely cited. He leads the Value in Cancer Care initiative, a statewide quality and cost reporting program aimed at improving oncology care. His other research interest includes cancer care delivery research, pragmatic trial design, cost-effectiveness analysis, and stakeholder engagement.
Dr. Ramsey is co-Chair National Cancer Institute’s Cancer Care Delivery Research Steering Committee and a co-chair of SWOG’s Cancer Care Delivery Committee. He is past President of the International Society of Pharmacoeconomics and Outcomes Research (ISPOR) and has served on the National Academy of Science’s Cancer Policy Forum. He is Co-Principal Investigator for the Coordination and Communications Center of the National Cancer Institute’s Cancer Screening Research Network.
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Jeffrey T. Hamilton, BA, MSc
GSK, Westfield, NJ, United States
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Marina Richardson
ICER, Boston, MA, United States
Marina Richardson is an associate director, Health Technology Methods and Health Economics with the Institute for Clinical and Economic Review (ICER). In her role, Marina leads and oversees the development of economic models to inform pricing and reimbursement decision-making and identifies and executes opportunities to enhance ICER's methodology and processes within Health Technology Assessment (HTA) and Health Economics. Prior to joining ICER, Marina led and contributed to reimbursement review reports and recommendations at Canada's Drug Agency (CDA-AMC), formerly CADTH. Marina has a PhD in Health Services Research from the University of Toronto and is an active contributor to the field including as a deputy editor for the International Journal of Technology Assessment in Health Care (IJTAHC), a member of the Ontario Immunization Advisory Committee (OIAC) in Ontario, Canada, and as a co-chair of the International Scientific Program Committee for Health Technology Assessment International (HTAi) 2025.
2:45 PM - 3:15 PM
Coffee and Connect
Session Type: General Meeting
Head to the exhibit hall to connect with fellow attendees and exhibitors over a steaming cup of coffee.
3:15 PM - 3:45 PM
Navigating Literature Reviews in the Age of AI: Making Sense of Review Types and AI
Session Type: Exhibit Hall Theaters
Topics: Methodological & Statistical Research, Health Technology Assessment, Study Approaches
Level: Intermediate
Literature reviews are a cornerstone of HEOR evidence generation, yet the terminology, typology, and methods remain a source of persistent confusion. This two-part session provides a structured overview of key concepts and methodological considerations.
Part 1 offers a practical orientation to the literature review landscape: key review types, the common language used to describe them, and how to align each approach specific research objectives and evidence requirements. Grounded in established methodological guidance and best practices for evidence planning, it establishes a clear foundation for researchers navigating this space.
Part 2 tackles a question on increasingly discussed across the evidence synthesis community: how artificial intelligence tools may be appropriately incorporated into literature review workflows? We explore when AI tools are appropriate and when they are not, across different review types and specific workflow steps, including areas where guidance is still evolving. Drawing on current practices and emerging methodological discussions in AI-enabled evidence synthesis, we offer an objective overview of the current capabilities, limitations, and methodological considerations associated with using AI in literature review processes.
The audience will gain practical insights into selecting appropriate literature review approaches and evaluating the potential role of AI-supported tools across different stages of evidence synthesis workflows.
Speaker
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Zarmina Khankhel
Genesis Research Group, Lowell, MA, United States
Leveraging Open Claims In Real World Evidence Generation: An Emerging Innovative Solution
Session Type: Fast Facts
Topics: Real World Data & Information Systems, Study Approaches, Methodological & Statistical Research
Track: Real-World Evidence (RWE)
Level: Intermediate
This session will examine the growing role of open claims databases in HEOR/RWE by highlighting their strengths—such as enhanced population diversity, increased sample sizes, and improved data recency—as well as their challenges, including data fragmentation and potential biases. Speakers shall discuss current evidence utilizing open claims, methodological strategies and analytical frameworks that can mitigate limitations and improve the robustness of real world evidence. The session will culminate with guidance on best practices, and the optimal use of open or hybrid claims data to strengthen real-world evidence generation.
Speakers
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Phani Veeranki, MPH, DrPH, MD
Optum Life Sciences, CYPRESS, TX, United States
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Arpita Nag, MBA, MS, RPh, PhD
ASTRAZENECA, Sudbury, MA, United States
3:15 PM - 4:15 PM
Making Market Access Work in LMIC Settings: Practical Examples and Future Considerations
Session Type: Forums
Topics: Health Technology Assessment, Epidemiology & Public Health, Economic Evaluation
Track: Access and Drug Pricing
Level: Intermediate
In many low- and middle-income countries (LMICs), where a majority of patients pay out-of-pocket, traditional HEOR frameworks don’t always reflect real patient affordability and market realities. As disease burdens shift toward noncommunicable diseases (NCDs) and therapies become more specialized, reimbursement delays and limited public budgets widen the gap between innovation and access. In these environments, patients rely heavily on private insurance or personal funds, underscoring the need for access strategies tailored to LMIC-specific constraints not just adapted from high-income markets. This session is designed to bridge that gap by providing experience-based insights directly from LMIC settings. The session will explore practical, data-driven approaches for strengthening market access strategies in LMICs. Economist Panos Kanavos will open with an overview of how the market access and value assessment environment has evolved in LMICs. (10 min) Saba will introduce innovative tools and predictive models for segmenting patient affordability and creating sustainable access strategies in out-of-pocket markets – showing how these methods can complement and strengthen conventional HEOR assessments. (10 min) Oestergaard will outline real-world HTA challenges in LMICs, including the evolving role of differential pricing, and pragmatic approaches for improving value assessment in resource-constrained settings. (10 min) Venable will provide the industry perspective, sharing lessons on navigating the payer landscape in LMICs. (10 min) Audience participation will focus on a real LMIC oncology case study. Working through key strategic questions with the guidance of our panelists, participants will practice applying the tools and frameworks introduced in the session. (20 min) This session blends expert insights with hands-on application to give attendees practical tools and actionable steps they can immediately apply to access strategy in LMICs.
Moderator
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Richard Willke, PhD
Scintegral Health Economics, Soddy Daisy, TN, United States
Speakers
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Joseph Saba, MD
Axios International, Dublin, Ireland
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Yvette A Venable, MPH
AstraZeneca, Cambridge, United Kingdom
Ms. Venable is an accomplished life sciences leader, with more than 25 years’ experience in health policy, patient advocacy, and patient access. Currently, she leads global payer policy for AstraZeneca’s Biopharmaceutical Business Unit. Previously, Ms. Venable was the first vice president of patient and community engagement for the Institute of Clinical and Economic Review (ICER), a non-profit Health Technology Assessor in the U.S.A. She also previously led global and European public policy and patient advocacy functions within life sciences companies across a range of serious conditions including cancer, hepatitis, asthma, RA, diabetes and rare and ultra-rare conditions. Earlier in her career, Yvette held increasingly senior roles within global health communication and public affairs consultancies.
Ms. Venable graduated with honors from Drake University in Des Moines, Iowa, and is a candidate for a Global Master’s of Public Health at Imperial College London.
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Mikkel Oestergaard, PhD
Merck Sharp & Dohme International Service B.V., Zurich, Switzerland
Communicating Value in the Age of AI—Skills, Tools, and Confidence for HEOR Careers
Session Type: Forums
Topics: Methodological & Statistical Research, Organizational Practices
Track: AI
Level: Introductory
Join us for an interactive, skills-forward panel bringing together voices from academia, consultancy, and industry to explore how AI up-skilling can enable improved communication and in turn, accelerate early-career growth in HEOR. Building on survey insights from ISPOR New Professionals and Students, this session tackles the real-world challenge of translating complex analyses into clear, compelling “so what?” narratives without overstatement. Panelists will share practical strategies for:
- Balancing technical rigor with impactful messaging to different stakeholders
- Demonstrating competitiveness by integrating strong technical foundations with soft skills
- Developing confidence and leadership presence in communication
- Using AI and modern tools to automate workflows and surface insights worth communicating
Expect live audience interaction, applied examples, and take-home frameworks for sharpening your message, improving credibility, and positioning your work and your career for impact across sectors. This session is brought to you by the ISPOR New Professionals Steering Committee and the ISPOR Student Network. Open to all conference attendees.
Moderator
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Irwin Tran, MS, MSc, PharmD
NextLeader Coaching, Alameda, CA, United States
Over my 18 years in the biotech industry across the US, UK, and global markets, I’ve grown from a technical expert in pharmacy, health economics and outcomes research to a corporate leader, managing and building technical teams worldwide. Throughout this journey, my greatest insight wasn’t just in the HEOR data, models, and leadership itself, but in my passion for coaching and developing future leaders. I’m now an independent consultant in HEOR and Market Access, as well as an International Coaching Federation (ICF) certified coach and a practitioner of the Insights Discovery assessment. My aim now is to help individuals and teams leverage their technical expertise and other natural talents to grow towards the impactful leaders they aspire to be, all with the intent of getting health innovations to the patients who will benefit from them!
Speakers
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Chintan Dave
Rutgers University, New Brunswick, NJ, United States
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Juan-David Rueda, MS, PhD, MD
AstraZeneca, Gaithersburg, MD, United States
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Sonya Snedecor, PhD
Science Clarity, Silver Spring, MD, United States
Raising the Bar on RWE for Publication: A Discussion with Leading Journal Editors
Session Type: Forums
Topics: Real World Data & Information Systems, Organizational Practices, Study Approaches
Track: Professional Development
Level: Intermediate
Real-world evidence (RWE) is increasingly used to inform regulatory, HTA, and payer decisions, as well as clinical guidelines. Yet, acceptance of RWE in leading journals—particularly clinical journals-- remains inconsistent. Concerns relate to causal methods and findings, transparency, bias, and reproducibility. This session will identify some of the most pressing challenges in reviewing and accepting RWE studies and what leading editors look for to meet high quality expectations for RWE, before transitioning to identify tools, training and practices that can support its publication. The objective of this session is two-fold: (1) identifying the problems when working to publish high quality RWE to a journal, and (2) proposing and reacting to solutions to the presented problems with an overview of best practices and existing tools to support its acceptability. The session will engage audience members by inviting them to react to proposed solutions along with the journal editors for the final 10 minutes, along with the Q&A.
Moderator
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Sebastian Schneeweiss, ScD, MD
Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States
Speakers
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Shirley Wang, PhD
Brigham & Women's Hospital, Harvard Medical School, Boston, MA, United States
Dr. Wang is an associate professor at Brigham and Women’s Hospital, Harvard Medical School and lead epidemiologist for the Food and Drug Administration's (FDA) Sentinel Innovation Center. She leads the Meta-Research in Pharmacoepidemiology program, with recent projects aimed at improving the transparency, reproducibility, and robustness of evidence from healthcare databases (www.repeatinitiative.org) and informing when and how real-world evidence studies can draw causal conclusions to inform regulatory or other healthcare decision-making (www.rctduplicate.org). She is currently PI on multiple NIH R01s and is also funded by FDA. Her methods work has received 3 awards from international societies.
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Christine Laine, MD, MPH
Annals of Internal Medicine, Philadelphia, PA, United States
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Gregory Curfman, MD
Journal of the American Medical Association (JAMA), Boston, MA, United States
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Daniel Solomon, MPH, MD
Arthritis and Rheumatology, Boston, MA, United States
4:00 PM - 4:45 PM
PROs and Patient Preference Poster Tour
Session Type: Research Posters
This tour will take place during Poster Session 4, Posters will be hung from 4:00 PM - 7:00 PM.
Posters featured in this tour:
PT31: INDIVIDUAL PREFERENCES FOR UPPER EXTREMITY PROSTHETICS ALONG A USER-COMPLEXITY FRAMEWORK: A DISCRETE CHOICE EXPERIMENT
PT32: SHEDDING LIGHT ON PATIENT-REPORTED OUTCOME MEASURE UTILIZATION ACROSS NSCLC THERAPIES
PT33: ALIGNMENT OF PATIENT-REPORTED OUTCOME IMPROVEMENTS WITH ICER COST-EFFECTIVENESS AND VALUE-BASED PRICE RECOMMENDATIONS IN RHEUMATOID ARTHRITIS
PT34: THE IMPACT OF ESKETAMINE ON ALZHEIMER’S DISEASE IN PATIENTS WITH MILD COGNITIVE IMPAIRMENT AND MAJOR DEPRESSIVE DISORDER: A TARGET TRIAL EMULATION
PT35: EVALUATING PATIENT PREFERENCES FOR COPD MAINTENANCE TREATMENT DELIVERY DEVICES: A DISCRETE CHOICE EXPERIMENT
PT36: IMPACT OF GOLD-GUIDED PHARMACIST-LED PHARMACEUTICAL CARE ON CLINICAL OUTCOMES AND QUALITY OF LIFE IN COPD: A PROSPECTIVE RANDOMIZED TRIAL
Real-World Evidence Poster Tour
Session Type: Research Posters
This tour will take place during Poster Session 4, Posters will be hung from 4:00 PM - 7:00 PM.
Posters featured in this tour:
PT37: EFFECTIVENESS AND SAFETY OF GLP-1 RECEPTOR AGONISTS IN PATIENTS WITH WEIGHT RECURRENCE AFTER BARIATRIC SURGERY: A REAL-WORLD STUDY
PT38: REAL-WORLD ADHERENCE TO GLP-1RA AND DUAL GIP-GLP-1RA AMONG COMMERCIALLY INSURED US PATIENTS WITH TYPE 2 DIABETES AND OBESITY
PT39: USE OF REAL-WORLD EVIDENCE ON US BRANDED HCP DRUG WEBSITES: AN AI-ENABLED CONTENT ANALYSIS
PT40: WHEN TRIALS FALL SHORT: LEVERAGING REAL-WORLD EVIDENCE TO ADVANCE PRECISION THERAPIES
PT41: REAL-WORLD EVIDENCE TO SUPPORT HEALTH TECHNOLOGY ASSESSMENT AND PAYER DECISION MAKING: A REVIEW OF POLICY AND GUIDANCE ACROSS EUROPE, CANADA, AND THE UNITED STATES
PT42: WHEN THERAPIES ARE TARGETED BUT METHODS ARE GUESSING: CLOSING THE GAP IN PRECISION ONCOLOGY EVALUATION
4:00 PM - 7:00 PM
Poster Session 4
Session Type: Research Posters
Poster Tours 4:00PM–4:45PM | Presenters will be with their posters from 6:00PM–7:00PM
4:45 PM - 5:45 PM
The Time Has Come for Patient-Centric Composite Endpoints in Comparative Studies
Session Type: Workshop
Topics: Study Approaches, Methodological & Statistical Research, Clinical Outcomes
Level: Intermediate
Purpose: Traditional analyses of randomized clinical trials (RCTs) or other comparative effectiveness studies do not routinely incorporate patient preferences. This workshop will provide participants with a step-by-step approach to eliciting preference weights and applying them to data from RCTs using novel methodologies—Win Statistics and Weighted Composite Endpoints (WCE)—to enable patient-centered comparative effectiveness research.
Description: Dr. Gouda will review newer analytic approaches, including win statistics and weighted-composite endpoints (WCE), designed to address limitations of conventional analytic methods for treatment comparisons in RCTs.
Dr. Reed will review alternative stated-preference methods that can be used to quantify the relative importance of various medical events for incorporation in these analytic methods. The audience will participate in a Case-1 best-worst scaling exercise used to generate weights for medical events relevant to benefit-risk evaluations of anticoagulants in a survey of 1028 patients with atrial fibrillation.
Dr. Shoji will demonstrate how these patient-preference weights can be applied in win statistics and WCE approaches using a worked example from a patient-level analysis of 58,541 individuals across four RCTs of direct oral anticoagulants versus warfarin.
The audience answer polling questions about their interpretation of findings from different approaches.
Moderator
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Pishoy Gouda, MD, MSc
University of Calgary, Calgary, AB, Canada
Speakers
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Shelby Reed, RPh, PhD
Duke Clinical Research Institute, Durham, NC, United States
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Satoshi Shoji, MD, PhD
Duke Clinical Research Institute, Durham, NC, United States
Advancing Real-World Evidence for Pediatric Drug Safety: Methods, Off-Label Use, and Regulatory Applications
Session Type: Other Breakout Session
Topics: Real World Data & Information Systems, Methodological & Statistical Research, Health Policy & Regulatory
Track: Real-World Evidence (RWE)
Level: Intermediate
Purpose
Children are often not included in randomized trials, leaving major evidence gaps for many medications used in pediatric care. Off-label prescribing is common across pediatric specialties, which increases the need for reliable real-world evidence (RWE) to inform safety and benefit–risk decisions. However, generating high-quality pediatric RWE is challenging because of low event rates, changing treatment patterns, and limited pediatric-specific clinical information in many datasets. This session aims to provide practical strategies to improve the design, analysis, and interpretation of pediatric RWE studies and to discuss how these approaches can support regulatory and clinical decision-making.
Description
Panelists will outline how to evaluate whether a real-world data source is fit for use in pediatric studies, including assessing completeness of variables, follow-up, capture of off-label use, and the ability to define exposures, covariates, and outcomes relevant to children. The session will describe approaches for addressing confounding and bias when sample sizes are small or covariates are imbalanced, such as overlap weighting. Examples from pediatric studies of biologics and other widely used therapies will illustrate how these methods work in practice, especially when studying rare safety outcomes such as serious infections. The session will also consider how strengthened RWE can inform safety assessment for off-label pediatric use and complement existing regulatory frameworks for benefit–risk evaluation. Panelists will highlight the importance of transparency, reproducibility, and clear communication of uncertainty when estimates are imprecise.
Attendees will gain practical guidance for evaluating data fitness, selecting appropriate analytical methods, and interpreting findings in settings where traditional trial evidence is limited or unavailable. The discussion will emphasize actionable steps to support pediatric RWE generation.
Moderator
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Ning Lyu, MS, PhD
University of Houston College of Pharmacy, Sugar Land, TX, United States
Speakers
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Daniel Horton, MD, MSCE, FISPE
Institute for Health, Health Care Policy and Aging Research, Rutgers University, New Brunswick, NJ, United States
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Timothy Savage, MD, MPH, MSc
Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States
Can New Approaches to Estimating Dynamic Efficiency Help to Maintain Both Access and Innovation in Pharmaceutical Markets?
Session Type: Issue Panel
Topics: Economic Evaluation, Health Policy & Regulatory, Health Technology Assessment
Track: Access and Drug Pricing
Level: Intermediate
Pharmaceutical firms and payers face dual challenges of ensuring patient access to medicines while maintaining economic incentives for development of innovative treatments. This balance - in economic terms, dynamic efficiency - is crucial. The global nature of pharmaceuticals adds complexity, as preferences and resources very across countries. Recently, novel frameworks have been proposed to estimate optimal producer surplus (PS), each with unique assumptions and relevance to different markets.
