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Short Courses

All short courses require a separate registration fee.

* Program subject to change

Sun 12 Nov8:00 - 12:00Short Course Morning SessionsHealth Economic Modeling in R: A Hands-on IntroductionLevel: IntroductoryTrack: Economic Evaluation

Separate registration required.

This highly practical course will outline the computational and transparency advantages of using R, for those used to health economic modelling using Microsoft Excel. This course explores the use of R for health economic modelling in the context of health economics and outcomes research (HEOR) and faculty will guide the participants through practical examples of HEOR. The faculty are expert speakers who have diverse experience in academia, national Health Technology Assessment agencies (NICE, NCPE), and industry. The faculty will lead participants through practical examples of health economic modelling including using R for Markov models from deterministic analysis through to probabilistic sensitivity analysis and EVPI. Additional useful packages for modelling using R will also be discussed. All sessions will interchange between descriptive lectures and hands-on exercises. Participants will be provided with materials, including model examples in R and information on where to go for further learning.

This course is designed for those with some familiarity with modelling techniques, such as the concepts of discrete time cohort Markov models and probabilistic sensitivity analysis, but familiarity with R coding is not required.

Attendees will require a laptop with RStudio (v1.1.0 or higher) and R (v4.2.1 or higher) downloaded and installed.

Faculty Member

Gianluca Baio, PhD

University College London, London, United Kingdom

Gianluca Baio is a professor of Statistics and Health Economics in the Department of Statistical Science at University College London (UK). Gianluca graduated in Statistics and Economics from the University of Florence (Italy). He then completed a PhD programme in Applied Statistics again at the University of Florence, after a period at the Program on the Pharmaceutical Industry at the MIT Sloan School of Management, Cambridge (USA); he then worked as a Research Fellow and then Temporary Lecturer in the Department of Statistical Science at University College London (UK). Gianluca's main interests are in Bayesian statistical modelling for cost effectiveness analysis and decision-making problems in the health systems, hierarchical/multilevel models and causal inference using the decision-theoretic approach. Gianluca leads the Statistics for Health Economic Evaluation research group within the department of Statistical Science and he is the co-director of UCL MSc Programme in Health Economics and Decision Science.

Rose Hart, PhD

Lumanity Inc., Sheffield, United Kingdom

Rose Hart is a senior health economist at Lumanity, where she has been part of the modeling team for over 5 years with a focus towards advanced analytics and strategic solutions. She is experienced in developing health economic models for early-phase cost effectiveness and for health technology assessment. As a specialist in R modelling, with and without Shiny interface functionality, she is responsible for internal Shiny training and is a development leave in expanding Lumanity’s intRface™ services. Rose previously worked in the BioPharm team at GlaxoSmithKline and researched for her PhD at the University of Sheffield.

Felicity Lamrock, PhD

Queens University Belfast, Belfast, ANT, United Kingdom

Dr. Felicity Lamrock is a Lecturer in Data Analytics at Queen’s University Belfast. She is currently the Director of the Northern Ireland Centre for Health Analytics and Decision Science (NI-CHADS) with a focus on the analysis of health data for decision modelling. Current projects include a range of disease areas including cancer, rare diseases, diabetes, COVID-19, and cardiovascular disease. Felicity was previously a statistician at the National Centre for Pharmacoeconomics (NCPE) working with a team of pharmacists and clinicians on Health Technology Assessments to advise the Health Service Executive on the recommendation of new drug therapies in Ireland. She remains involved with NCPE as a statistical advisor and is exploring how Northern Ireland could benefit from more decision modelling/pharmacoecononomic assessment.

Howard Thom, MSc, PhD

University of Bristol, Bristol, UK; Clifton Insight, Bristol, SOM, United Kingdom

Howard Thom is a Senior Lecturer in Health Economics at the University of Bristol and Senior Director at the consultancy Clifton Insight. His research interests are value of information, uncertainty in economic models, network meta-analysis, and R for health economics.