This panel will discuss the core challenge of dynamic efficiency in pharmaceutical markets. Panelists will provide diverse perspectives on approaches to estimating dynamic efficiency at the industry and product levels. The issue that will be debated is whether dynamic efficiency and estimates of PS are helpful for characterizing the value of a medicine retrospectively, prospectively, or not at all. Attendees will gain insights into the complexities of dynamic efficiency and potential pathways to maintaining and demonstrating it as more patient-centered aspects of value are incorporated into value assessments.
With real-time polling and 15-20 minutes of Q&A, the audience will be able to provide their perspectives on the importance of achieving dynamic efficiency and implications for value assessment.
Moderator
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Robert J Nordyke, BS, MS, PhD
Beta6 Consulting, Topanga, CA, United States
Speakers
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Kimberly Westrich, MA
National Pharmaceutical Council, Herndon, VA, United States
Kimberly Westrich, MA, is the Chief Strategy Officer of the National Pharmaceutical Council (NPC), which sponsors and conducts research on health policy issues related to the development and use of innovative biopharmaceuticals to improve the health of patients. NPC’s research contributes to the body of evidence that supports discussions and decisions about patient access to treatments, appropriate use, and the value innovative treatments provide to both patients and the healthcare system.
Ms. Westrich provides strategic guidance to NPC’s policy research and communications activities. She leads several research initiatives across NPC’s portfolio, including employer-sponsored insurance. She has published extensively on issues related to value assessment frameworks, patient-centered formulary and benefit design, value-based contracts, quality performance measurement, and accountable care organizations. Additionally, Ms. Westrich leads NPC’s workplace culture initiative — most notably demonstrated by our company's recognition as a Certified Great Place To Work®.
Ms. Westrich began her NPC career in 2000. She has also served as Director of Research at the Pharmaceutical Research and Manufacturers of America (PhRMA), worked as a healthcare consultant at The Lewin Group and Xcenda, and as a health economics and outcomes researcher at Johnson & Johnson.
Ms. Westrich is a certified yoga teacher and life coach with a passion for helping others learn and thrive. She received her master’s degree in economics from Northwestern University and her undergraduate degree in economics and mathematics from the College of William and Mary.
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Robert B McQueen, BA, MA, PhD
University of Colorado Skaggs School of Pharmacy and Pharmaceutical Science, Aurora, CO, United States
R. Brett McQueen is the director for the Center for Pharmaceutical Value (pValue) at the University of Colorado Skaggs School of Pharmacy and Pharmaceutical Sciences, where he is an associate professor in the Department of Clinical Pharmacy. Brett’s work includes comparative effectiveness research, cost-effectiveness applications and methods development, multi-criteria decision analysis, outcomes-based contracting, and patient preferences research. He is active in ISPOR through contributions to short courses, workshops, issue panels, and research presentations.
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Anirban Basu, PhD
University of Washington, Seattle, WA, United States
Looking Beyond Traditional Domains in Patient-reported Outcomes
Session Type: Research Podiums
This session explores innovative approaches to patient-reported outcomes and health-related quality-of-life measurement beyond traditional frameworks. Presentations will examine societal preferences for physical and mental health, establish contemporary SF-6D population norms and behavioral risk impacts, and demonstrate empirical applications of disease-specific and productivity measures. The session will conclude with an assessment of the validity and stability of life satisfaction measures across age and gender groups.
HOW SOCIETY VALUES HEALTH: UNEQUAL CONTRIBUTIONS OF PHYSICAL AND MENTAL WELL-BEING TO SOCIAL WELFARE
OBJECTIVES: Health-related quality-of-life (HRQOL) utility weights aggregate physical and mental health into a single measure of societal value, yet the implicit sensitivities and tradeoffs embedded in these weights are poorly understood. This study characterizes the shape of the societal utility function with respect to physical and mental health, asking how marginal health improvements are valued across the health spectrum. Rather than debating which domains should matter more, we treat the societal value set as given and empirically recover how it converts experienced health into utility.
METHODS: We use nationally representative Medical Expenditure Panel Survey (MEPS) data from 2018-2023. Individuals’ health profiles are measured using the VR-12 instrument and linked to societal utility weights derived from a preference-based discrete choice experiment. Physical and mental health are summarized using the Physical Component Summary (PCS) and Mental Component Summary (MCS) scores. We estimate flexible models of societal utility as a function of individual-level PCS and MCS scores, allowing for nonlinearities and interactions. Model performance is assessed using 10-fold cross-validation, and the best-fitting specification is used to characterize the implied societal utility function and its marginal utilities across the spectrum of individual physical and mental health.
RESULTS: Mental health exhibits a U-shaped marginal utility curve. Societal utility is highly sensitive to improvements at very low and very high levels of mental functioning. In contrast, physical health displays diminishing returns throughout the spectrum with marginal utility at its highest at low PCS levels. Unlike physical health, marginal utility for mental health does not converge to zero at high functioning, suggesting that societal valuation extends beyond restoration toward higher levels of psychological well-being.
CONCLUSIONS: Societal HRQOL preferences implicitly prioritize alleviating severe physical limitations while valuing both recovery and flourishing in mental well-being. These asymmetric sensitivities have important implications for how health gains are valued in economic evaluation.
AGE AND GENDER-SPECIFIC DIMENSIONALITY OF THE SATISFACTION WITH LIFE SCALE
OBJECTIVES: The Satisfaction With Life Scale (SWLS) generally operates as unidimensional but demonstrates invariance issues. This study aimed to examine the construct validity and stability of various SWLS across age and gender groups.
METHODS: Employing a convenience sample of community-dwelling European adults (N = 7531, median age = 26 (22-28) years, 51.1% females), this instrumental study investigated the structure and stability of SWLS through exploratory/confirmatory factor analysis (EFA/CFA) and multigroup CFA in SPSS and JASP.
RESULTS: EFA in 30% of the sample (n = 2246, KMO (0.86), Bartlett’s test of sphericity χ2 (10) = 4561.84, p = 0.001) revealed a single factor with an eigenvalue of 3.12, which explained 62.35% of the variance. The unidimensional and two bidimensional structures (present/past life satisfaction; achievement/acceptance) expressed excellent fit (χ2 (4-5) = 92.60-106.14, ps = 0.001; all CFIs = 0.994, ; TLI = 0.985-0.987, ; RMSEA = 0.052-0.056, ; SRMR = 0.013-0.014). Bifactor and second-order structures based on both two factor-structures did not converge. The three structures were invariant at the configural metric, scalar, and strict levels across age (<26, ≥26 years) while only the unidimensional SWLS was invariant at all levels across genders. Achievement/acceptance SWLS converged only in males while present/past life satisfaction converged only in females—the fit of both models was excellent, and the fit of the latter slightly improved when the errors of items 2 and 4 correlated.
CONCLUSIONS: The findings support the use of the SWLS as a single-factor instrument for comparative purposes. SWLS components (cognitive or experiential) are interpreted uniformly among different age groups while gender-specific convergence patterns suggest meaningful gender-related nuances in its dimensional expression—males and females differently conceptualize SWLS components. Research should explore theoretical mechanisms underlying differential structuring of life satisfaction and examine whether these gender-specific dimensional patterns replicate across cultures and longitudinal designs.
SF-6D POPULATION NORMS AND DISUTILITY WEIGHTS FOR SINGULAR AND CO-OCCURRING BEHAVIOURAL RISK FACTORS: EVIDENCE FROM TRADITIONAL AND MACHINE LEARNING MODELS
OBJECTIVES: To estimate contemporary Short Form Six-Dimension (SF-6D) population norms for Australian adults and quantify health-related quality of life (HRQoL) impacts of major behavioural risk factors, obesity, smoking, physical inactivity, and risky alcohol use, both individually and in combination, including potential non-linear and interaction effects relevant to economic modelling.
METHODS: Data were drawn from the nationally representative Household, Income and Labour Dynamics in Australia (HILDA) Survey. SF-6D utilities were derived from the SF-36. Multivariable regression models were used to estimate disutilities associated with behavioural risk factors and sociodemographic characteristics. Predicted utilities for behavioural health-state profiles defined by combinations of behavioural risks were generated separately for males and females. Gradient boosting and random forest models were estimated to explore potential non-linearities and interaction effects, with predictive performance assessed using cross-validated root mean squared error and mean absolute error.
RESULTS: Physical inactivity, obesity, and smoking were monotonically associated with lower HRQoL. In contrast, risky alcohol use was associated with near-neutral differences in utility after adjustment. Predicted utilities declined monotonically with increasing behavioural risk burden, with the lowest values observed among individuals with multiple co-occurring risk factors. While absolute utility levels differed by sex, the relative ordering and magnitude of utility differences across behavioural risk profiles were consistent for males and females. Machine learning models did not meaningfully improve predictive accuracy relative to regression models, but identified modest interaction effects involving physical activity, employment status, and body mass index.
CONCLUSIONS: This study provides contemporary Australian SF-6D population norms and utility estimates for combined behavioural risk profiles. By enabling direct parameterisation of multi-risk health states, these results support more realistic economic evaluation of lifestyle and prevention interventions.
PATIENT-REPORTED OUTCOMES AFTER KIDNEY TRANSPLANTATION: REAL-WORLD EVIDENCE OF BURDEN POST-TRANSPLANT
OBJECTIVES: Kidney transplantation recipients may develop, or continue to experience, complications and comorbidities post-transplant, resulting in impaired quality of life. We aimed to explore patient-reported quality of life outcomes post-kidney transplant in the United States (US).
METHODS: Data were drawn from the Adelphi Real World Kidney Transplant Disease Specific Programme™, a cross-sectional survey of nephrologists and kidney transplant recipients in the US from September 2024 - April 2025. Nephrologists reported patient demographics for six consecutively consulting patients. Patients completed the Kidney Disease Quality of Life 36-item (KDQOL-36) and Work Productivity and Activity Impairment (WPAI). Regression analyses were performed to assess the relationship between time since transplant, and KDQOL scores.
RESULTS: Forty-one physicians provided data for 282 patients. Mean (standard deviation; SD) patient age was 53.2 (12.6) years and 60.0% were male. Mean (SD) time since transplant was 3.0 (4.8) years. Overall, 38.3% of patients were ≤1 year post-transplant, 29.4% were >1 - <2 years, 14.5% were >2 - <4 years, and 17.7% were ≥4 years. Mean (SD) activity impairment was 31.9% (22.0%) for patients ≤1 year post-transplant, 16.9% (19.7%) for patients >1 - <2 years, 12.0% (12.3%) for patients >2 - <4 years, and 29.6% (31.3%) for patients ≥4 years post-transplant. Among all patients >1 year post-transplant, regression analyses showed that as time since transplant increased by 1 year, KDQOL-36 symptom/problems scores decreased by -0.59, physical health composite scores by -0.58, and mental health composite scores by -0.38 (all p≤0.05).
CONCLUSIONS: Kidney transplantation does not eliminate long-term patient burden. Recipients continue to experience impairments in physical health, mental health, and daily functioning beyond the first year post-transplant, underscoring the need for sustained, long-term post-transplant care and monitoring.
Following the Trail: A Journey of Individual Patient Preference Data from Response to Analysis to Clinical Encounter
Session Type: Workshop
Topics: Patient-Centered Research, Methodological & Statistical Research, Study Approaches
Track: Expanded Value Measures
Level: Introductory
PURPOSE: This workshop will guide participants along the trail of individual patient preference data from the moment a patient responds to a survey, through analytic methods that transform those responses into actionable insights, and finally to the clinical encounter where these insights inform shared decision-making.
DESCRIPTION: Participants will begin their journey with a threshold exercise, experiencing firsthand the cognitive process patients navigate when expressing risk tolerance using this approach. Next, discussants will compare approaches for estimating patient-level preferences and risk-tolerance (probablistic threshold technique, the multidimensional threshold technique, respondent-level estimates from mixed logit models, and segmentation of individuals across latent classes that vary by risk-tolerance). Discussants will highlight practical considerations across methods including sample-size requirements, participant burden, and within-person consistency. We will conclude with a demonstration of how latent-class findings can be utilized to design predictive questions for decision-support tools, enabling clinicians to personalize benefit-risk discussions for individual patients. Attendees will conclude their journey with a greater understanding of the patient experience (i.e. what it feels like to contribute individual level preference data) and the researcher experience (i.e. weighing the methodological differences and practical applications across methods).
Agenda:
• Welcome and introduction (5 minutes)
• Participate in threshold exercise (10 minutes)
• Share/reflect break-out (5 minutes)
• Probablistic Threshold and DCE Case Study (10 minutes)
• Multidimensional Threshold Case Study (10 minutes)
• Method Compare Q&A (5 minutes)
• Individual Latent-class Predictions (10 minutes)
• Questions/Group Discussion (5 minutes)
Moderator
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Marco Boeri, BSc, MSc, PhD
OPEN Health, London, United Kingdom
Speakers
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Jessie Sutphin, MA
Duke Clinical Research Institute, Mooresville, NC, United States
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Jennifer Whitty, PhD
Thermo Fisher Scientific, London, United Kingdom
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Juan M Gonzalez, PhD
Duke Clinical Research Institute, Cary, NC, United States
Advancing HEOR With Next-Generation AI: Multimodal LLMs, Digital Twins, and Reinforcement Learning for Personalized Therapy
Session Type: Workshop
Topics: Methodological & Statistical Research, Real World Data & Information Systems, Patient-Centered Research
Track: AI
Level: Intermediate
Purpose:This workshop will introduce AI and ML approaches—including unsupervised and supervised ML, LLMs, digital twins, and RL—to address unmet needs in HEOR. The session will help attendees understand when next-generation AI adds value beyond traditional analytics; how these approaches can strengthen personalized therapy in RWE studies; and review methodological, ethical, and transparency considerations for responsible HEOR application.
Description:AI innovations—including generative and multimodal LLMs, digital twins, and RL—are reshaping HEOR by enabling deeper insights from real-world data, identifying meaningful patient subgroups, and informing individualized treatment strategies. This workshop provides an accessible overview of these emerging methods, their applications, and considerations for ethical implementation.
The session will feature presentations:
•Dr. Marcum (moderator): Overview of the evolution of ML/AI in HEOR, highlighting unmet needs.
•Dr. Tian: Case study showing how integrating unsupervised and supervised ML uncovers meaningful patient subgroups in schizophrenia and inform personalized treatment strategies.
•Dr. Wu: Application of digital twins and multimodal LLMs to predict treatment responses in oncology and mental health disorders, emphasizing potential to enhance individualized decision support.
•Dr. Lo-Ciganic: Use of advanced ML to characterize complex treatment pathways using sunburst plots to reveal real-world prescribing patterns. RL Illustrations show support for providers tailoring treatment strategies for patients with opioid use disorder and co-occurring mental health conditions, along with key ethical considerations like fairness, bias detection, and transparency.
Interactive components include live polling and scenario-based questions to engage attendees in evaluating strengths, limitations, and implementation challenges. The workshop will conclude with a moderated discussion on best practices for integrating next-generation AI/ML into HEOR to support personalized therapy and evidence-informed decision making.
Moderator
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Zachary Marcum
Medicus Economics, Hamilton, OH, United States
Dr. Marcum is a Principal at Medicus Economics specializing in pharmacoepidemiologic methods. He has extensive experience designing and implementing descriptive and comparative real-world data analyses on topics including medication adherence, medication effectiveness, and medication safety in the cardiovascular, infectious diseases, and neurological settings. Prior to joining Medicus, he worked as a Director at Aetion as well as a tenured faculty member at the University of Washington School of Pharmacy. He has published 160+ peer-reviewed manuscripts in leading medical journals, including JAMA, JAMA Internal Medicine, and JAMA Neurology. Dr. Marcum received a PharmD from Butler University, completed a PGY1 Pharmacy Practice Residency at the Roudebush VA Medical Center (Indianapolis, IN), a Master of Science degree in Clinical Research as well as a PhD in Clinical & Translational Science from the University of Pittsburgh.
Speakers
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Weihsuan J Lo-Ciganic, MS, PhD
University of Pittsburgh School of Medicine, Pittsburgh, PA, United States
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Marc Y Tian, PhD
Teva Pharmaceuticals, Skillman, NJ, United States
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Yonghui Wu, PhD
University of Florida, Gainesville, FL, United States
Beyond the Usual First Launch: Making Differential Pricing Work for Innovative NCD Medicines in Middle-Income Countries
Session Type: Issue Panel
Topics: Health Policy & Regulatory, Economic Evaluation, Health Technology Assessment
Track: Access and Drug Pricing
Level: Intermediate
ISSUE: Shifts in US and EU pricing and reimbursement policies are reshaping launch incentives and global market access strategies. As these changes take hold, companies may look beyond traditional first-to-access countries. Yet middle-income countries (MICs)—home to 75% of the world’s population and 75% of the non-communicable disease (NCD) burden—still face delayed or absent access to patented innovations.
This panel will explore how sustainable global differential pricing can enable timely, value-based, and affordable access to innovative NCD therapies in MICs. We will focus on system-level enablers and pragmatic solutions aligned with evolving market dynamics and commercial viability.
Overview:
A practical model for global differential pricing — anchored in countries’ health opportunity costs and local value-based assessment (Value-based Tiered Pricing, VBTP) — has been proposed to expand access in low- and middle-income settings. The panel will examine bottlenecks to implementation and highlight actionable pathways for payers, policymakers, and manufacturers to move from concept to execution in MICs.
What the audience will learn
• How US/EU policy shifts alter commercial opportunities for biopharmaceutical firms that prioritize MIC.
• Why MICs are central to access for NCD innovations—and what delays timely uptake.
• How to operationalize VBTP that is feasible, impactful and sustainable.
• Concrete steps stakeholders can take within 12–24 months.
Speaker contributions
• Richard Xie: Commercial opportunities in MICs—assessing growth potential under differential pricing, with a case example from China.
• Kalipso Chalkidou: Health system readiness—closing gaps in data, HTA capacity, and governance to enable credible local value assessment, transparent pricing, and accountable implementation.
• Prashant Yadav: Safeguarding the model—assessing arbitrage risks and proposing supply chain and traceability solutions to prevent leakage while sustaining differential prices.
Format: Moderator scene-setting: 5 minutes; Speaker presentations: 3 × 12 minutes; Audience discussion: ~20 minutes focused on implementation challenges and near-term actions.
Moderator
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Mikkel Oestergaard, PhD
Merck Sharp & Dohme International Service B.V., Zurich, Switzerland
Speakers
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Richard Xie, PhD
RA Capital Management, Newton, MA, United States
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Kalipso Chalkidou, PhD
The Global Fund to Fight AIDS, TB and Malaria, Geneva, Switzerland
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Prashant Yadav, PhD
Council on Foreign Relations, Washington, DC, United States
Health Equity in Treatment, Costs, and Care Delivery
Session Type: Research Podiums
This session explores critical dimensions of health equity, examining how socioeconomic factors, geographic location, and policy design influence access to care, treatment utilization, and health outcomes across diverse populations. Featured studies address disparities in medication expenditures, advanced therapy access, preventive care adherence, and program eligibility criteria. Collectively, these presentations offer implications for policies aimed at reducing disparities in access, utilization, and outcomes.
Moderator
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Maja Kuharic, PhD
Northwestern University Feinberg School of Medicine, CHICAGO, IL, United States
Maja Kuharic, MPharm, MSc, PhD, is an Assistant Professor in the Department of Medical Social Sciences at Northwestern University Feinberg School of Medicine. Her research focuses on patient-reported outcomes (PROs), health-related quality of life, and economic evaluation. She specializes in the development, validation, and application of PROMIS measures and preference-based instruments such as the EQ-5D and EQ-HWB.
NOT JUST GLP-1 COSTS: WHY LOWER DIABETES DRUG EXPENDITURES MAY NOT REFLECT BETTER CARE
OBJECTIVES: Because GLP-1 receptor agonist (GLP-1 RA) medications are widely used and expected to increase prescription expenditures, we evaluated how GLP-1 RA regimens, other treatment patterns, clinical complexity, and access-related factors were associated with prescription expenditures (RXEXP) among U.S. adults with diabetes.
METHODS: We analyzed pooled 2018-2021 MEPS data for adults with diabetes. RXEXP (log(RXEXP + $1)) was modeled using survey-weighted multivariable linear regression, with therapy type as the primary independent variable (SAS 9.4).
RESULTS: Results:
The analytic sample included 11,436 adults (weighted N≈22,771,988). Overall, 45.7% received non-GLP-1 monotherapy, 31.5% combination therapy without GLP-1, 12.7% GLP-1-based combination therapy, 1.2% GLP-1 monotherapy, and 8.9% no antidiabetic medication. Compared with GLP-1 monotherapy, adjusted RXEXP were 106.52% (95% CI: 81.13-139.86) for GLP-1 combinations, 34.86% (95% CI: 26.49-45.40) for combinations without GLP-1, 15.41% (95% CI: 11.78-20.14) for non-GLP-1 monotherapy, and 8.51% (95% CI: 6.15-12.64) for no therapy. RXEXP increased with complexity: vs none, 130.38% (95% CI: 116.78-145.57) with one comorbidity and 319.73% (95% CI: 195.39-523.19) with ≥4. Relative to 0-4 years, RXEXP was 162.05% (95% CI: 137.24-191.34) at 10-14 years and 238.55% (95% CI: 206.92-275.00) at ≥20 years. Lower RXEXP occurred among uninsured adults (45.39%; 95% CI: 32.12-64.14), among adults whose providers did not discuss alternative medication options (78.05%; 95% CI: 70.05-86.96), and among Hispanic (69.02%; 95% CI: 59.64-79.89) and non-Hispanic Black adults (75.82%; 95% CI: 66.20-86.84) compared with non-Hispanic Whites.
CONCLUSIONS: Prescription expenditures were higher among adults receiving GLP-1 RA regimens and among those suffering from diabetes for longer period and with greater clinical burden. Lower expenditures were observed among uninsured adults, hispanics and in visits where providers did not discuss alternative medication options to patients. Differences in expenditure may reflect variation in treatment intensity and access, while lower expenditure may sometimes signal restricted access to needed therapies rather than better quality of care.
DISPARITY CONSIDERATIONS IN AN ALTERNATIVE ELIGIBILITY CRITERION FOR MEDICARE MEDICATION THERAPY MANAGEMENT PROGRAMS WITH MACHINE LEARNING
OBJECTIVES: Evidence suggests current eligibility criteria for Medicare Medication Therapy Management (MTM) programs, which focuses on the number of chronic conditions, the number of covered medications, and an annual threshold for drug spending, may disadvantage racial/ethnic minority groups. As health plans increasingly apply predictive modeling on healthcare costs to guide MTM eligibility, these tools risk perpetuating existing disparities. This study examined whether hospitalization and emergency room (ER) costs could serve as an alternative eligibility criterion to improve minority representation in MTM enrollment and whether machine learning models reflect racial/ethnic differences.
METHODS: A cross-sectional analysis of a 10% random sample of fee-for-service Medicare beneficiaries in 2019 was conducted. The outcome was inclusion in the top quartile of hospitalization and ER expenditures. Racial/ethnic differences were assessed using a multivariable logistic regression. Five machine learning algorithms (regularized logistic regression, support vector machines, neural networks, random forest, and gradient boosting trees) were developed, with their predictions combined in a consensus model. A multivariable fractional logistic regression tested whether predicted probabilities reproduced observed racial/ethnic difference.
RESULTS: The analytic sample included 1,848,654 beneficiaries. Black beneficiaries were significantly more likely than non-Hispanic White (White) beneficiaries to be in the top cost quartile (odds ratio [OR]=1.09, 95% confidence interval [CI]=1.07-1.12), while Asian (OR=0.66, 95% CI=0.63-0.69) and Other groups (OR=0.87, 95% CI=0.85-0.89) were less likely. No significant Hispanic-White difference was observed. Machine learning models largely reproduced these patterns.
CONCLUSIONS: Hospitalization and ER costs represent a potential alternative MTM eligibility criterion that may enhance inclusion of Black beneficiaries but may lead to underrepresentation of other minority groups. Machine learning models reinforced observed differences, highlighting the importance of equity-focused design in predictive tools. Incorporating hospitalization and ER costs into MTM eligibility could extend outreach to patients with substantial acute care utilization, yet relying on this measure alone may risk overlooking other beneficiaries.
MATERIAL HARDSHIP AND MULTI-CANCER SCREENING ADHERENCE: IMPLICATIONS BEYOND INSURANCE STATUS
OBJECTIVES: Material hardship creates barriers to screening beyond insurance coverage. This study examines the association between material hardship and multi-cancer screening adherence according to the U.S. Preventive Services Task Force (USPSTF) recommendations among women aged 45-64.
METHODS: We analyzed data from the 2022 and 2024 Behavioral Risk Factor Surveillance System (BRFSS) for women aged 45-64, excluding U.S. territories and 2023 data due to a smaller sample size. Multi-screening adherence was defined as completing all three: mammography within two years (USPSTF lowered the starting age in 2024), cervical cancer screening within guideline intervals (Pap test within 3 years or HPV/co‑testing within 5 years), and colorectal cancer screening according to test‑specific intervals (1-10 years). Material hardship scale included seven indicators (medical cost burden, employment loss, food insecurity, food stamps, inability to pay bills, utility shut-off, and unreliable transportation) categorized as 0, 1, or ≥2 hardships. We used a multivariable survey‑weighted linear probability model with state and year fixed effects, adjusting for income, health status, insurance, healthcare access, other sociodemographic characteristics and psychosocial distress.
RESULTS: The analytic sample comprised 10,915 respondents representing 1,412,228 women in the population. Overall, 23.8% were adherent to all three screenings while 12.6% completed none; 31.8% reported ≥1 hardship and 94.9% had health insurance. Material hardship was inversely associated with screening adherence. Compared with no hardship, one hardship corresponded to a 5‑percentage‑point decrease (p=0.02), and ≥2 hardships to a 7‑percentage‑point decrease (p=0.01). Compared with those earning <$25,000 annually, only women earning ≥$100,000 had higher adherence (p=0.01). Insurance status was not significantly associated with adherence (p=0.96). Sensitivity analysis restricted to insured women yielded similar results.
CONCLUSIONS: Material hardship was associated with significantly lower multi-cancer screening adherence, independent of income and insurance coverage. Multi-level interventions should integrate screening with social support systems and launch targeted interventions in low-income communities to address these barriers.
MAPPING ACCESS DESERTS: A GEOSPATIAL ASSESSMENT OF SOCIOECONOMIC DISPARITIES IN THE UNITED STATES DLBCL CAR-T THERAPY NETWORK
OBJECTIVES: Chimeric Antigen Receptor T-cell (CAR-T) therapy offers curative potential for relapsed/refractory diffuse large B-cell lymphoma (DLBCL); however, administration is limited to certified centers, potentially creating geographic barriers to access. The extent of socio-spatial disparities in access to the evolving treatment network remains poorly characterized. This study mapped geographic access to CAR-T centers for DLBCL in 2025 across the contiguous United States (US) and evaluated the association between travel burden and county-level social vulnerability.
METHODS: We conducted a cross-sectional geospatial network analysis. The network included 169 manufacturer-listed authorized treatment centers for Yescarta, Kymriah, and/or Breyanzi. Using 2020 US Census population centroids for 3,108 counties to proxy geographic distribution of patient residence and potential utilization, ArcGIS Pro Network Analyst calculated driving time to the nearest center for each county. Counties were classified by driving time (<60 vs. ≥60 minutes), reflecting common CAR-T program proximity requirements. Socioeconomic vulnerability was measured using the CDC Social Vulnerability Index (SVI 2020). We employed bivariate choropleth mapping to identify "double burden" regions characterized by high driving time (≥60 minutes) and high social vulnerability (SVI≥0.66), i.e., ‘high-vulnerability access deserts’.
RESULTS: Seventy percent (229 million) of the population resides within 60 minutes of a center, while 30% (99 million) face driving times exceeding 60 minutes. Bivariate analysis identified a substantial "double burden" population: forty-four million (13%) individuals reside in high-vulnerability access deserts, a population more than twice as large (20 million) as the low-vulnerability residents (SVI<0.33) living in access deserts.
CONCLUSIONS: The 2025 US CAR-T network includes a substantial catchment population living in areas characterized by significant travel burdens and socioeconomic vulnerability. This "double burden" highlights a misalignment between network capacity and vulnerability, suggesting that the current configuration reinforces existing socioeconomic disparities. Policy interventions must be geographically targeted to these identified high-vulnerability regions to ensure equitable delivery of curative therapies.
Measuring What Matters: A New Blueprint for HEOR Impact Metrics
Session Type: Issue Panel
Topics: Organizational Practices
Track: Expanded Value Measures
Level: Intermediate
Issue:
HEOR provides the evidence needed to support affordability, value-based decision-making, and policy development, yet its strategic importance is still not consistently recognized. Traditional productivity metrics, such as publication counts or timelines, do not capture HEOR’s influence on payer strategy, evidence prioritization, policy engagement, or enterprise value. As policymakers and payers demand clearer demonstrations of value, HEOR’s inability to quantify its contributions has become a barrier to its credibility and relevance. The issue is understanding why HEOR’s impact remains difficult to measure and identifying practical approaches to clarify its role in policy, access, and value decisions.
Overview:
This 60-minute issue panel will debate the real-world challenges of demonstrating HEOR’s impact and explore contrasting viewpoints on how the field can strengthen its visibility with internal and external decision-makers. Three panelists representing biotech, midsize, and large HEOR organizations will present concise, distinct positions (10 minutes each). John will argue that HEOR undersells its influence and fails to measure the impact cross-functional partners already acknowledge. Kinga will contend that impact metrics should be grounded in how evidence is used in payer and policymaker interactions, supported by rapid feedback from integrated field teams. Jan will caution that global complexity, regional variation, and
inconsistent data flows make unified HEOR impact metrics difficult to implement and potentially misleading.
Moderated by AESARA—drawing on insights from its 2024 industry HEOR benchmarking initiative and its consulting experience in organizational transformation and evidence strategy—the session will begin by framing measurement gaps and opportunities for defining credible HEOR impact metrics. A 30-minute moderated debate and audience Q&A will challenge
assumptions and surface practical solutions.
HEOR stakeholders will leave with strategies to elevate HEOR’s visibility and better demonstrate its impact on policy, access, and enterprise decisions.
Moderator
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Yamini Misra
AESARA, Houston, TX, United States
Speakers
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Jan E Hansen, PhD
Sanofi, Scottsdale, AZ, United States
Dr. Jan Hansen is Global Head of Health Economics and Value Assessment (HEVA), which is a function in the Global Market Access organization in Sanofi's Specialty Care business. In this role, Jan oversees global health economics and outcomes research (HEOR) strategy development and tactical project execution. Her team’s work leads to impactful dissemination and application of HEOR across global stakeholders and health care systems.
Prior to joining Sanofi, Jan had an impressive career spanning over three decades in life sciences. Jan has held distinguished leadership positions at Genentech and Allergan, where she demonstrated her talent for building and guiding high-performing HEOR and access teams. Her expertise in integrating health economics and HTA considerations into development strategies has consistently led to successful product positioning and enhanced patient reach.
As a past President of ISPOR and active contributor to prestigious organizations like the National Pharmaceutical Council, AMCP Foundation, and PhRMA Foundation, Jan has established herself as a thought leader in our industry. Jan holds a Ph.D. in Pharmacy Administration from the University of South Carolina and a B.S. in Pharmacy from the University of Iowa, where she was honored with the Distinguished Alumni Award for Science.
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Kinga Borsos, MASc, MBA, PharmD
Boehringer Ingelheim, Randolph, NJ, United States
Kinga Borsos (PharmD, MSc, MBA) is a transformational HEOR and Market Access executive recognized for building and scaling high performing organizations, shaping enterprise payer strategy, and delivering evidence-driven differentiation for major global and U.S. biopharmaceutical assets. She currently serves as VP, Head of U.S. HEOR at Boehringer Ingelheim.
With deep expertise in HEOR/RWE, HTA strategy, ICER/CMS processes, and value demonstration, she has led global and U.S. evidence planning for multi indication, multi billion dollar assets. With a career spanning more than two decades across the U.S., Europe, and global markets in the pharmaceutical industry, she has led cross-functional, multi country teams and built capabilities that elevate HEOR and access as strategic drivers of launch excellence, health system engagement, and long term portfolio value. She is a builder of teams, capabilities, and systems, and a leader committed to elevating people, evidence, and strategic clarity to enable organizational success.
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John O'Donnell, MPP, PhD
Madrigal Pharmaceuticals, Thornton, PA, United States
4:45 PM - 6:00 PM
Distributional Cost-Effectiveness Analysis in Practice: Are We Facing Mountains or Molehills?
Session Type: Spotlight
Topics: Economic Evaluation, Health Technology Assessment, Methodological & Statistical Research
Track: Expanded Value Measures
Level: Advanced
As health systems confront rising costs and widening inequalities, decision-makers must look beyond how much benefit an intervention delivers to consider who benefits.
The Health Science Policy Council's Spotlight session provides a critical evaluation of distributional cost-effectiveness analysis (DCEA) as a framework for quantitatively embedding equity into value assessment. Dr Ankur Pandya will introduce the Threshold Inequality Aversion Parameter (TIAP), a methodological advance that identifies the point at which society’s preference for fairness justifies choosing a more equitable—even if less efficient—option. The discussant will provide a critique of the TIAP method and DCEA in general from a policy perspective. The session will examine methodological challenges, data requirements, remaining normative issues, and practical implications of the approach.
For DCEA enthusiasts and sceptics alike, this session offers timely and candid perspectives on equity methods for value assessment and their place in decision making.
Moderator
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Amanda Cole, BSc, PhD
Office of Health Economics, London, United Kingdom
Amanda Cole is a Director at the Office of Health Economics (OHE). She leads OHE’s Economics of Innovation theme and is an Honorary Professor of Practice at University College London, as well as a member of ISPOR’s Health Science Policy Council.
Her research focuses on value based payment models, incentives for innovation, pharmaceutical market design, and how HTA policy shapes R&D decisions. She is particularly interested in aligning reimbursement practices with emerging drug development paradigms, and in advancing the use of real world evidence to support technology development and adoption.
Amanda has a strong interest in rare diseases and serves on several advisory groups in the rare disease space. Before joining OHE, she was a research fellow at the University of Birmingham, where she earned her PhD in Health Economics in 2013.
Speakers
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James Koh, BA, MSc, PhD
NICE, Manchester, United Kingdom
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Ankur Pandya, MPH, PhD
Harvard T.H. Chan School of Public Health, Boston, MA, United States
Dr. Ankur Pandya is an Associate Professor of Health Decision Science at the Harvard T.H. Chan School of Public Health. His areas of interest are: 1) applied decision science studies evaluating cardiovascular disease policies; 2) connecting cost-effectiveness analysis with broader value-based health policies being implemented or piloted in U.S. health reform; and 3) methodological topics within cost-effectiveness modeling (calibration, validation, distributional cost-effectiveness analysis). He currently serves as the President Elect of the Society for Medical Decision-Making.
6:00 PM - 7:00 PM
Philadelphia Street Festival supported by ISPOR's Year-Round Conference Sponsors
Session Type: General Meeting
Experience the vibrant flavors of the city at our "Philadelphia Street Festival," a dynamic reception where each participating sponsor booth will offer Philadelphia-inspired food and beverage. Sponsored by ISPOR's year-round conference sponsors.
Wed May 20
7:00 AM - 8:00 AM
Coffee and Connect
Session Type: General Meeting
Head to the exhibit hall to connect with fellow attendees and exhibitors over a steaming cup of coffee.
7:00 AM - 1:00 PM
Registration Hours
Session Type: General Meeting
8:00 AM - 9:00 AM
From Engagement to Strategy: An Evidence Based Framework for Evaluating Patient-Centricity in the Pharmaceutical Industry
Session Type: Issue Panel
Topics: Organizational Practices, Patient-Centered Research, Health Policy & Regulatory
Track: Expanded Value Measures
Level: Introductory
ISSUE. Pharmaceutical companies increasingly articulate commitments to patient-centricity, yet the concept remains vague, variably defined, and inconsistently operationalized across the industry. In contrast, patient-centeredness in medicine is a well-established construct, coined by Enid Balint in 1969, expanded by Mead and Bower’s 2000 framework for doctor–patient relationships, and reinforced by the Institute of Medicine’s designation of patient-centeredness as a core dimension of healthcare quality in 2001. By contrast, the term is much newer for the pharmaceutical sector, surfacing in 1993 in the context of drug promotion and marketing and gaining traction in 2012, alongside regulatory initiatives such as the FDA’s Patient-Focused Drug Development program. In this session, panelists will propose robust frameworks with definitions, outcomes, and methods for evaluating patient centricity in the pharmaceutical industry, that can help sponsors as they develop a comprehensive patient centered corporate strategy and move beyond patient engagement in clinical research.
OVERVIEW: In this session, the moderator will provide background and characterize current practices across companies. Industry panelists will discuss case examples, frameworks and performance indicators being developed to support patient centricity and along with challenges in addressing tensions between patient and corporate goals. Patients will provide experiences and perceptions of patient centricity within the sector and recommend considerations for improving practices. An academic and ethicist will offer ethical considerations and a framework to guide pharmaceutical company-patient relationships, informed by a literature review and focus groups with patients and clinicians (in oncology and infectious disease). The outcome of this session will include proposal of comprehensive frameworks to guide pharmaceutical company-patient relationships and translate commitments into coherent organizational strategy and accountable practice.