Developing Decision-Grade Real-World EvidenceLevel: IntermediateTrack: Real World Data & Information Systems

Separate registration required.

In this course, participants will be guided through a hands-on analysis of real-world data to develop decision-grade real-world evidence (RWE) that could be used to support an indication expansion. The first section of the course focuses on what makes RWE “decision-grade.” We will review the most recent RWE frameworks and guidelines set by regulatory agencies and professional organizations, and we will examine case studies in which these guidelines were used in regulatory and HTA approval. The second half of the course is an active workshop where participants will use principles from the first half of the course to execute a decision-grade RWE study. Participants will be guided step-by-step in using a software platform that will enable them to work within a longitudinal US insurance claims database with anonymized patients. After the study has been executed, we will discuss how these results could be communicated to decision makers. Participants should come with a laptop with Google ChromeTM installed.

PREREQUISITE: Students are expected to be familiar with relevant concepts and methodologies for analyzing real-world data, but this course does not require specific programming skills.

Faculty Member

Dorothee Bartels, PhD, MSc

Aetion, Inc., Neuss, Germany

Dorothee Bartels is a trained epidemiologist and is currently the chief digital officer at Aetion. She has more than 15 years of experience in pharma industry as head of Real-World Evidence (RWE) and Digital Sciences at UCB Biosciences GmbH, as corporate head of Global Epidemiology at Boehringer Ingelheim, and as Chief digital science officer in the innovation Lab, Bi X. She also was the Clinical and Real-World Data Strategy lead at X, Moonshot (Alphabet Inc., former Google X). She maintains appointments as associate professor for Public Health and Epidemiology at Hannover Medical School (MHH), as adjunct professor for Epidemiology and Biostatistics at McGill University and teaches in the course “Successful Implementation of Digital Health” at the Institute for Communication and Leadership (Switzerland). She also holds several roles on advisory boards. Her aim is to enhance evidence generation based on real-world data, including patient-generated health data (digital epidemiology), and applying ML/AI in combination with established epidemiological statistical methods.

Shirley Wang, PhD, MSc

Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

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.

Risk-Sharing/Performance-Based Arrangements in Developing CountriesLevel: IntermediateTrack: Health Policy & Regulatory

Separate registration required.

During recent years, Managed Entry Agreements (MEAs) have become instrumental in ensuring the access of innovative medicines. This course is designed for healthcare professionals (including public decision-makers, academia, and industry) involved in pricing and reimbursement decisions who are wishing to understand the applicability and technical aspects of managed entry agreements (MEAs) in countries with severe economic constraints and explicit cost-effectiveness criterion. The topic will be introduced with key features of pricing and reimbursement systems in representative countries to understand why special methods are needed to facilitate evidence-based reimbursement policies of new health technologies. Faculty will present an economic model to explain the methodology and implications of managed entry agreements in cost-effectiveness and budget impact analysis. Participants will then have the opportunity to apply what they have learned through a hands-on exercise on making pricing and reimbursement decisions. A decision algorithm will be presented to support evidence and value-based policy decisions of high-cost new technologies. A series of password protected economic models will add more and more complexity to a pragmatic case study on a new pharmaceutical product in oncology. To close the course faculty will lead a discussion on the applicability of a pragmatic decision tool illustrating the pros and cons of different managed entry agreements and their usefulness in CEE settings. Participants who wish to gain hands-on experience must bring their laptops with Microsoft Excel for Windows installed.

Faculty Member

Rok Hren, PhD, MSc IHP (HE)

University of Ljubljana, Ljubljana, Slovenia

Rok Hren has more than 15 years of commercial experience in pharmaceutical industry, with more than 12 years on a board level in both (i) line management, which has included full P&L responsibility for operations in Slovenia and Romania, and (ii) leadership regional functions in Central and Eastern Europe. He regularly presents on the topic of pharmaceutical economics and policies at conferences in Europe and is well experienced in healthcare media business. He received his PhD in Physiology and Biophysics from Dalhousie University, Canada and MSc in International Health Policy (Health Economics) with Distinction from London School of Economics and Political Science, UK while he was a post-Doctoral Fellow at Nora Eccles Harrison Cardiovascular Research and Training Institute, University of Utah Medical School, USA. He is also a professor at the University of Ljubljana and past president of ISPOR Slovenia Regional Chapter. In total, his publications gathered 300/394 citations (excluding self-citations) in WoS/Scopus (as of September 10, 2016).