Moderator
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Jennifer Miller, PhD
Yale School of Medicine, Westport, CT, United States
Speakers
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Pamela Gavin, BA, MBA
National Organization for Rare Disorders, Danbury, CT, United States
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Alan Balch, MS, PhD
Patient Advocate Foundation and National Patient Advocate Foundation, Hampton, VA, United States
Dr. Balch has more than 22 years of executive leadership in the non-profit sector spanning multiple advocacy areas including access and affordability, health equity, prevention and early detection, and cancer research. He became the CEO of both PAF and NPAF in 2013 and has served as a member of both Boards of Directors since 2007. From 2006-2013, he served as Vice President of the Preventive Health Partnership -- a national health promotion collaboration between the American Cancer Society, American Diabetes Association, and American Heart Association. Dr. Balch currently serves on dozens of selective boards, steering committees, and councils for an array of institutions. Most recently, Dr. Balch was selected as the Chair of the Global Patient Council for the American Patient Representatives Roundtable for the Professional Society for Health Economics and Outcomes Research (ISPOR) after serving as the Co-Chair of the North American Patient Representatives Roundtable.
Dr. Balch recently stepped into the role of Editor-in-Chief of Journal of Clinical Pathways. He has served on the editorial board and as a contributing editor for many years and on the advisory board for the Journal of Oncology Navigation and Survivorship. He is frequently invited to peer review article submissions to various publications including the Journal of Health Care for the Poor and Underserved, Journal of Clinical Oncology, American Journal of Preventive Medicine, and the American Journal of Public Health.
He earned his PhD in 2003 from the University of California Santa Cruz, his master’s degree in 1997 from the University of Texas San Antonio; and his bachelor’s degree in 1994 from Trinity University in San Antonio
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Cosmina Hogea, MS, PhD
Gilead, Foster City, CA, United States
Real-World Data and Evidence Supporting Value Assessment for Access and Reimbursement Decisions: Advancements and Experiences in US and China
Session Type: Other Breakout Session
Topics: Health Policy & Regulatory, Real World Data & Information Systems, Health Technology Assessment
Track: Real-World Evidence (RWE)
Level: Intermediate
PURPOSE: The objective of this session is to explore, with series of new national initiatives, how real-world data (RWD) and real-world evidence (RWE) can better support comprehensive value assessment of innovative drugs for access and reimbursement decisions in the US and China. It offers a multi-stakeholder perspective on policy progress, international experience, and industry implications.
DESCRIPTION: In recent years, the US and China have increasingly embraced RWD/RWE in access and reimbursement decisions, such as Medicare Part D and National Reimbursement Drug List (NRDL) negotiations, respectively. However, despite this progress, gaps and barriers remain. The session will begin with an introduction of the context and current status (5 minutes, Xie).
The next speaker will then discuss China’s evolving policy environment and key initiatives (e.g., real-world research pilot for comprehensive value assessment), along with the administration’s vision and expected outcomes. Challenges in integrating RWE into value assessment and reimbursement decisions in China will also be addressed (15 minutes, He).
The session will continue with a comparative analysis of RWE’s role in Medicare Part D vs. China’s NRDL reimbursement pathway. Specifically, the role of RWE in the first round of US Medicare Part D negotiations and recent price reduction in weight management products will be examined, offering insights for China’s evolving system (15 minutes, Shi).
The last speaker will then provide a global pharmaceutical industry perspective. The impact of recent RWE-related policy shifts on market access strategy, the operational and technical barriers, and examples of RWE successfully supporting value assessment will be shared (15 minutes, Tang).
The session concludes with a 10-minute panel discussion among presenters and the audience, addressing open questions and practical recommendations to strengthen the RWE ecosystem for drug value assessment, especially in evolving markets like China.
This session will benefit all HTA professionals, policymakers, pharmaceutical manufacturers, and RWE researchers.
Moderator
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Yang Xie, MPH, PhD
IQVIA, Shanghai, China
Speakers
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Xiaoning He, PhD
Tianjin University, Tianjin, China
Associate Professor, Major in Health and Pharmacy Administration, School of Pharmaceutical Science and Technology, Tianjin University. Visiting Scholar during Sep, 2019 to Mar, 2020 in the University of Sheffield in the UK.
Research directions: Pharmacoeconomics, Real-World Research, Health Equity, and Health Policy Evaluation.
PI for 1 General Program and 1 Youth Program of the National Natural Science Foundation of China, 1 Youth Program of the Natural Science Foundation of Tianjin.
Published more than 50 journal papers, including over 30 SCI & SSCI papers in journals such as Value Health and Pharmacoeconomics.
Participated in compiling Pharmacoeconomic Evaluation Guidelines in China 2020.
Member and Secretary of the Pharmacoeconomics Professional Committee of the Chinese Pharmaceutical Association, Member of the Pharmacoeconomics Professional Committee of the Chinese Research Hospital Association, Member of the Health Technology Economic Evaluation Professional Committee of the Chinese Health Economics Association, Member of the Real-World Research Professional Committee of the Chinese Association of Chinese Materia Medica, Member and Secretary of the Pharmacoeconomics Professional Committee of the Tianjin Pharmaceutical Association.
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Zhiliu Tang, Dr
GSK, Shanghai, China
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Lizheng Shi, PhD
Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, United States
Lizheng Shi, PhD, MsPharm, MA, is the Neal A. and Mary Vanselow Endowed Chair in the Department of Health Policy and Management at the School of Public Health and Tropical Medicine of Tulane University. He is the founding director of Tulane’s Health Systems Analytics Research Center (HSARC). Dr. Shi’s current health services research interest focuses on innovative health technologies to improve healthcare quality, access, and cost of patient-centered care from the equity perspective, using pharmaco-economics, health technology assessment, health analytics, and policy evaluation. Dr. Shi is dedicated to disseminating and translating population health knowledge at the local, national, and international levels. He is the associate editor of Value In Health and co-editor in chief for Pharmacoeconomics and Policy.
A Rare Dilemma: How to Fit an Unfittable Into Current HTA Paradigm
Session Type: Issue Panel
Topics: Health Policy & Regulatory, Health Technology Assessment, Real World Data & Information Systems
Track: Access and Drug Pricing
Level: Intermediate
ISSUE: Rare diseases (RDs) expose critical limitations in traditional frameworks. Small, heterogeneous populations, surrogate endpoints, single-arm trials, and lack of natural history data make it difficult to apply conventional evaluation methods. These challenges result in significant delays to patient access, as payers and manufacturers struggle to reconcile clinical uncertainty with pricing and value. Dominant QALY-based frameworks—used by 90% of OECD countries—may fall short in capturing the nuanced value of rare disease treatments, further compounding access barriers. This panel will explore how select HTA systems have adapted their frameworks to better accommodate RDs specificities, and which best practices should be implemented more broadly.
OVERVIEW: According to the EU WAIT indicator, time to reimbursement for RDs therapies remains significantly longer than for non-RD across Europe and currently stands at an average of 607 days without significant improvement over the last 5 years.
Diana Sinkevich will first clearly state the issue and present how some EU HTA bodies have begun adapting their HTA frameworks due to growing recognition of the need for flexibility (e.g. UK, Germany, Scotland, Sweden, Netherlands).
Dr. Santos will present the CONITEC approach to RDs HTA evaluations and discuss that in the absence of specific pathway for RDs in Brazil, CONITEC takes a pragmatic approach and rely on evidence-collection post-approval.
Dr. Alyami will discuss the broader evolution of HTA in Saudi Arabia, and highlight how international best practices that support the assessment of RD evidence packages are being incorporated into evolving HTA.
Lastly, Dr. Wong-Rieger will discuss the Canadian experience as well as the patient expectation from the HTA bodies and the role patients play in supporting HTA bodies in minimizing uncertainties.
Stakeholders who will benefit include HTA agencies, payers, industry leaders, patient advocates, and policy makers seeking to improve equity and timeliness in rare disease access.
Moderator
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Dziyana Sinkevich, BSc, MSc
Chiesi, parma, Italy
Speakers
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Marcos Santos, MSc, PhD
ISPOR Brazil Chapter, Sao Paulo, Brazil
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Fatimah Alyami
Center of Health Technology Assessment, Riyadh, Saudi Arabia
Dr. Fatimah Alyami is a senior health economist and licensed senior pharmacist with
over a decade of multidisciplinary experience spanning health economics, health
technology assessment (HTA), pharmaceutical policy, and clinical pharmacy. She
currently serves as Health Economic Assessment Senior Specialist at the Center of
Health Technology Assessment within the Center for National Health Insurance (CNHI),
where she leads the design and appraisal of economic evaluations, value-based
healthcare models, and evidence-based policy strategies tailored to the Saudi
healthcare system.
Dr. Alyami holds a PhD in Pharmaceutical Science (Health Outcomes) from the
University of Cincinnati, along with dual master’s degrees in Pharmaceutical Economics
& Policy and Pharmaceutical Outcomes & Policy. She is an active member of ISPOR,
ISPE, and the Saudi Pharmaceutical Society, with research presented at leading
international conferences and published in peer-reviewed journals. Recognized for her
leadership and scholarly contributions, Dr. Alyami brings a strong commitment to
advancing value-driven, evidence-based decision-making to improve healthcare
efficiency, sustainability, and patient outcomes in Saudi Arabia.
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Durhane Wong-Rieger, PhD
Canadian Organization for Rare Disorders, Toronto, ON, Canada
Dr. Durhane Wong-Rieger is the president and CEO of the Canadian Organization for Rare Disorders. She holds a Ph.D. in psychology from McGill University and previously served as a professor at the University of Windsor. Internationally, she is president of the Asia Pacific Alliance of Rare Disease Organisations, treasurer of the United Nations Nongovernmental Committee for Rare Diseases, patient advisor to the APEC Rare Disease Network, member of the International Research Consortium on Rare Diseases and RDI-Lancet Commission on Rare Diseases as well as board member of Testing to Targeted Treatments (FT3). She is Co-Founder and Immediate Past Chair of Rare Diseases International. In Canada, she is chair of the Consumer Advocare Network, president and CEO of the Institute for Optimizing Health Outcomes, and chair of the Canadian Heart Patient Alliance. She is currently Co-Chair of the Implementation Advisory Group of Canada’s National Strategy on Drugs for Rare Diseases. A certified health coach, trainer, and frequent lecturer, Dr. Wong-Rieger has authored three books and multiple articles.
Productivity Gains From Generative AI Across the HEOR Workflow: Successful Case Studies
Session Type: Other Breakout Session
Topics: Economic Evaluation, Health Technology Assessment, Health Policy & Regulatory
Track: AI
Level: Introductory
Purpose
Generative AI (GenAI) is increasingly being adopted for systematic literature reviews, yet its broader potential to accelerate additional components of the HEOR workflow—such as health economic model development and verification, and HTA submissions—remains under-recognized. The objective of this session is to present real-world applications that provide concrete evidence of GenAI’s ability to enhance efficiency, improve productivity, and maintain methodological rigor across diverse HEOR activities.
Description
This session will feature practitioner-led case studies illustrating how GenAI is being successfully deployed to gain productivity. The session will be moderated by Uwe Siebert, who will introduce recent advances in GenAI technologies and discuss their emerging role in reshaping HEOR workflows, quality standards, and evidence generation practices.
Jag Chhatwal will present a case study on the use of GenAI to automate components of health economic model verification, including a project conducted in collaboration with NICE. He will describe how GenAI-enabled workflows applied standard verification checklists with significant efficiency gains while preserving transparency and methodological rigor.
Ipek Stillman will share insights from a GenAI-supported health economic model replication project performed in industry. This presentation will highlight both the benefits and the challenges encountered when using GenAI into complex modeling tasks.
Turgay Ayer will demonstrate how 1000+ agentic GenAI systems were used to generate comprehensive landscape assessment reports within 48 hours. Their case study will illustrate how multi-agent architectures can coordinate evidence gathering, synthesis, and narrative development across large information spaces to inform HEOR work.
The session will conclude with a moderated discussion on best practices, limitations, risks, and key considerations for responsibly and effectively incorporating GenAI into HEOR workflows, along with implications for long-term productivity, methodological standards, and expectations of regulatory and HTA bodies.
Moderator
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Uwe Siebert, MPH, MSc, ScD, MD
UMIT TIROL - University for Health Sciences and Technology; Harvard Chan School of Public Health, Hall in Tirol, Austria
Uwe Siebert, MD, MPH, MSc, ScD, is a professor of Public Health, Medical Decision Making and Health Technology Assessment (HTA), chair of the Department of Public Health, Health Services Research and HTA at UMIT TIROL-University for Health Sciences and Technology in Austria and director of the Division for HTA in the ONCOTYROL–Center for Personalized Cancer Medicine in Austria. He is also adjunct professor of Epidemiology and Health Policy & Management at the Harvard T.H. Chan School of Public Health and Affiliated Researcher in the Program on Cardiovascular Research at the Institute for Technology Assessment and Department of Radiology at the Massachusetts General Hospital, Harvard Medical School, Boston.
After medical school, he worked for several years as a physician in international public health projects in West Africa, Brazil, and Germany. He then earned an MPH at the Munich School of Public Health and completed an MSc in Epidemiology and a ScD in Health Policy and Management with a concentration in decision sciences at the Harvard School of Public Health.
His research interests include applying real-world evidence-based quantitative, causal and translational methods from public health, epidemiology, artificial intelligence, comparative effectiveness research, health services and outcomes research, economic evaluation, modeling, and health data a d decision science in the framework of health care policy advice and HTA as well as in the clinical context of routine health care, clinical guideline development, public health policies and patient guidance. His research focuses on cancer, infectious disease, cardiovascular disease, neurological disorders, and others.
He has been leading projects/work packages in several EU FP7, H2020 and Horizon Europe projects (eg, ELSA-GEN, BiomarCaRE, MedTecHTA, DEXHELPP, EUthyroid, FORECEE, MDS-RIGHT, RECETAS, CORE-MD, EUREGIO-EFH, CIDS, OnCoVID, 4D PICTURE, CATALYSE). He teaches HTA, health economics, modeling, epidemiology, causal inference and target trial emulation, and data and decision science for academia, industry, and health authorities in Europe, North and South America, and Asia. He directs the Continuing Education Program on Health Technology Assessment & Decision Sciences (htads.org).
He has served as member of the ISPOR Directors Board and as president of the Society for Medical Decision Making (SMDM). He is a leadership member of the ISPOR Personalized/Precision Medicine SIG, a member of the Latin America Consortium Advisory Committee of ISPOR, and co-chair of the ISPOR-SMDM Modeling Good Research Practices Task Force. He is a member of the Oncology Advisory Council and the National Committee for Cancer Screening of the Austrian Federal Ministry of Health.
He has authored more than 400 publications (> 30,000 citations, H index > 80), and is editor of the European Journal of Epidemiology. Further information Internet: http://htads.org, umit-tirol.at/dph, hsph.harvard.edu/uwe-siebert, Twitter: @UweSiebert9, LinkedIn: uwe-siebert9.
Speakers
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Jag Chhatwal, PhD
Harvard Medical School / Massachusetts General Hospital, Boston, MA, United States
Jag Chhatwal, PhD, is the director of the Institute for Technology Assessment at Massachusetts General Hospital and an associate professor at Harvard Medical School. He also serves as core faculty at the Center for Health Decision Science, Harvard T.H. Chan School of Public Health. Dr. Chhatwal has co-authored more than 125 original research articles and editorials in leading peer-reviewed journals. His research has informed health policy decisions at prominent organizations including the White House, the World Health Organization, and the CDC, and has been featured in major media outlets such as CNN, Forbes, National Public Radio, The New York Times, and The Wall Street Journal. Dr. Chhatwal serves as an associate editor of Value in Health and as guest editor for its special issue on artificial intelligence. He is also a member of the ISPOR Generative AI Working Group.
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Ipek Ozer Stillman, MBA, MSc
Takeda, Cambridge, MA, United States
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Turgay Ayer, PhD
Value Analytics Labs, Boston, MA, United States
Turgay Ayer, PhD, holds the Virginia C. and Joseph C. Mello Chair and serves as the research director for Healthcare Analytics and Business Intelligence at the Center for Health & Humanitarian Systems at Georgia Tech. He is also the chief technology officer at Value Analytics Labs. Dr. Ayer holds a courtesy appointment at Emory Medical School where he teaches Big Data Analytics courses and serves as a Senior Scientist at the Centers for Disease Control and Prevention (CDC). Dr. Ayer’s research focuses on health economics modeling (HEOR), real-world evidence, data science, machine learning, econometric modeling, and healthcare analytics. He has published over 80 peer-reviewed journal papers and more than 300 conference abstracts, with his work featured in top-tier business, engineering, medical, and health policy journals. His research has attracted substantial attention from major media outlets, including The Wall Street Journal, The Washington Post, US News, and NPR. A recognized expert in HEOR, Dr. Ayer has been at the forefront of applying generative AI to navigate healthcare systems and support better decision-making. He has contributed significantly to the development of advanced models for predicting healthcare outcomes and designing innovative cost-effectiveness analysis frameworks. Under his leadership, Value Analytics Labs has focused on the development of cutting-edge technologies, including ValueGen.AI, to enhance healthcare analytics and improve the efficiency of healthcare decision-making processes.
Patient-Centered Clinical Trial Design: Using Patient Experience Research to Improve the Patient-Centeredness of Patient-Reported Outcomes Measures and Patient Preference Research to Prioritize Patient-Centered Endpoints
Session Type: Other Breakout Session
Topics: Patient-Centered Research, Methodological & Statistical Research, Study Approaches
Track: Expanded Value Measures
Level: Introductory
Purpose: Discuss challenges and considerations in using patient experience and patient preference research to:
1. assess the patient-centeredness of patient reported outcome measures (PROMs) used in clinical trials and
2. understand how patients prioritize among meaningful aspects of health (MAH).
Description: The FDA’s patient focused drug development (PFDD) program encourages use of patient reported outcomes (PRO) and patient preference information (PPI) throughout the product development lifecycle. The identification of MAH can inform endpoint selection in patient-centered clinical trial design.
In an FDA-sponsored study, we assessed symptoms and function and PROMs used for genitourinary syndrome of menopause (GSM). Qualitative interviews followed by a best-worst scaling (BWS) survey were conducted to examine MAH in GSM. The findings describe patient priorities among MAH, and can inform selection of patient-centered trial endpoints and future adaptations of existing PROMs.
The GSM study will highlight challenges and lessons learned. The session will start with an overview of, and practical considerations for, use of patient experience evidence in endpoint selection (Poulos, 8 minutes). Dr. Peay will describe qualitative research to identify gaps in PROs used for GSM and identify ways to improve patient-centeredness (14 minutes). Dr. Poulos will describe the application of Case 1 BWS to prioritize MAH and the conceptual and methodological challenges in this application of PPI (14 minutes). Dr. Roberts will describe the FDA’s perspective on the value of this type of patient-centered research and how it may be used in FDA decision making and advice (14 minutes). Speakers will attend to challenges including a common but heterogeneous syndrome, underinformed patients, poorly defined symptoms and symptom impacts, and lack of specific PROMs. Interactive polling will be used to engage participants.
The session will conclude with an interactive discussion on pragmatic approaches to ensuring that the potential for patient-centered clinical trial design is realized (10 minutes).