Katarzyna Kolasa, PhD

Kozminski University, Warsaw, MZ, Poland

Katarzyna Kolasa PhD Professor of Health Economics at Kozminski University Warsaw Poland Digital Health Start Me Up Course leader ISPOR Digital Health SIG founder “The Digital Transformation of the Healthcare System” Routledge; 1st edition (July 31, 2023) Driven with passion to improve healthcare, Katarzyna has focused her academic and busi-ness career on the health economics. She has been working with multiple pricing & reimbursement challenges worldwide for the last 25 years, while holding various Regional and Global leadership positions at Astra Zeneca, BMS, Biogen Idec, Lundbeck, GE Healthcare, Straub Medical, BD and the Swedish county council of Kalmar. Katarzyna is mentor and consultant to start ups involved in the development of innovative medical devices and digital health solutions from both Holland and Poland. Since 2000 she has been academic teacher and supervisor for over 30 MBA and Phd stu-dents. In partnership with the Polish Medical Research Agency, Deloitte Digital and the Polish Central Hospital of Ministry of Interior Affairs she founded the first Digital Health six months educational program designed for digital transformation leaders working in the healthcare sector. Katarzyna developed innovative Master Program Health Economics & Big Data (HEBDA) which first edition was financed by EU Power Grant 2018 as well. She is the founder of the Global Special Interest Group Digital Health and short courses “The Role of Digital Endpoints in the Value Generation for Health Technologies”, “Risk-Sharing/Performance-Based Arrangements in Developing Countries” at International Society of Pharmacoeconomics and Outcomes Research (ISPOR). She is the current member of Edu-cational and post member of Health Science Policy Councils at ISPOR as well. Katarzyna has dedicated her academic research towards the methodological advancements into the value assessment of pharmaceuticals, medical devices, and digital health solutions. Passionate about Big Data, she led the first project of machine learning adaptation for the optimal utilization of CT scanners granted by the Polish Ministry of Health as well. Since January 2022, she is the leader of AI special interest group at the Polish Chamber of Physi-cians. With the patronage of the Polish Parliamentary Commission for Innovation & Digitali-zation, she organized the first dialog about the societal preferences towards the adoption of AI in the healthcare in Poland. Being coauthor of more than 50 IF publications, she presented her research at more than 60 international scientific conferences. As of 2022, Google Scholar reports over 730 cita-tions to her work.

Bertalan Nemeth, PhD

Syreon Research Institute, Budapest, Hungary

Bertalan Németh PhD graduated from the Corvinus University of Budapest (MSc in Quantitative economics and Operation research), the Eötvös Loránd University (Pharmaceutical economics and drug policies), and the Semmelweis University School of PhD Studies. Between 2010 and 2015 he was a health economist at the Hungarian HTA office. Since August 2015 Bertalan has been a senior health economist, and since 2019 a Principal Researcher at Syreon Research Institute. Bertalan is responsible for strategic consulting, and he is involved in various projects that include modelling, economic evaluation in health, health technology assessment and health statistics as well. Bertalan was the president of the ISPOR Hungary Chapter and was the chair of the ISPOR CEE Consortium. He was a participant in the international EUnetHTA project, the ISPOR HTA Roundtable Europe, and the Scientific Committee of the META Conference. Bertalan was also a faculty member of the global ISPOR HTA Training and was the module leader of Health Technology Assessment for the MSc program at Eötvös Loránd University.

Network Meta-Analysis in Relative Effectiveness ResearchLevel: IntermediateTrack: Study Approaches

Separate registration required.