Moderator
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Christine Poulos, PhD
RTI- Health Solutions, Research Triangle Park, NC, United States
Speakers
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Holly Peay, MS, PhD
Faegre Drinker Biddle & Reath, Washington, DC, United States
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Jason Roberts, PhD
US Food and Drug Administration, Silver Spring, MD, United States
Rewriting the Global Evidence Playbook: China’s Emergence as a Strategic Hub for Evidence Generation
Session Type: Issue Panel
Topics: Real World Data & Information Systems, Health Policy & Regulatory, Health Technology Assessment
Track: Access and Drug Pricing
Level: Intermediate
ISSUE:
China’s biopharmaceutical ecosystem is moving from “in China for China” to a bidirectional evidence model linking China and ex-China decisions. China’s stronger science, faster R&D, and growing pipeline are driving multinationals to source Phase 1/2 assets from Chinese innovators, increasing demand for China-generated clinical data to support global development (“in China for ex-China”). When trial design, execution, and quality align with global standards, these data are increasingly portable, enabling earlier development, indication expansion, and post-approval commitments. China real-world evidence (RWE), however, is not yet broadly transferable for ex-China payer/HTA use. Gaps in data provenance, coding, care pathways, representativeness, and governance limit comparability. This clinical-versus-RWE split raises practical questions about what China evidence can support globally today, and what must change for RWE to contribute tomorrow.
Rare disease is a key proving ground. Diagnostic uncertainty, thin epidemiology, and heterogeneous care are major access and value barriers worldwide. In China, uneven diagnosis and limited natural-history data can deepen uncertainty; yet lower-cost, high-speed study infrastructure may enable faster trials and natural-history cohorts that strengthen both China filings and ex-China indication expansion. The landscape demands a new evidence playbook.
OVERVIEW:
Presentations (~15 minutes each) will cover:
• Why China clinical evidence is becoming globally acceptable and how to make trials exportable.
• Why China RWE remains limited for ex-China use and what advances could narrow the gap.
• Bidirectional frameworks for using ex-China evidence in China and China evidence ex-China, including hybrid designs.
• Rare disease methods to reduce diagnostic/epidemiologic uncertainty and enable indication expansion.
The panel will conclude with audience debate to identify principles and guardrails for integrating China and global evidence streams to improve patient access.
Moderator
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Lung-I Cheng, PhD
AESARA, Somerville, MA, United States
Speakers
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Sheng Feng
LinkDoc Technology, Beijing, China
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Kasey Fu, DrPH
Vertex, Boston, MA, United States
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Hui Huang, PhD
CSD Partners, Boston, MA, United States
Multi-Agent AI and Interoperability: Advancing Reliable, Transparent Evidence Generation in HEOR
Session Type: Issue Panel
Topics: Methodological & Statistical Research
Track: AI
Level: Intermediate
Issue: Retrieval-Augmented Generation (RAG) is rapidly becoming a cornerstone for grounding evidence in HEOR workflows. By anchoring outputs in sourced literature and real-world data, RAG ensures that evidence generation is both transparent and traceable. Multi-agent architectures build on this foundation by orchestrating specialized agents to collaboratively process complex HEOR tasks, in which each agent has distinct roles such as document retrieval, synthesis, validation, and communication. This modular approach allows for consistency and reliability across the entire evidence generation pipeline, as each agent can leverage RAG to verify information and maintain a clear chain of reasoning.
As HEOR processes scale, interoperability emerges as a critical enabler. Seamless communication among diverse agents and platforms ensures that data, context, and reasoning can be exchanged without loss of fidelity or meaning. The Model Context Protocol (MCP) addresses this challenge by offering a standardized framework for sharing contextual information, evidence, and logical reasoning among systems. MCP supports reproducibility, facilitates integration with regulatory workflows.
This panel will present a comprehensive overview of how multi-agent architectures, RAG, and MCP have the potential to reshape the landscape of evidence generation in HEOR. System designers will share practical insights on interoperable, modular AI-driven solutions, while an HTA representative will discuss expectations around transparency, governance, validation, and responsible AI use. Attendees will gain an understanding of the opportunities and governance perspectives for deploying these advanced architectures.
Overview: (5 min) Bill Malcolm: Introduction to multi-agent AI, interoperability, and MCP in HEOR/HTA. (10 min) Rajdeep Kaur: Agentic AI and RAG: how agentic systems interact with RAG for evidence retrieval, grounding, and workflow integration. (15 min) Sven L Klijn: Multi-agent architectures: designs, coordination, and interoperability challenges. (15 min) Daniel Ollendorf : HTA perspective: expectations for interoperable, agentic systems. (15 min) Audience Q&A
Moderator
Speakers
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Rajdeep Kaur, PhD
Pharmacoevidence Pvt. Ltd., Mohali, India
Dr. Rajdeep Kaur is the Lead of AI Sciences at Pharmacoevidence, with a Ph.D. in Computer Science and Engineering and 17+ years of expertise in advanced technologies. Her work focuses on Generative AI, machine learning, and cloud-enabled data systems, with a strong emphasis on real-world healthcare applications. She has successfully led multiple GenAI projects, combining deep technical expertise to deliver impactful AI-driven solutions.
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Sven L Klijn, MSc
Bristol Myers Squibb, Utrecht, Netherlands
Sven Klijn is director at Bristol Myers Squibb in the Global HEOR Economic & Predictive Modeling group, where he leads the innovative modeling agenda in hematology and cell therapy. In addition, Sven has an active role in providing modeling education and masterclasses at international congresses. He has widely published on innovative methods, especially in the field of survival extrapolation and Generative AI. Sven has training in public health and health economics and previously had various roles in CROs related to health economic modeling.
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Dan Ollendorf, MPH, PhD
Institute for Clinical & Economic Review, Boston, MA, United States
Advancing Patient-Centered Health Technology Assessment to Strengthen Equity and Transparency in Latin American Health Systems
Session Type: Issue Panel
Topics: Health Technology Assessment, Patient-Centered Research, Real World Data & Information Systems
Track: Real-World Evidence (RWE)
Level: Introductory
ISSUE: Over the past four decades, Latin America (LATAM) health systems have increasingly adopted participatory governance, reflecting broader democratic transition. In parallel, patient-centricity has become a core principle in research, value assessment and health technology assessment (HTA). Several HTA bodies in LATAM now formally acknowledge patient and citizen involvement (PCI) as essential to transparent, equitable, and legitimate decision-making. Yet meaningful implementation remains inconsistent and often disconnected from internationally used evidence-informed frameworks. The session will explore main successes and challenges in LATAM, how the region can learn from international good practices and frameworks, including those used in Canada and Europe, adapting to its local context considering governance capacity, patient heterogeneity, and structural inequities. We will also discuss how the global community can learn from LATAM experiences and successes.
OVERVIEW:
Ramiro Gilardino (5 min) will contextualize the global evolution of patient involvement in HTA, highlighting how lived experience, real-world evidence, and co-creation increasingly influence value frameworks and reimbursement decisions.
Aline Silva (15 min) will present the current state of PCI in LATAM HTA, including including successes, persistent gaps, sustainability challenges, and recommendations based on global good practices/frameworks and learnings from a five-year implementation of a framework to improve PCI in Brazil’s HTA system.
Helaine Capucho (15 min) will offer an industry perspective, reflecting on opportunities and limitations for integrating PCI across public and private systems in Brazil, and identifying enablers such as capacity-building, predictable processes, and transparent governance.
Veronica Gousset (15 min) will share methodological approaches to planning, evaluating, and reporting the impact of patient involvement, focusing on how HTA agencies and stakeholders can measure value, reduce burden, and ensure equitable participation.
A 10-minute Q&A will engage multiple stakeholders interested in improving patient-centricity and HTA.
Moderator
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Ramiro E Gilardino, MSc, MD
R-Impact, Dubendorf, Switzerland
Impact-driven healthcare executive with 15+ years of leadership in Global Market Access, Health Policy, and HEOR. Successfully led strategies that improved patient access, drove reimbursement success, and shaped health policy in pharma, biotech, and global organizations. Expert in advancing HTA frameworks and forging stakeholder partnerships to promote health equity and deliver value-based healthcare solutions globally.
Speakers
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Aline Silva Silveira, PhD
Patient Voices Network and HTAi Patient and Citizen Involvement Interest Group, Brasila, Brazil
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Veronica Lopez Gousset, MPH
Harvard T.H. Chan School of Public Health, Paris, France
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Helaine Capucho, PhD
Interfarma, São Paulo, Brazil
8:30 AM - 10:00 AM
Networking Breakfast Bites (Exhibit Hall)
Session Type: General Meeting
Join us for Networking Breakfast Bites, designed to kickstart the final day of ISPOR 2026, with light refreshments and valuable networking opportunities.
8:30 AM - 11:30 AM
Exhibit Hall Hours
Session Type: General Meeting
8:45 AM - 9:45 AM
Real-World Burden in Clinical Practice
Session Type: Research Podiums
This session highlights how real-world data can be leveraged to quantify clinical burden, treatment impact, and patient vulnerability across diverse care settings and disease areas. Featured studies demonstrate the value of real-world evidence in identifying high-risk populations, informing clinical decision-making, and guiding strategies to optimize care delivery and resource allocation in routine practice.
Moderator
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Aaron N Winn, MPP, PhD
University of Illinois at Chicago, Chicago, IL, United States
REAL-WORLD TREATMENT PATTERNS AND OUTCOMES IN PATIENTS WITH MUSCLE-INVASIVE BLADDER CANCER TREATED WITH RADICAL CYSTECTOMY BY CISPLATIN ELIGIBILITY STATUS: A US MULTICENTER CHART REVIEW STUDY
OBJECTIVES: Patients with muscle-invasive bladder cancer (MIBC) remain at substantial risk for recurrence after radical cystectomy (RC), with particularly poor outcomes among those who are ineligible for cisplatin-based chemotherapy. Real-world evidence describing treatment patterns and outcomes in these subgroups is limited. We assessed clinical characteristics, treatment patterns, outcomes, and the correlation of real-world event-free-survival (rw-EFS) with overall survival (OS) in patients with MIBC undergoing RC stratified by cisplatin-eligibility.
METHODS: A retrospective chart review was conducted across 8 US academic medical centers. Adults with MIBC who underwent RC from 01Jan2009-31Dec2018 were included and classified as cisplatin-eligible or -ineligible based on Galsky criteria. Descriptive analyses summarized characteristics and outcomes of interest. Kendall’s tau, using Clayton and Gumbel copula models, assessed the rw-EFS-OS association.
RESULTS: The cohort included 430 patients (cisplatin-eligible: n=373; cisplatin-ineligible: n=57). Median age was 67.0 years (cisplatin-eligible: 66.0 y; cisplatin-ineligible: 72.0 y), most were male (76.7%), White (85.8%), and had ≥1 comorbidity (90.2%). At surgery, 37.5% of cisplatin-eligible patients and 56.7% of cisplatin-ineligible patients had pT3 or pT4 disease. Among patients who received neoadjuvant therapy (cisplatin-eligible: 65.4%; cisplatin-ineligible: 24.6%), the pCR rates were 31.9% (74/232) and 15.4% (2/13), respectively. Median rw-EFS, metastatic disease-free survival, and OS were 85.3, 80.9, and 113.1 months, respectively, for cisplatin-eligible patients, and 33.6, 38.9, and 58.1 months, respectively, for cisplatin-ineligible patients. Across models, rw-EFS was associated with OS (Clayton Kendall’s Tau: 0.786 [95% CI: 0.739, 0.835]; Gumbel Kendall’s Tau: 0.760 [95% CI: 0.708, 0.811]), with consistent subgroup analyses.
CONCLUSIONS: In this multicenter, real-world, RC-treated MIBC cohort, cisplatin-ineligible patients had lower receipt of neoadjuvant therapy, higher pathologic stage at surgery, and poorer outcomes compared to cisplatin-eligible patients. rw-EFS demonstrated a strong patient-level correlation with OS across cisplatin-eligibility strata. These findings help establish a contemporary benchmark of treatment patterns and outcomes preceding recent approvals.
COMPARING THE RISK OF CHRONIC OBSTRUCTIVE PULMONARY DISEASE EXACERBATIONS BETWEEN GABAPENTINOIDS AND DULOXETINE
OBJECTIVES: Gabapentinoids reduce excitatory neurotransmission in the brainstem respiratory pathway—which may impair mucus clearance—but their antioxidant and immunomodulatory properties could mitigate COPD-related oxidative stress. Given these competing mechanisms and limited evidence, we evaluated the risk of exacerbations among patients with COPD initiating gabapentinoids versus duloxetine.
METHODS: We conducted a new-user active-comparator retrospective cohort study using 2019-2023 MarketScan® Commercial claims data. Adults with COPD (≥41 years) were included if initiating gabapentinoids (i.e., gabapentin, pregabalin) or duloxetine without prior use of either drug for ≥365 days. The primary outcome, severe COPD exacerbation, was defined as hospitalization with a primary diagnosis of COPD or primary diagnosis of respiratory failure and secondary COPD. Secondary outcomes included moderate exacerbation—outpatient or emergency visits for COPD and oral systemic corticosteroid within 7 days—and a composite of moderate/severe exacerbations. We fit inverse probability of treatment weighted (IPTW) Cox proportional hazards regression models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs); IPTWs were estimated from demographics, comorbidities, and baseline medication use. We assessed proportional hazards using log-log survival curves. A secondary stratified Cox model with a 30-day cut point was fit based on evidence of non-proportional hazard.
RESULTS: Among 110,867 patients initiating gabapentinoids (n=94,658) or duloxetine (n=16,209), there were 3,126 severe (median follow up time=283 vs 280 days) and 8,299 moderate (264 vs 262 days) COPD exacerbations. Patients initiating gabapentinoids demonstrated no difference in severe (HR 1.03; 95%CI: 0.92-1.15), moderate (0.96;0.90-1.02), or composite (0.96;0.91-1.02) COPD exacerbations. In the secondary model, the hazards of severe exacerbation were higher during the first 30 days following gabapentinoid initiation (HR 1.39; 95%CI: 1.07-1.79) but not thereafter (HR 0.97; 95%CI: 0.87-1.08).
CONCLUSIONS: Gabapentinoid initiation was not associated with an overall increased risk of COPD exacerbation versus duloxetine, although risk of severe exacerbations was higher during the first 30 days after initiation and then attenuated.
REAL-WORLD SAFETY PROFILE OF PEMBROLIZUMAB VS. NIVOLUMAB AND CETUXIMAB IN ADULTS WITH HEAD AND NECK SQUAMOUS CELL CARCINOMA: A COMPARATIVE ANALYSIS
OBJECTIVES: Head and neck squamous cell carcinoma (HNSCC) remains a major cause of morbidity and mortality in the U.S., largely driven by tobacco, alcohol, and human papillomavirus (HPV) infection. Immunotherapy, particularly pembrolizumab, has replaced cetuximab-based chemotherapy as first-line treatment for recurrent or metastatic disease but introduces immune-related adverse events, including pneumonitis, mucositis, thyroid dysfunction, anemia, and neutropenia. However, real-world comparative safety data across HNSCC treatments remain limited. This study aimed to compare the risk of immune-related adverse events associated with pembrolizumab, as the reference group, versus nivolumab and cetuximab among HNSCC patients.
METHODS: Using retrospective electronic health record data from TriNetX, we compared adverse event risks between pembrolizumab and nivolumab or cetuximab after propensity score matching on biological and comorbidity factors. Risk estimates included hazard ratios (HRs) and odds ratios (ORs). Time-to-event outcomes were assessed using Kaplan-Meier curves with log-rank tests.
RESULTS: After matching, 3,518 patients were included in the pembrolizumab-nivolumab comparison and 4,107 in the pembrolizumab-cetuximab comparison. Compared with nivolumab, pembrolizumab was associated with higher risk of pneumonitis (HR = 1.11 [1.01-1.22], p = 0.030), oral mucositis (HR = 1.29 [1.11-1.49], p = 0.001), hemolytic anemia (HR = 1.28 [1.13-1.44], p < 0.001), and neutropenia (HR = 1.54 [1.33-1.78], p < 0.001), while hyperthyroidism risk was lower (HR = 0.74 [0.61-0.89], p = 0.002). Compared with cetuximab, pembrolizumab showed lower hazard of oral mucositis (HR = 0.32 [0.29-0.37], p < 0.001) but higher hazards of hypothyroidism (HR = 1.50 [1.34-1.67], p < 0.001), hyperthyroidism (HR = 2.47 [1.90-3.22], p < 0.001), and hemolytic anemia (HR = 1.66 [1.46-1.89], p < 0.001).
CONCLUSIONS: Pembrolizumab was associated with higher risks of hematologic and thyroid adverse events than cetuximab but lower oral mucositis. Compared with nivolumab, it showed higher risks of mucositis and anemia but lower hyperthyroidism, which may inform treatment selection based on toxicity risk.
REAL-WORLD HEALTHCARE RESOURCE UTILIZATION AND COSTS OF HOSPITAL-ONSET METHICILLIN-RESISTANT STAPHYLOCOCCUS AUREUS NON-VENTILATOR-ASSOCIATED PNEUMONIA IN U.S. HOSPITALS: 2023-2025
OBJECTIVES: Hospital-onset methicillin-resistant Staphylococcus aureus (MRSA) non-ventilator-associated pneumonia (NVAP) represents a serious clinical challenge and imposes considerable economic burden. Recent evidence on healthcare resource utilization (HCRU) and costs for these infections is limited. This study assessed real-world HCRU, costs, and clinical outcomes associated with hospital-onset MRSA NVAP in the U.S.
METHODS: We conducted a retrospective cohort analysis using the Premier Healthcare Database. Hospitalizations of adult patients (≥18 years) with microbiologically confirmed hospital-onset MRSA NVAP who were discharged between January 1, 2023, and June 30, 2025, were included. HCRU, including length of stay (LOS), ICU utilization, in-hospital mortality, and 180-day readmissions, and costs for index hospitalization and follow-up were reported.
RESULTS: A total of 1,103 hospitalizations met inclusion criteria. Median LOS was 15 days (IQR: 8-32), and median index hospitalization cost was $52,013 (IQR: $23,625-$123,650). ICU admission occurred in 63.7% of patients, with a median ICU LOS of 10 days (IQR: 4-19) and median ICU cost of $67,182 (IQR: $29,098-$134,225). In-hospital mortality was 33.7%. Of those surviving the index hospitalization (n=901), within 180 days of discharge, 53.6% (n=483) had all-cause readmissions, and 26.1% (n=235) had NVAP-related readmissions. Median time to first readmission was 27 days (IQR: 12-63). The cumulative 180-day cost for all-cause readmissions was $40,898 (IQR: $19,166-$86,417) among those with any readmission in that period.
CONCLUSIONS: Hospital-onset MRSA NVAP imposes a considerable clinical and economic burden, characterized by extended hospital stays, ICU utilization, and high mortality. The substantial costs associated with both initial infection and subsequent readmissions highlight the need for more effective infection control measures and improved treatment and discharge planning. Strategies aimed at reducing recurrence and optimizing care pathways could significantly mitigate resource use and improve patient outcomes.