For several medical questions of interest, many treatment options exist for the same indication. These treatments may have been compared against placebo or against each other in clinical trials. Knowing whether one specific treatment is better than placebo or some other specific comparator is only a fragment of the big picture, which should incorporate all available information. Ideally, one would know how all the treatment options rank against each other and the level of differences in treatment effects between all the available options. Network meta-analysis provides an integrated and unified method that incorporates all direct and indirect comparative evidence about treatments. Based in part on the ISPOR Task Force Reports on Indirect Treatment Comparisons, the fundamentals and concepts of network meta-analysis will be presented. The evaluation of networks presents special challenges and caveats, which will also be highlighted in this course. The material is motivated by instructive and concrete examples. The ISPOR-AMCP-NPC questionnaire for assessing the credibility of a network meta-analysis will also be introduced.

This course requires at least a basic knowledge of meta-analysis and statistics.

Faculty Member

Sarah Goring, MSc

SMG Outcomes Research, Vancouver, BC, Canada

Sarah Goring has nearly 20 years of experience in health economics and outcomes research. Sarah is currently an independent consultant, providing scientific leadership on a broad range of studies including epidemiological and burden of illness studies, health services research, systematic reviews, and evidence synthesis. Sarah has a B.Sc. in mathematics from the University of Victoria and an M.Sc. in health care and epidemiology from the University of British Columbia. Sarah is a co-editor of a Springer textbook on Health Services Research, and has co-authored over 70 research contributions.

Jeroen Jansen, PhD

University of California – San Francisco, San Francisco, CA, USA

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. Furthermore, 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.

Introduction to Health Technology AssessmentLevel: IntroductoryTrack: Health Technology Assessment

Separate registration required.

This introductory course is designed to teach academic researchers, health policy decision makers, manufacturers, and clinicians about the key elements, methods, and language of health technology assessment (HTA). The course provides an overview of basic HTA principles including benefit assessment (biostatistics, clinical epidemiology, patient-relevant outcomes, risk-benefit assessment), economic evaluation (costing, cost-effectiveness analysis, pharmacoeconomic modeling, budget impact analysis, resource allocation), and ELSI (ethical, legal, and social implications). Using real world examples covering both drugs and devices, the course will review the practical steps involved in developing and using HTA reports in different countries and healthcare systems. Discussion with participants will focus on the implementation of HTA in health care decision making and stakeholder perspectives.

This course is suitable for those with little or no experience with HTA.

Faculty Member

Petra Schnell-Inderst, MPH, PhD, Dipl. Biol

UMIT TIROL - University for Health Sciences and Technology, Hall i. T., 7, Austria

Dr. Dipl.-Biol. Schnell-Inderst, MPH, is a Senior Scientist at the Institute of Public Health, Medical Decision Making and Health Technology Assessment at UMIT TIROL - University for Health Sciences and Technology in Hall i. T., Austria. She heads the Program on Health Technology Assessment at the Institute. Her main research interests are in health technology assessment methodology with a focus on medical devices (see www.medtechta.eu. www.core-de.eu), digital health technologies, and public health interventions (screening programs).

Uwe Siebert, MD, MPH, MSc, ScD

UMIT TIROL - University for Health Sciences and Technology, Hall in Tirol, Austria. ONCOTYROL - Center for Personalized Cancer Medicine, Innsbruck, Austria. Harvard T.H. Chan School of Public Health and Harvard Medical School, Hall in Tirol, 7, 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, EUCAPA, PREMIO COLLAB). 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.