Medical Devices and Diagnostics: Economic Evaluation to Inform Decisions
Session Type: Research Podiums
This session examines how health economic evidence is translated into real-world decisions for medical devices and diagnostics across the technology lifecycle. Presentations span early health economic modeling under uncertainty, methodological standards for device HTA, budget impact and affordability analyses, and broader system-level implications. Together, the session illustrates how decision-relevant economic evidence can meaningfully inform HTA, payer, provider, and procurement decisions for non-pharmaceutical technologies.
Moderator
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Michael J Cangelosi, MA, MPH
Boston Scientific, Natick, MA, United States
DECISION-RELEVANT EARLY HEALTH ECONOMIC MODELLING TO INFORM DEVELOPMENT AND INVESTMENT IN EMERGING HEALTH TECHNOLOGIES
OBJECTIVES: To examine how early health economic modelling (EHEM) can support development and investment decision-making for diagnostics, medical devices, and digital health technologies (DMDD), and to identify recurring decision-relevant insights generated through early modelling under conditions of high uncertainty.
METHODS: We synthesized evidence from published EHEM frameworks, applied case studies, and stakeholder-oriented analyses in the DMDD space. The focus was on how early decision-analytic models integrate sparse technical, clinical, and operational evidence to explore potential value under uncertainty. We assessed the types of outputs generated by EHEM that inform early strategic decisions, including value drivers, performance thresholds, scenario analyses, and priority levelling of evidence needs.
RESULTS: Across technology domains, early modelling consistently supported five decision-critical functions. First, EHEM clarified where value is generated within clinical and operational pathways. Second, threshold and headroom analyses identified minimum performance, uptake, or cost conditions required for viability. Third, early modelling refined product-market alignment by highlighting high-value indications, populations, and use cases. Fourth, EHEM identified the uncertainties that most strongly influence value, enabling more targeted and efficient evidence generation. Fifth, scenario-based analyses reduced commercial and investment risk by identifying development paths that were unlikely to succeed under plausible assumptions. Iterative use of EHEM could show to improve communication between manufacturers, investors, and other stakeholders by making assumptions, trade-offs, and value propositions explicit at an early stage.
CONCLUSIONS: Early health economic modelling is an effective strategic decision-support tool for diagnostics, medical devices, and digital health technologies. When applied early and iteratively, EHEM can support capital-efficient development, improve product-market alignment, and increase the likelihood for emerging technologies to advance with credible, decision-relevant value propositions. By generating transparent, decision-relevant value signals at the point where key development and investment decisions are made, EHEM directly addresses ISPOR’s 2030 priority of improving the relevance, timeliness, and usability of HEOR for real-world decision-makers.
DEVELOPMENT OF THE MEDICAL DEVICE ECONOMIC EVALUATION METHODOLOGICAL QUALITY (DEEM-Q) CHECKLIST
OBJECTIVES: Economic evaluations increasingly inform adoption and reimbursement decisions for medical devices. However, existing methodological quality assessment tools often fail to capture several features commonly associated with medical devices, such as learning curve effects, organizational impact, incremental innovation, and diversity in design and use. The objective of the medical Device Economic Evaluation Methodological Quality assessment (DEEM-Q) study was to develop a consensus-based instrument for assessing the methodological quality of economic evaluations of medical devices.
METHODS: Candidate items were identified through a systematic review of existing methodological quality assessment tools and economic evaluation guidelines, including those from Canada’s Drug Agency. A two-round modified e-Delphi study was conducted with 40 health economists experienced in Canadian medical device evaluation (response rates: 100% and 90% for Rounds 1 and 2, respectively). Using a 9-point importance scale, items were retained if ≥70% of participants rated them as critical (scores 7-9) and ≤15% rated them as not important (scores 1-3). The resulting checklist underwent pilot testing for clarity, applicability, and consistency.
RESULTS: The initial 49 items were refined to 39, covering general economic evaluation domains (decision problem, comparators, perspective, time horizon, modeling, analysis, and uncertainty) and device-specific considerations (evidence gaps, learning curve, organizational impacts, incremental innovation, and diversity). Pilot testing confirmed clarity and consistent application.
CONCLUSIONS: The DEEM-Q represents the first consensus-based checklist for assessing the methodological quality of medical device economic evaluations. It provides a practical tool for researchers, reviewers, and decision-makers. Future work will include a companion explanation and elaboration paper to support its consistent application and adaptation as methods in medical device evaluation continue to evolve.
POTENTIAL ENVIRONMENTAL AND ECONOMIC IMPLICATIONS OF ROBOTIC ASSISTED SURGERY FOR UROLOGIC ONCOLOGY
OBJECTIVES: To assess the potential environmental and associated economic implications of robotic-assisted surgery compared with open and laparoscopic approaches for prostatectomy and partial nephrectomy procedures with primary focus on medical waste generation and disposal costs, secondarily assessing carbon emissions with hospital resource utilization.
METHODS: De-identified electronic medical record data from 708 robotic-assisted surgery urologic procedures performed in 2022 were analyzed and benchmarked against a published laparoscopic and open surgery cohorts. Clinical outcomes available included length of hospital stay, 30-day readmission and blood transfusion rates. Medical waste generation and carbon emissions were modeled using published conversion figures linking inpatient outcomes to environmental impact. Economic outcomes were then estimated based on waste disposal costs. A scenario analysis estimated the minimum and maximum effect sizes at the system level for waste, disposable costs, and carbon emissions by surgical modality.
RESULTS: Relative to open and laparoscopic benchmarks, robotic-assisted surgery was associated with reduced hospital resource utilization which was translated to avoid 12-24 kilograms of medical waste per procedure with medical disposal costs ranging between $19,000 - $31,000 on an annual basis. At the health system level, this creates a meaningful annual reduction in medical waste volume and associated costs with disposing of that waste across the evaluated procedures and modalities. Reduced inpatient utilization also was associated with modeled carbon avoidance of 70-100 metric tons of carbon dioxide per year. Scenario analysis demonstrated consistent waste, cost, and carbon reductions across all modeled baseline.
CONCLUSIONS: Evaluating medical waste generation and costs throughout perioperative outcomes should be assessed in any environmental and cost assessments. These findings suggest that robotic-assisted surgery may support environmental and economic performance through reducing resource use and downstream waste generation in patient care areas like the general ward. Incorporating waste and carbon related outcomes could help inform policy decisions, economic and sustainability strategies.
BUDGET IMPACT OF ADOPTING A TRI-LAYER HYBRID SURGICAL MESH FOR VENTRAL HERNIA REPAIR: A U.S. HOSPITAL PERSPECTIVE
OBJECTIVES: Assess the economic benefits of a Tri-Layer Hybrid Surgical Mesh (HSM) vs. three alternative mesh devices including a permanent polypropylene mesh with absorbable coating ("Device A”), a reinforced hybrid biologic mesh (“Device B”), and a fully resorbable synthetic mesh (“Device C”), placed in the intraperitoneal plane for ventral-incisional hernia repair. Differences in resource use and the budget impact to an average large U.S. hospital were assessed.
METHODS: Cost-consequence and budget impact analyses were derived from patient outcomes identified for each device through a targeted literature review. The primary outcome measured was 90-day readmissions. Costs and reimbursement were sourced from publicly available fee-schedules and analysis of a large real-world database. The proportion of inpatient and outpatient cases and respective costs and reimbursement were calculated to account for differences in settings of care.
RESULTS: The 90-day readmission rate for HSM was 1.4% compared to 11.9%, 24% and 12.9% for devices A, B and C, respectively. The average 90-day cost per patient treated was lowest for HSM at $7,143 for HSM followed by device A at $9,705, device B at $13,328 and device C at $12,462. Modelling 100% adoption of HSM for a hospital performing 600 procedures annually led to an expected cost savings of $4,689 per patient treated over 90 days. Furthermore, this resulted in a projected budget impact of $2.81 Million in savings to the hospital. Sensitivity analyses showed results to be robust to reasonable changes in base input values.
CONCLUSIONS: This model shows that using the Tri-Layer Hybrid Surgical Mesh for ventral incisional hernia repair led to less resource use and substantial expected cost savings for an average US hospital compared to competitors, driven by lower readmission rates.
9:00 AM - 11:30 AM
Poster Session 5
Session Type: Research Posters
Presenters will be with their posters from 9:00AM–10:00AM
10:00 AM - 11:00 AM
From Debate to Dialogue: Building Consensus on Prior Authorization Reform
Session Type: Issue Panel
Topics: Health Policy & Regulatory, Health Service Delivery & Process of Care
Track: Access and Drug Pricing
Level: Introductory
ISSUE: Prior authorization (PA) requires a care provider to obtain a health plan’s approval for a treatment or service before the plan will provide coverage. PA has become a prevalent component of healthcare benefit design, used to contain costs and manage prescription drug use. However, as PA has expanded, it has become a source of frustration across healthcare stakeholders. Policy reform activity has recently accelerated, but may be missing the mark.
Payers acknowledge PA limitations but say it is an essential tool for ensuring clinically appropriate care and maintaining affordability. Patients report delays and disruptions in access, while clinicians experience administrative burden in navigating complex rules and appeals processes. Researchers have analyzed the implementation and impact of PA, including instances where restrictions are inconsistent with clinical guidelines.
As PA reform activity intensifies, there is ongoing debate over how it should be scoped and executed. Payers seek to preserve mechanisms that promote appropriate care and contain costs, while patients and clinicians underscore the access barriers and harms created by current practices. Researchers seek to provide evidence to inform the discussions.
This session will frame the current debate by examining trends in PA implementation over time and its impact on healthcare delivery and patient care from multiple stakeholder perspectives. It will highlight PA technology opportunities, ongoing reform efforts and aim to identify areas of common ground among stakeholders to support the development of more transparent and standardized approaches.
OVERVIEW:
Westrich will review the evolution of UM/PA and recent policy reform efforts (10 min)
Chambers, Tsiao, and Hyde will share their perspectives on the application of PA in benefit design and patient care and how it can be improved (10 min each; see panelist perspective section for details).
Moderated Q&A will explore common ground for meaningful reform and address audience questions (20 mins).
Moderator
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Kimberly Westrich, MA
National Pharmaceutical Council, Herndon, VA, United States
Kimberly Westrich, MA, is the Chief Strategy Officer of the National Pharmaceutical Council (NPC), which sponsors and conducts research on health policy issues related to the development and use of innovative biopharmaceuticals to improve the health of patients. NPC’s research contributes to the body of evidence that supports discussions and decisions about patient access to treatments, appropriate use, and the value innovative treatments provide to both patients and the healthcare system.
Ms. Westrich provides strategic guidance to NPC’s policy research and communications activities. She leads several research initiatives across NPC’s portfolio, including employer-sponsored insurance. She has published extensively on issues related to value assessment frameworks, patient-centered formulary and benefit design, value-based contracts, quality performance measurement, and accountable care organizations. Additionally, Ms. Westrich leads NPC’s workplace culture initiative — most notably demonstrated by our company's recognition as a Certified Great Place To Work®.
Ms. Westrich began her NPC career in 2000. She has also served as Director of Research at the Pharmaceutical Research and Manufacturers of America (PhRMA), worked as a healthcare consultant at The Lewin Group and Xcenda, and as a health economics and outcomes researcher at Johnson & Johnson.
Ms. Westrich is a certified yoga teacher and life coach with a passion for helping others learn and thrive. She received her master’s degree in economics from Northwestern University and her undergraduate degree in economics and mathematics from the College of William and Mary.
Speakers
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John Watkins, MPH, PharmD
University of Washington, Bothell, WA, United States
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James Chambers, MSc, PhD
Tufts Medical Center, Boston, MA, United States
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Anna Hyde, MA
Arthritis Foundation, Silver Spring, MD, United States
Beyond Black Boxes: Case Studies of Transparent, Validated LLM Workflows for Accelerating Global HTA Submissions and Decisions
Session Type: Spotlight
Topics: Health Technology Assessment, Methodological & Statistical Research, Real World Data & Information Systems
Track: AI
Level: Intermediate
Validation of AI/ML, LLM-enabled automation and model outputs cannot be one-size-fits-all; instead, it must be tailored to each application's evidentiary role and downstream decision-making impact. For clinical data extraction, automation workflows, and health economic model parameterization, this requires transparent, auditable frameworks with clearly defined gold standards, robust sampling strategies, and quality assurance pipelines. For higher-order applications like network meta-analyses and physician insight synthesis, validation must address both the accuracy of extracted source data and the reliability of model-synthesized conclusions. Key issues include managing heterogeneity in model behavior across settings, ensuring privacy and clinical oversight at scale, and communicating uncertainty introduced by model choices. While scientific consensus on a validation framework may not have been achieved yet, we can review case studies of recent frameworks applied in practice. Strengthening these validation practices will be essential to unlock the efficiency gains of LLM-enabled evidence generation while maintaining scientific rigor and enabling equitable, evidence-based decision-making globally. Dr. Devine opens the session, providing an overview and setting the context (8 minutes). Dr. Adamson introduces the application of LLMs for extraction of unstructured EHR data and physician insights and the VALID framework for assessing accuracy and reliability for decision making, providing a case study in disease progression dates in multiple countries. Mr. Reason demonstrates how validated LLM-generated data can be integrated into AI workflows for network meta-analysis, highlighting implications for transparency, reproducibility and HTA use. Finally, Mr. Malcolm outlines how AI-enabled automation has reduced HTA submission burden, particularly in LMIC contexts, and how automated evidence assembly can therefore accelerate submissions while maintaining data quality standards (12 minutes). Dr. Devine will facilitate an engaging discussion with the audience involving audience participation (15 min).
Moderator
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Beth Devine, PhD, PharmD, MBA, MSc
University of Washington, Seattle, WA, United States
Speakers
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Blythe Adamson, MPH, PhD
Flatiron Health, New York, NY, United States
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Bill Malcolm, MSc
Bristol Myers Squibb, Middlesex, United Kingdom
Bill Malcolm Leads the Economic & Predictive Modeling Team for Global HEOR at BMS. He has over 20 years of experience across a broad range of therapeutic areas and has published extensively in the field of HEOR. His current focus is transforming HEOR workflows using Generative AI methods and he has published several key papers on this innovative topic area. Bill is a member of the ISPOR AI Working Group.
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Tim Reason, MSc
Estima Scientific, South Ruislip, United Kingdom
Tim Reason is co-founder of Estima Scientific and specializes in AI and evidence synthesis, having spent 15 years in the field of HEOR and technology. Tim is managing director of Estima, driving business activities, innovation and strategy for the company. Tim’s specializes in the intersection of HEOR, software development and AI to drive better outcomes for patients. Tim is the lead author on 2 seminal papers in AI for HEOR, showing that AI can be used to automate health economic modelling and NMA.
Changing Policies in the United States and the Return of Pediatric Vaccine Preventable Diseases
Session Type: Issue Panel
Topics: Epidemiology & Public Health, Health Policy & Regulatory, Economic Evaluation
Track: Expanded Value Measures
Level: Intermediate
Issue: Despite the safety and effectiveness of childhood vaccines, vaccine uptake is under threat due to hesitancy, acceptance, and politics. With the recent changes in personnel on the Advisory Committee on Immunization Practices (ACIP) and their active discussions about changing the recommended pediatric dosing schedule, along with ongoing outbreaks of pertussis and measles, the United States is at a crossroads. In fact, measles ‘elimination status’ is at risk or has been lost in all North American countries, so preparing for and managing endemic circulation of these pathogens is vital. Historically, mathematical modeling of infectious diseases has been a vital tool in predicting and controlling the spread of these pathogens. Effective communication strategies of these modeling efforts to inform policy makers and medical professionals is critical.
Overview: Managing ongoing outbreaks of vaccine preventable disease (VPDs) and communicating strategies to mitigate their effects will be of utmost importance. Healthcare has changed since these pathogens last circulated endemically in North America and strategies for control and elimination have changed in the interim. Since it has been decades since these VPDs were endemic in North America, most scientists here are inexperienced with understanding and managing ongoing VPD outbreaks. To address this potential gap in guidance, scientific input from researchers who are experienced in elimination efforts in countries where these pathogens have remained endemic in tandem with disease modeling may help in informing policy decisions and communicating these results to stakeholders.
Moderator
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Ruthie Birger, MS, PhD
Merck Inc. and Co., Rahway, NJ, United States
Speakers
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Kevin Bakker
Merck & Co., Inc. - North Wales, PA, North Wales, PA, United States
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Matt Ferrari, MS, PhD
Pennsylvania State University, State College, PA, United States
Amplifying Patient Voice: AI-Driven Narrative Analysis in Clinical Trials
Session Type: Issue Panel
Topics: Patient-Centered Research, Methodological & Statistical Research, Clinical Outcomes
Track: AI
Level: Advanced
ISSUE: Traditional Patient-Reported Outcome (PRO) instruments often miss the nuance of lived patient experience. Free-text entries and direct patient voice offer richer insights but have been underused due to analytical complexity and scalability challenges. Advances in AI—particularly large language models (LLMs) and conversational AI—now enable scalable capture, interpretation, and communication of patient narratives. Conversational agents provide interactive dialogue that elicits deeper context, reduces missingness, and generates structured summaries for clinicians, regulators, and decision-makers. This panel will examine how AI amplifies patient voice across development phases, improves interpretability for diverse stakeholders, and addresses risks such as bias, hallucination control, transparency, and regulatory validation.
OVERVIEW: AI-enabled free-text analysis and direct patient voice complement structured PRO data, enabling scalable extraction of symptom narratives, patient priorities, and quality-of-life context that traditional instruments may miss. Practical frameworks for operationalization, validation, and regulatory acceptance of LLM-assisted analysis are essential for integrating narrative responses within eCOA platforms.
This session offers an integrated view from real-world use, methodological standards, and future applications. Talk 1: Case study of LLM-based extraction and coding of an open-ended patient preference measure, covering workflow, timelines, quality checks, and integration into evidence packages. Talk 2: Methodological rigor—model performance metrics, bias detection, construct validity, version control, human review, and reproducibility—using oncology symptom capture examples. Talk 3: Conversational AI for dynamic engagement, reduced missingness, and richer lived-experience capture, alongside safety, hallucination control, and privacy considerations.
Each talk runs 12 minutes, followed by 20 minutes of audience interaction. Attendees will gain actionable frameworks, validated benchmarks, and practical guidance to responsibly integrate AI-driven narrative analysis in PRO/eCOA research.
Moderator
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Denise Globe, PhD
Gilead Sciences, Foster City, CA, United States
Denise Globe PhD is currently the Head of the GHEOR and the Global Value and Access Center of Excellence at Gilead. She has 30 years of experience in health care with a focus on quantitative policy research and direct research experiences in health economics research including the outcomes, process, financing and delivery of care. She leads a team at Gilead that is accountable for global observational research, evidence for access strategy and execution for the oncology, virology, liver and inflammation portfolios to maximize reimbursement and access across the life cycle.
Speakers
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SAEID SHAHRAZ
Gilead Sciences, Mountain View, CA, United States
Saeid Shahraz, MD, PhD, is a physician and measurement scientist with over 20 years of experience in health outcomes research. He leads clinical outcome assessment strategy and analytics as Director of Health Economics and Outcomes Research. With expertise in psychometrics, COA validation, and real-world data analysis, Dr. Shahraz supports evidence generation for clinical trials and regulatory submissions. His work bridges scientific rigor and patient-centered measurement to enhance the value and reliability of health outcomes data.
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Yuelin Li, PhD
Memorial Sloan Kettering Cancer Center, New York, NY, United States
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Bill Byrom, PhD
Signant Health, Nottingham, United Kingdom
Is It Worth Building Disease-Specific Patient Reported Outcomes (DSPRO) Value Propositions for Orphan and Innovative Therapies? Bridging Economic Models and Patient Lived Experience
Session Type: Other Breakout Session
Topics: Patient-Centered Research, Clinical Outcomes, Health Technology Assessment
Track: Expanded Value Measures
Level: Intermediate
Purpose: This breakout session will create a shared space for both US and global patients, caregivers, payers, regulators, clinicians, and industry perspectives to openly discuss when does investing in DSPROs Value Propositions actually change conversations, decisions, and experiences and when does it mostly add complexity and cost?
By the end of the session, participants will be able to:
• Compare the pros and cons of DSPROs vs generic measures for valuing orphan/innovative therapies.
• Discuss ROI for companies and “return on burden/benefit” for patients and families.
• Pinpoint when DSPROs are truly “must-have” versus “nice-to-have” in real-world decisions.
Description: This session will begin with a brief framing presentation (10 minutes) to outline how orphan and innovative therapies are currently evaluated, highlight where generic measures seem to miss what matters most to patients and caregivers when developing a value proposition.
Next, three brief talks (~10 minutes each) will examine DSPROs from different perspectives:
• Steve brings 15+ years of experience in industry HEOR perspective currently representing Ionis Pharmaceutical talks on when DSPROs strengthen (or fail to strengthen) value and “return on investment”
• Angie brings 30+ years of experience as global lead for patient-led musculoskeletal health advocacy patient advocacy and EUPATI Fellow, she talks about how DSPROs can amplify or miss lived experience, including “return on burden”
• Nora brings 10+ years of conducting and disseminating research on child health outcomes at Queens University and gives an academic perspective on how DSPROs show up in real-world decision making, including what level of outcome evidence feels meaningful versus excessive in practice.
The session will conclude with a moderated, interactive discussion and live polling (20 minutes), using case scenarios and a simple discussion guide to help attendees explore when investing in DSPROs adds meaningful value for stakeholders and when existing approaches may be sufficient in both US and global settings.
Moderator
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Nathan T Jibat, MBA, MPH, MD
Johns Hopkins University, Baltimore, MD, United States
Speakers
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Steven Kymes, MHA, PhD
Ionis Pharmaceuticals, Carlsbad, CA, United States
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Nora Fayed, PhD
Queen's University, Kingston, ON, Canada
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Angie Botto-van Bemden, PhD
Musculoskeletal Research International, Holiday, FL, United States
Access: Pricing, Policy, and Market Dynamics
Session Type: Research Podiums
This session examines pharmaceutical pricing trends, international benchmarking strategies, and the impact of recent U.S. Medicare reforms on drug costs. Featured studies provide timely insights into pricing dynamics across care settings, payer systems, and international markets, offering evidence to inform policy decisions on drug affordability and reimbursement reform.
Moderator
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Soumana Nasser, PharmD
Lebanese American University, Byblos, Lebanon
SETTING EVIDENCE STANDARDS BEFORE SETTING INTERNATIONAL PRICE BENCHMARKS: INSIGHTS FROM EX-U.S. G7 HEALTH TECHNOLOGY ASSESSMENTS ON TOP-SPENDING U.S. MEDICARE PART B BIOLOGICS
OBJECTIVES: Ex-U.S. drug prices are increasingly cited as value-based benchmarks in U.S. pricing policy, yet the evidentiary standards supporting those prices remain unexamined. The objective is to assess the rigor of comparative effectiveness research (CER) and the use of patient-reported outcomes (PROs) in ex-U.S. health technology assessments (HTA) for top-spending U.S. Medicare Part B biologics.
METHODS: Using the Medicare Part B Drug Spending Dashboard (2023), the top-spending biologics—aflibercept, denosumab, daratumumab, nivolumab, and pembrolizumab—were identified. For each, two FDA-approved indications with the largest U.S. market share were selected. HTA reports from ex-U.S. G7 countries (Canada, France, Germany, Italy, Japan, UK) were retrieved from NAVLIN. Reports were assessed using a framework capturing CER presence and type, design validity, comparator appropriateness, evidence quality, transparency, study outcomes, economic assessments, and HTA and reimbursement decisions. A CER-rigor score categorized reports as Low (0-3), Moderate (4), or High (5-6).
RESULTS: Among 47 reports, CER was used in 80.9%, with 55.3% relying on direct evidence. CER use and rigor varied across agencies. Indirect comparisons appeared in 11 reports, but only one was considered valid by the HTA. Comparator appropriateness (59.6%), CER design quality (55.3%), and transparency (57.4%) were present in roughly half of reports. Overall, 51.1% had Low, 4.3% Moderate, and 44.7% had High CER rigor. Favorable HTA/reimbursement decisions were more common in high-rigor reports. Only 19 (40.4%) reports, mainly from the UK and Canada, incorporated PROs into their final decision rationale. Economic assessments included cost-utility (55.3%) and budget-impact analyses (48.9%).
CONCLUSIONS: Inconsistent CER rigor and sparse PRO use across ex-U.S. G7 countries show the risk of referencing foreign prices without scrutinizing evidence. U.S. pricing policy must depend on benchmarks supported by strong CER and patient-centered outcomes. The framework and CER-rigor score provide a proof-of-concept foundation that future work can refine to assess evidence robustness for U.S. pricing decisions.
INTERNATIONAL AVAILABILITY AND PRICE OF ULTRA-EXPENSIVE DRUGS IN MEDICARE PART D: ASSESSING THE FEASIBILITY OF EXTERNAL REFERENCE PRICING
OBJECTIVES: The increasing prevalence of high-cost specialty drugs poses key concerns for policymakers and patients. Particularly, ultra-expensive drugs (UEDs) compose a growing share of Medicare Part D spending, prompting interest in external reference pricing. However, limited evidence on their international availability and pricing constrains feasibility assessments. This study characterizes UEDs in Medicare Part D and examines their availability and relative prices across industrialized countries.
METHODS: We conducted a retrospective cohort analysis of UEDs, defined as therapies with annual per-beneficiary spending above U.S. per-capita GDP. Data sources included Medicare Part D Drug Spending (2019-2023) and OECD countries’ wholesaler acquisition prices (November 2025) through Eversana® Navlin’s pricing database. We characterized UEDs by spending, years since launch, therapeutic area, orphan designation, and modality. Outcomes were international availability across 36 OECD nations and U.S.-to-foreign price ratios. Subgroup analyses examined 22 OECD countries with GDP per capita ≥60% of the U.S. Logistic regression assessed associations between drug characteristics and availability.
RESULTS: UEDs in Medicare Part D increased from 123 to 189 between 2019-2023, with spending rising from $28.9B to $45.5B (35.4% of Part D spending). Of 2023 UEDs, 31.9% were biologics, 77.8% had orphan indications, and 31.3% were antineoplastic therapies. Across OECD countries, availability ranged from 9 to 125 UEDs (median 102). Internationally available UEDs were more likely antineoplastic (44.3%), small-molecule (65.1%), orphan-indicated (74.9%), and had higher per-beneficiary spending (p<0.001). Biologics were associated with increased availability (OR 1.3, p=0.03). The median U.S.-to-foreign price ratio was 3.62 (IQR 2.10-5.96).
CONCLUSIONS: Despite rapid expansion of UEDs in Medicare Part D, international availability in comparable economies remains limited, concentrated in small-molecule antineoplastic agents with orphan indications, with US prices 3.6-fold higher than reference countries. The absence of international price benchmarks limits feasibility of external reference pricing and indicates policy challenges for drugs reliant on the U.S. market.
GROWTH IN PRIVATE-PAYER MARKUPS FOR INFUSED CHEMOTHERAPY RELATIVE TO MEDICARE AVERAGE SALES PRICE BY SITE OF CARE, 2015-2023
OBJECTIVES: Medicare reimburses most infused chemotherapy based on a standardized Average Sales Price (ASP), which serves as a transparent benchmark tied to drug acquisition costs. In contrast, private insurers negotiate prices that may deviate substantially from ASP, with growing concern that site-of-care payment differentials amplify spending growth. This study evaluates trends in private-payer reimbursement markups relative to Medicare ASP for infused chemotherapy from 2015-2023, comparing physician office and hospital outpatient department (HOPD) settings.
METHODS: We used de-identified data from MarketScan Commercial Claims to identify privately insured patients who received physician-administered infused chemotherapy between 2015 and 2023. For each claim, we calculated the ratio of total reimbursed amount to Medicare ASP, derived by multiplying publicly reported ASPs by units administered. Site of care was classified as physician office or HOPD. We estimated annual mean reimbursement-to-ASP ratios by site of care. Linear regression models adjusted for year, site of care, and a year-by-site interaction assessed differential growth in markups over time.
RESULTS: Private-payer reimbursement relative to Medicare ASP increased steadily over the study period in both settings, but growth was substantially larger in HOPDs. Mean reimbursement-to-ASP ratios in HOPDs increased from approximately 1.5 in 2015 to more than 2.2 by 2023, while ratios in physician offices increased from near parity with ASP to approximately 1.4. In adjusted models, the interaction between year and physician office setting was statistically significant (−0.06; p<0.05), indicating that markups grew more slowly in physician offices than in HOPDs.
CONCLUSIONS: Private-payer prices for infused chemotherapy are increasingly decoupled from Medicare ASP benchmarks, particularly in hospital outpatient settings. These findings suggest that site-of-care payment differentials contribute not only to higher overall spending but also to faster growth in margins over acquisition-based reference prices. Ongoing policy efforts focused on site-neutral payment and price transparency may have important implications for moderating private-payer chemotherapy spending growth.
PROJECTED MEDICARE DRUG PRICE NEGOTIATION SAVINGS IN 2027
OBJECTIVES: The Medicare Drug Price Negotiation Program (MDPNP) was introduced to reduce Medicare drug spending. In the first and second rounds, MDPNP negotiated prices for 10 and 15 high-cost, single-source Part D drugs, with negotiated prices taking effect in 2026 and 2027. Using historical spending data, CMS estimated savings of $6 and $12 billion for the first-round and second-round of negotiation, respectively. This study projects actual 2027 Medicare drug spending for the selected drugs.
METHODS: Of the 25 selected drugs, three first-round drugs were deselected by statute for 2027 following generic or biosimilar entry. For the remaining 22 drugs, we estimated 2027 Medicare drug spending by using net prices under a no-negotiation scenario and negotiated Maximum Fair Prices (MFPs) under the MDPNP, each applied to projected drug volumes. Volumes were projected by extrapolating 2022-2024 IQVIA NSP unit data to 2027 and calibrating them to the most recent Medicare Part D utilization data. Net prices were extrapolated from 2021-2022 benchmarks. Spending estimates also accounted for expected generic or biosimilar entry.
RESULTS: Projected 2027 Medicare spending for the 22 drugs was $55.9 billion without negotiation and $44.3 billion with negotiation, representing an estimated $11.6 billion reduction (20.7%). Of this reduction, $1.8 billion was attributable to the first-round drugs in their second year of negotiated pricing and $9.8 billion to the second-round drugs in their first year, which was below CMS’s $12 billion estimate. While drugs with high pre-negotiation rebates showed large reductions overall, a greater relative reduction was observed for older drugs with low pre-negotiation rebates, such as Xifaxan.
CONCLUSIONS: The MDPNP will effectively reduce Medicare drug spending by $11.6 billion in 2027. Savings varied by drug characteristics, with relative reductions for older low-rebate drugs and absolute savings for high-spending drugs.
Beyond Commercially Available Real-World Data: Harnessing Public Data for HEOR Research in the US and Globally
Session Type: Workshop
Topics: Real World Data & Information Systems, Study Approaches, Economic Evaluation
Track: Real-World Evidence (RWE)
Level: Introductory
Purpose: Commercial datasets are widely used in health economics and outcomes research studies (HEOR); however, public data sources offer advantages in transparency, accessibility, and population representativeness. This session will highlight the value of public data for HEOR research, focusing on access mechanisms, data coverage, and depth of available information, and how these resources can complement or substitute for proprietary datasets.
Description: This session will begin with an overview of major public data sources globally (10 minutes), including sources from the United States (e.g., Medical Expenditure Panel Survey [MEPS]), Europe (e.g., Clinical Practice Research Datalink [CPRD]), Asia (e.g., Taiwan’s National Health Insurance Research Database [NHIRD]), and South America (e.g., DADASUS). The presentation will address database selection including trade-offs between commercial and public data and will consider timeliness, access requirements, cost, representativeness, depth of information, and linkage potential.
Next, workshop facilitators will present three real-world case studies (10 minutes each) that illustrate how public data can be applied to answer HEOR research questions. Lia Pizzicato will present a U.S. example using MEPS on obesity; Cameron Cook will describe a study on cardiovascular disease using CPRD in the United Kingdom; and Fang-Ju Lin will outline a use case in oncology leveraging Taiwan’s NHIRD, cancer registry, and mortality data. Each case study will highlight practical considerations, strengths, and limitations encountered when working with public datasets.
The session will conclude with an interactive component (20 minutes), beginning with a 10-minute facilitated discussion on the strengths and limitations of public data sources. In the final 10 minutes, facilitators will pose hypothetical HEOR research questions (e.g., burden of illness, treatment pattern evaluation, outcome comparisons), inviting the audience to propose suitable data sources. Through this discussion, participants will apply key concepts from the workshop and practice selecting datasets that are fit for purpose across various research scenarios.
Moderator
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C. Daniel Mullins, PhD
University of Maryland School of Medicine, Baltimore, MD, United States
C. Daniel Mullins is a Professor at the University of Maryland School of Pharmacy. He is Founder and Executive Director of the University of Maryland PATient-centered Involvement in Evaluating effectiveNess of TreatmentS (PATIENTS) Program, a community-academic partnership for patient-driven research. Dr. Mullins has received approximately $25 million in funding as a Principal Investigator from AHRQ, FDA, NCI, NHLBI, NIA, NIMHD, the Patient-Centered Outcomes Research Institute (PCORI) and various patient advocacy organizations and pharmaceutical companies. At the University of Maryland Baltimore (UMB), he received the Dr. Patricia Sokolove Outstanding Mentor Award and the Dr. Martin Luther King Jr. Faculty Diversity Award. He was named Researcher of the Year at UMB and was awarded a University System of Maryland Wilson H. Elkins Professorship. At ISPOR, he has served as Editor-in-Chief of Value in Health since 2010 and received the Marilyn Dix Smith Leadership Award in 2017 and the Avedis Donabedian Lifetime Achievement Award in 2024.
Speakers
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Cameron C Cook, BA, MA, MS, PhD
AMGEN, Durham, NC, United States
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Fang-Ju (Irene) Lin, RPh, PhD
National Taiwan University, Taipei City, Taiwan
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Lia N Pizzicato, MPH
IQVIA, Rochester, NY, United States
From Engagement to Influence: What Should Patient-Centered Economic Models Actually Look Like?
Session Type: Issue Panel
Topics: Economic Evaluation, Patient-Centered Research, Health Technology Assessment
Track: Expanded Value Measures
Level: Intermediate
Patient engagement in value assessment has advanced considerably, yet its integration into economic modeling remains the exception rather than the rule. Most economic models continue to rely on clinician-driven assumptions, generic utility instruments, and representations of disease that may not fully reflect patients’ lived experiences and priorities. While emerging examples demonstrate that engagement can shape model structure, outcome selection, and interpretation, the field lacks agreement on what meaningful patient-centered modeling should look like and whether this evolution strengthens or challenges methodological rigor.
This panel will debate the central issue: Should lived experience play a greater role in shaping the analytical components of economic models, or remain primarily advisory? If involvement is to extend beyond reviewing lay summaries, key questions arise: How should patient-identified outcomes be incorporated when they fall outside traditional cost-per-QALY frameworks? When does lived experience justify revisiting structural assumptions? How might patient-informed perspectives influence cost-effectiveness results, equity considerations, and uncertainty analysis? And what safeguards are needed to prevent bias, double-counting, or unintended scope expansion?
Building on recent research and global practice, panelists will explore both opportunities and tensions: ensuring methodological rigor while improving relevance, enhancing legitimacy without compromising internal validity, and identifying scalable approaches to embed patient insights across the modeling lifecycle.
Ultimately, this panel asks: if future economic models are co-created with patients, how should this be operationalized in practice? What principles, safeguards, and governance structures are required to integrate patient-generated inputs while maintaining transparency, rigor, and fairness?
Moderator
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Elisabeth Oehrlein, MS, PhD
Applied Patient Experience, LLC, Washington, DC, United States
Speakers
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Ramiro E Gilardino, MSc, MD
R-Impact, Dubendorf, Switzerland
Impact-driven healthcare executive with 15+ years of leadership in Global Market Access, Health Policy, and HEOR. Successfully led strategies that improved patient access, drove reimbursement success, and shaped health policy in pharma, biotech, and global organizations. Expert in advancing HTA frameworks and forging stakeholder partnerships to promote health equity and deliver value-based healthcare solutions globally.
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Marina Richardson
ICER, Boston, MA, United States
Marina Richardson is an associate director, Health Technology Methods and Health Economics with the Institute for Clinical and Economic Review (ICER). In her role, Marina leads and oversees the development of economic models to inform pricing and reimbursement decision-making and identifies and executes opportunities to enhance ICER's methodology and processes within Health Technology Assessment (HTA) and Health Economics. Prior to joining ICER, Marina led and contributed to reimbursement review reports and recommendations at Canada's Drug Agency (CDA-AMC), formerly CADTH. Marina has a PhD in Health Services Research from the University of Toronto and is an active contributor to the field including as a deputy editor for the International Journal of Technology Assessment in Health Care (IJTAHC), a member of the Ontario Immunization Advisory Committee (OIAC) in Ontario, Canada, and as a co-chair of the International Scientific Program Committee for Health Technology Assessment International (HTAi) 2025.
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Eric W Low
Eric Low Consulting, Haddington, United Kingdom
Eric has worked in medical research, health technology appraisal, market access, health policy and patient organisations for over 30 years.
He established Myeloma UK in 1996, developing it from an idea to a successful and respected organisation he led as Chief Executive until 2017. During this time, he designed and implemented a disease blueprint and bench-to-bedside strategic model to accelerate and prioritise the discovery, development of and access to effective new treatments, best practices, as well as information and support for patients and their families
In 2017, Eric established a small specialist consultancy specialising primarily in strategic HTA and market access, life sciences and healthcare policy, and patient and patient group engagement.
Eric is committed and focused on improving patient outcomes. He has a strong track record of delivery and success in building multi-stakeholder research collaborations, patient coalitions, market access strategies, changing policy, and delivering innovative solutions to complex issues, challenges and barriers in progress.
Eric also holds several Board, honorary, advisory and voluntary positions. He also advises numerous medical and health-focused charities on a pro bono basis. He was awarded an OBE for services to charity in the Queen’s Birthday Honours 2012.
Strategic Integration of Generative AI in Health Economic Modeling: Emerging Methods, Implementation, Evaluation, and HTA Implications
Session Type: Workshop
Topics: Methodological & Statistical Research, Economic Evaluation, Health Technology Assessment
Track: AI
Level: Intermediate
PURPOSE:
Advances in genAI are reshaping health economic analysis workflows, spanning academic methodological research through HTA submissions. As we increasingly engage with genAI-assisted modeling, clearer methodological guidance, performance evaluation standards, and implementation frameworks are needed. This workshop will present cross-stakeholder perspectives on: (1) recent genAI advancements and proposed frameworks for integrating agentic intelligence into economic modeling; (2) operational and methodological barriers to using genAI in industry and academic modeling workflows and the need for performance-based evaluation criteria; and (3) how HTA bodies may assess performance, transparency, and verification of genAI-assisted models.
DESCRIPTION:
Dr. Wang will contextualize recent advancements in genAI within HEOR and present her collaborative research on an implementation framework for integrating agentic intelligence into economic modeling (15 min).
Mr. Feng will present the industry user’s perspective on integrating genAI into internal workflows, including how genAI-assisted health economic models should be evaluated on their performance rather than on their ability to replicate human-built models. He will discuss key barriers that limit modelers’ adoption of genAI tools in practice and will call for an initiative to establish a formal evaluation framework for genAI-assisted economic modeling (10 min).
Dr. Wright will discuss the HTA perspective, highlighting stages where genAI-assisted approaches are likely to be most useful in evidence synthesis and modeling. She will also address the importance of transparency and validation in these approaches (10 min).
Dr. Li will synthesize the discussion and present the academic user’s perspective, including practical concerns about the cost and access of specialized genAI tools, and methodological considerations related to ensuring comprehensive literature capture, transparent workflows, and reproducible modeling results. (10 min).
Audience engagement will include polling questions and Q&A (15 min).
Moderator
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Meng Li, MS, PhD
Tufts Medical Center; Stifel, Boston, MA, United States
Speakers
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Xiaoyan Wang, PhD
Tulane University, New Orleans, LA, United States
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Haidong Feng, MPH, MS
Merck, Boston, MA, United States
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Abigail Wright
Institute for Clinical and Economic Review, Boston, MA, United States
Oncology: Advancing Patient Centered Research
Session Type: Research Podiums
In oncology, where treatments often involve substantial benefits alongside significant burden and trade-offs, strengthening the role of the patient voice across clinical trials and routine care settings is particularly critical. This session includes studies on meaningful within-patient change in EORTC QLQ-C30 physical functioning scores in breast cancer (presentation #1), agreement between patient-reported and claims data in chronic pain (presentation #2), patient engagement in routine PRO completion in radiation oncology (presentation #3), and treatment preferences of patients with bladder cancer (presentation #4).
Moderator
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Tamas Agh, MSc, PhD, MD
Center for HTA and Pharmacoeconomic Research, University of Pecs & Syreon Research Institute, Budapest, Hungary
DERIVATION OF MEANINGFUL WITHIN-PATIENT CHANGE (MWPC) THRESHOLDS OF THE EUROPEAN ORGANISATION FOR RESEARCH AND TREATMENT OF CANCER QUALITY OF LIFE QUESTIONNAIRE C30 (EORTC QLQ-C30) PHYSICAL FUNCTIONING (PF) SCORES FROM THE ASCENT-03 TRIAL
OBJECTIVES: The EORTC QLQ-C30 PF subscale is a 5-item measure assessing a patient’s ability to perform daily physical activities, a key indicator of treatment impact on quality of life. We aimed to determine MWPC thresholds for EORTC QLQ-C30 PF scores in the first-line metastatic triple-negative breast cancer (mTNBC) population based on the randomized phase 3 ASCENT-03 trial, which included EORTC QLQ-C30 PF score at week 25 as a predefined key secondary endpoint.
METHODS: Analyses were conducted on the intent-to-treat population with baseline and ≥1 post-baseline PF assessment (through week 25; N=436). Participants completed EORTC QLQ-C30 at day 1 of each treatment cycle. Using pooled data from both treatment arms, anchor-based methods (ABMs; key anchors: Patient Global Impression of Severity [PGIS], Patient Global Impression of Change [PGIC]; supportive anchors: EORTC QLQ-C30 Items 29 and 30) were supplemented by distribution-based methods (DBMs). Spearman correlations (≥0.30) were used to confirm anchor validity. DBMs estimated MWPC using one-half standard deviation (1/2 SD) and standard error of measurement (SEM), calculated using test-retest reliability intra-class correlation coefficients (ICCs) from psychometrically and clinically stable PGIS and PGIC responses.
RESULTS: Of 436 participants, 293 had an assessment at week 25. Test-retest reliability ICC values were 0.87 based on PGIS response and 0.89 based on PGIC response. Correlations between PF changes through week 25 and anchors supported anchor adequacy (range: 0.39-0.50). Baseline DBM estimates for transformed PF scores were 9.76 (1/2 SD) and 7.00 (SEM). ABMs determined that between baseline and week 25, meaningful improvement was approximately +13.33 points, and worsening was -13.33 to -20.00 points, above the absolute value of ABM measures, corresponding to raw scores ≈0.4-0.6.
CONCLUSIONS: This analysis established MWPC thresholds of ±13.33 points in the first-line mTNBC population. This threshold will inform time-to-deterioration analyses and interpretation of PF outcomes in future clinical trials for this population.
BARRIERS AND FACILITATORS TO PATIENT ENGAGEMENT WITH PATIENT-REPORTED OUTCOME MEASURE COMPLETION IN ROUTINE RADIATION ONCOLOGY CARE
OBJECTIVES: Patient-reported outcome (PRO) measures (PROMs) are powerful tools for enhancing clinician and patient communication, identifying problematic symptoms, prioritizing treatment needs, and improving the quality of care. However, PRO data can exist only when patients participate, and nonresponse emerges as a significant challenge. Patient engagement is therefore essential for successful PROM collection. In this study, we conducted in-depth interviews with adult cancer patients to explore barriers and facilitators to engagement in PROM completion during routine care in radiation oncology clinics within the Mass General Brigham (MGB) health system.
METHODS: This qualitative interview study included adult cancer patients receiving care at five radiation oncology clinics within the MGB health system between September and November 2025. We purposively recruited patients through electronic health record (EHR) portals. Demographic characteristics and clinical information were collected from the EHR and pre-interview surveys, as needed. We conducted one-on-one in-depth interviews to understand (1) patients’ experiences with PROM completion, (2) the primary challenges influencing their decisions to complete PROMs, and (3) patient-recommended solutions to address these challenges. Sample size was determined based on information saturation.
RESULTS: A total of 19 one-on-one in-depth interviews were conducted, reaching information saturation. Among participants, half were female, approximately 42% were older than 60 years, and about 32% identified as non-White. We identified two key barriers and three facilitators to PROM completion. The barriers included a lack of actionable feedback following PROM completion and long recall periods of PROMs. Facilitators included clinicians discussing PRO scores with patients during appointments, timely responses from care teams, and patients’ perceived benefits of completing PROMs.
CONCLUSIONS: Timely, actionable feedback on PRO scores and responsive clinical follow-up are important factors associated with patient engagement in PROM completion.
PATIENT PREFERENCES FOR THE TREATMENT OF BCG-UNRESPONSIVE NON-MUSCLE-INVASIVE BLADDER CANCER (NMIBC): FINDINGS FROM A UNITED KINGDOM (UK) QUESTIONNAIRE
OBJECTIVES: In the United Kingdom (UK), adults with Bacillus Calmette-Guérin (BCG)‑unresponsive high-risk non‑muscle‑invasive bladder cancer (NMIBC) are offered radical cystectomy (RC) or various bladder‑sparing therapies (BSTs). Limited contemporary evidence exists on how patients weigh these options. This study aimed to (1) assess preferences for BSTs versus RC after BCG, and (2) identify factors influencing patient decision‑making.
METHODS: An online questionnaire was distributed via the patient‑advocacy group Fight Bladder Cancer to UK NMIBC patients who were currently receiving or had previously received BCG. The survey collected demographics, treatment priorities, and preferences using multiple‑choice and free‑text items. Descriptive statistics summarize responses; subgroup analyses explore differences by age, gender, and treatment status.
RESULTS: Eighty‑six patients completed the questionnaire (30% currently on BCG, 70% post‑BCG). The cohort was 54% female, despite lower bladder cancer prevalence. BCG discontinuation occurred because of planned completion (42%), disease progression/recurrence (33%), toxicity (22%), and supply shortages (3%). After BCG, 17% received intravesical hyperthermic mitomycin C (hMMC) and 32% underwent RC (including four who had hMMC). Nearly half of the respondents stated they would choose RC after BCG; however, 27% of patients preferred BST. Preference for BST was highest among participants still receiving BCG, whereas those who had already undergone RC showed a stronger preference towards repeating their decision to have RC. Older participants were less likely to favor RC. Clinical effectiveness - impact on disease recurrence, progression, and life expectancy - was rated “extremely important” by most respondents. Procedural considerations and daily‑life impact varied, with male participants expressing greater concern about lifestyle disruption from RC.
CONCLUSIONS: UK NMIBC patients exhibit diverse treatment preferences after intravesical BCG treatment failures. Preferences are shaped by current and past treatment experience, age, and personal values. Incorporating these patient‑centered insights into shared‑decision discussions may support more individualized, preference‑aligned management of BCG‑unresponsive NMIBC.
EVALUATING AGREEMENT BETWEEN PATIENT-REPORTED CLINICAL TRIAL DATA FROM ADOPT PGX AND MEDICARE AND MEDICAID CLAIMS
OBJECTIVES: A multicenter, randomized pragmatic trial, A Depression and Opioid Pragmatic Trial in Pharmacogenetics (ADOPT PGx; NCT05966129) evaluated the impact of CYP2D6-guided opioid prescribing. To assess the quality of patient-reported data from the trial and its potential integration with administrative claims, we examined agreement between selected patient-reported measures (prescriptions and healthcare utilization) and corresponding variables from Centers for Medicare and Medicaid Services (CMS) Medicare and Medicaid medical and pharmacy claims.
METHODS: Participants in the ADOPT PGx with ≥3 months of chronic pain who used or were considered for tramadol, hydrocodone, or codeine and were linked to CMS claims were included. Patient-reported trial data were compared with linked CMS claims for PGx non-concordance, all-cause emergency department (ED) visits, and hospitalizations. PGx non-concordance was defined using CYP2D6 activity scores for opioids, based on metabolizer phenotype and concomitant inhibitor use. Agreement between trial-reported and claims-based data was assessed using Cohen’s kappa (minimal acceptance threshold of κ≥0.61), and statistical differences were evaluated using McNemar’s test.
RESULTS: Among 398 participants (mean age 62 years; 73% female; 40% Black), 16% were Medicaid beneficiaries, 38% Medicare beneficiaries, and 46% were dual eligible. Agreement between trial-reported outcomes and CMS claims data was weak for PGx non-concordance (κ=0.57) and ED visits (κ=0.54), and minimal for hospitalizations (κ=0.36), all below the threshold for good agreement. Trial data reported a higher proportion of participants with ≥1 ED visit (31% vs. 25%) and hospitalizations (13% vs. 6%), whereas CMS claims captured a higher prevalence of PGx non-concordance (35% vs. 29%) (all p<0.01).
CONCLUSIONS: Agreement between patient-reported trial data and administrative claims ranged from minimal to weak. Trial data reported significantly more ED visits and hospitalizations, whereas CMS claims data captured more PGx non-concordance. These findings underscore the complementary role of administrative claims in improving outcome ascertainment in programmatic PGx research.
11:00 AM - 11:30 AM
Break (Exhibit Hall)
Session Type: General Meeting
11:30 AM - 1:00 PM
Plenary Session: Closing Remarks and Leadership Reports
Session Type: Plenary
As ISPOR 2026 draws to a close, join us for final reflections and forward-looking perspectives from the Society’s leadership. ISPOR’s Chief Executive Officer will highlight key takeaways from the conference, while the Chief Science Officer and Executive Director of the new ISPOR Institute for Healthcare Transformation will share updates on ISPOR’s evolving scientific priorities and opportunities for member engagement.
The session will then feature a closing keynote from John Singer, who will offer his perspective on the future of the healthcare system and the forces shaping its transformation.
Immediately following the opening presentations, the scientific plenary panel will take the stage.
Speakers
Plenary Session: Innovation Under Pressure: How Will U.S. Drug Policy Reshape Innovation, Evidence, and Access Globally?
Session Type: Plenary
Topics: Health Policy & Regulatory, Economic Evaluation, Health Technology Assessment
Track: Access and Drug Pricing
Level: Advanced
To say that we currently live in a VUCA (Volatile, Uncertain, Chaotic, Ambiguous) world when it comes to trade and policy would be an understatement. Global biopharmaceutical innovation is entering a pivotal decade, driven in large part by sweeping U.S. policy reforms that extend far beyond domestic borders. Building off the first plenary on U.S. Most Favored Nation and Medicare Drug Price Negotiation policies, this plenary will focus on the implications outside of the US.
With constrained budgets, trade policy influencing cost effectiveness thresholds, and reference pricing shaping launch decisions, the “global access ecosystem” is undergoing significant disruption. Drawing on perspectives from global HEOR, payer policy, and industry experts, this session will address the following questions: What will be the impact on development decisions, evidence generation, pricing corridors, launch strategies, and long run incentives to invest in innovation?
The session will conclude with a forward-looking discussion on how health systems can sustain meaningful rewards for innovation and adaptations that are necessary for innovators and the evidence generation community to remain resilient amidst change.
Moderator
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Indranil Bagchi, MS, PhD
GSK US, Collegeville, PA, United States
Dr. Indranil Bagchi is the Global Head of Pricing & Market Access at GSK. In this role, Indranil drives the overall strategy on value demonstration and market access across all product areas in the GSK portfolio, to secure access to medicines for our patients and to maximize the value of our portfolio.
Indranil has more than two decades of experience in market access across several major companies in the pharmaceutical industry. In 2014, Indranil received the ‘Outstanding 50 Asian Americans in Business’ award and in 2010, Indranil was recognized in Pharmaceutical Executive magazine’s annual roster of Emerging Leaders, “The New Breed of Leadership.” Indranil is a frequent speaker and contributor to forums, articles and conferences addressing issues related to access to medicines.
Prior to GSK, Indranil was Senior Vice President and Worldwide Head of Value and Access at Novartis Oncology. Previously at Pfizer, he was Vice President and Global Head of Payer Insights and Access and prior to that, he was with GlaxoSmithKline in Health Economics and Outcomes Research. Dr. Bagchi has an undergraduate degree in Pharmacy, a master’s degree in Pharmacy and Healthcare Administration and a doctoral degree in Pharmaceutical Socioeconomics.
Speakers
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Lotte Steuten, MSc, PhD
Office of Health Economics, London, United Kingdom
Lotte Steuten, PhD Deputy Chief Executive of the Office of Health Economics; former Member, Board of Directors, ISPOR
Prof Lotte Steuten is deputy chief executive of the Office of Health Economics (OHE), the world’s oldest independent health economics research organization, based in London, UK, and a globally recognized expert in health economics and outcomes research (HEOR).
Her research addresses challenges in valuing and paying for innovative therapies, with the aim of achieving effective, accessible, affordable, and efficient healthcare for all. She has published over 150 peer-reviewed papers on topics including the value of novel treatments, diagnostics and prevention for a wide range of non-communicable and infectious diseases.
With 2 decades of experience across Europe, the United States, and Asia Pacific, she advises governments, industry, and other organizations worldwide. She is frequently sought by media and international stakeholders for expert commentary on HEOR, value assessment, health policy innovation, and evolution of health technology assessment globally.
Alongside her position at OHE, Prof Steuten is a visiting honorary professor at City St George’s, University of London. Prior to joining OHE, she held academic faculty positions at the Fred Hutch Cancer Research Center and the University of Washington in the United States. She earned her PhD (with honors) from Maastricht University in the Netherlands.
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Darius Lakdawalla, PhD
University of Southern California, Los Angeles, CA, United States
Darius Lakdawalla is a widely published, award-winning researcher and a leading authority on health economics and health policy. He holds the Quintiles Chair in Pharmaceutical Development and Regulatory Innovation at the University of Southern California, where he sits on the faculties of the School of Pharmacy, the Sol Price School of Public Policy, and the Leonard D. Schaeffer Center for Health Policy and Economics, one of the nation’s premier health policy research centers.
His academic research has focused primarily on the economics of risks to health, the value and determinants of medical innovation, the economics of health insurance markets, and the industrial organization of healthcare markets. Dr. Lakdawalla serves as associate editor at the Journal of Health Economics and has previously served in this role at the American Journal of Health Economics and the Review of Economics and Statistics. His academic work has appeared in leading peer-reviewed journals of economics, health policy, and medicine, including the American Economic Review, Quarterly Journal of Economics, Health Affairs, the Journal of Health Economics, and the New England Journal of Medicine. In addition, his work has been featured by prominent popular press outlets, such as the Wall Street Journal, National Public Radio, Forbes, and the New York Times. Dr. Lakdawalla has also received the PhRMA Foundation Value Assessment Challenge Award, designed to encourage innovative approaches to defining and measuring value in health care, in 2019 (third place) and 2020 (first place), along with the ISPOR Excellence in Research Methodology Award, the Garfield Prize, and the Milken Institute Award for Distinguished Economic Research.
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Jens Grueger, PhD
Boston Consulting Group, Freiburg, Germany
Jens Grueger is a Senior Advisor at the Boston Consulting Group advising life sciences companies on pricing and market access, and a Senior Advisor at Curta, focusing on evidence, value, access and pricing. He is an Affiliate Professor of Health Economics at the CHOICE Institute, University of Washington School of Pharmacy and ISPOR’s 2020-2021 President.
Previously, Jens had a distinguished career in the pharmaceutical industry. He was Senior Vice President and Head of Global Access for F. Hoffmann-La Roche (2011-2019). Jens was Vice President and Head of Global Market Access Primary Care at Pfizer (2009-2011), Head of Global Pricing & Health Economics at Novartis (1999-2009), and Director of Health Economics at the German affiliate of SmithKline Beecham Pharma (1994-1997). He founded Diversified Health Systems, an internet-based disease management services start-up (1997-1999).
Jens holds a MSc in Medical Statistics and Theoretical Medicine and a PhD in Mathematical Statistics from the Technical University of Dortmund, Germany and has authored more than 40 publications.