Introduction to Machine Learning MethodsLevel: IntermediateTrack: Methodological & Statistical Research

Healthcare data are often available to payers and healthcare systems in real time, but are massive, high dimensional, and complex. Artificial intelligence and machine learning merge statistics, computer science, and information theory and offer powerful computational tools to enhance the extraction of useful information from complex healthcare data and prediction accuracy. This course gives an overview of basic machine learning concepts and introduces a few commonly used machine learning techniques and their practical applications in healthcare and pharmaceutical outcomes research. Participants will be introduced to foundational principles and concepts of statistical machine learning, then be provided with several specific machine learning techniques and their applications in health and pharmaceutical outcomes research. The course faculty will use R or Radiant to demonstrate several machine learning methods such as penalized regression and tree-based methods, as well as techniques for dimension reduction/feature selection. Participants will have hands-on practical experiences with machine learning and gain experience interpreting and evaluating the results and prediction performance that comes from machine learning modeling. Distinguishing prediction modeling from causal inference research in pharmacoepidemiology will be also presented and discussed. This is an entry-level course but is designed for those with some familiarity with traditional statistical modeling techniques (eg, linear regression, logistic regression).

PREREQUISITES: To get the most out of the course, students should have a basic statistical background. Participants who wish to gain hands-on experience are required to bring their laptops with Radiant (https://radiant-rstats.github.io/docs/install.html) installed.

Faculty Member

Wei-Hsuan Lo-Ciganic, PhD, MSPharm, MS

University of Florida, Gainesville, FL, USA

Dr. Wei-Hsuan Jenny Lo-Ciganic is a pharmacoepidemiologist and associate professor in the Department of Pharmaceutical Outcomes and Policy at the University of Florida College of Pharmacy. Her research agenda focuses on drug safety and addiction. Dr. Lo-Ciganic has extensive experience applying advanced predictive analytics including machine learning and trajectory modeling with large healthcare datasets. She conducts research to develop risk prediction algorithms and tools, and practical intervention applications for use in real-world settings to improve health outcomes and patient care. She is also a core faculty member in the Center for Drug Evaluation and Safety (CoDES) at the University of Florida College of Pharmacy.

William Padula, PhD, MSc, MS

University of Southern California, Los Angeles, CA, USA

William Padula, PhD is Assistant Professor of Pharmaceutical & Health Economics at the University of Southern California School of Pharmacy, and a Fellow in the Leonard D. Schaeffer Center for Health Policy & Economics. He is a Co-Founder & Principal at Stage Analytics. His research focuses on the theoretical foundations of medical cost-effectiveness analysis and applications of machine learning. He was the 2021 recipient of ISPOR’s Bernie O’Brien New Investigator Award, Co-Chair of the ISPOR Machine Learning Task Force, and is an Associate Editor for Value in Health.

Budget Impact Analysis I: A 6-Step ApproachLevel: IntroductoryTrack: Economic Evaluation

Separate registration required.

This course will describe the methods used to estimate the budget impact of a new health care technology and will present six basic steps for estimating budget impact: (1) estimating the target population; (2) selecting a time horizon; (3) identifying current and projected treatment mix; (4) estimating current and future drug costs; (5) estimating change in disease-related costs; and (6) estimating and presenting changes in annual budget impact and health outcomes. Both static and dynamic methods for estimating the budget and health impact of adding a new drug to a health plan formulary will be presented. These six steps will be illustrated using actual budget impact models.

This course is designed for those with some experience with pharmacoeconomic analysis.

Faculty Member

Thor-Henrik Brodtkorb, PhD

RTI Health Solutions, Ljungskile, O, Sweden

Thor-Henrik Brodtkorb, PhD, is executive director in Health Economics at RTI Health Solutions (RTI-HS). He holds a PhD in Health Technology Assessment from the University of Linköping and has been with RTI-HS for 12 years. He has been teaching courses in decision-analytic modeling at Linköping University as well as presented workshops and short courses on decision-analytic modeling techniques for organizations such as Pharma Industry Sweden, Swedish Agency for Health Technology Assessment and Assessment of Social Services (SBU), and ISPOR. At RTI-HS, Dr. Brodtkorb leads the development of cost-effectiveness, cost-utility, cost-consequence, and budget-impact models for pharmaceutical, device, and diagnostic technologies. These models have been used to support reimbursement decisions in more than 15 European countries including NICE in UK, SMC in Scotland, TLV in Sweden, and NOMA in Norway. He has developed models and analyses in the areas of oncology, alcohol dependence, major depressive disorder, Alzheimer’s disease, dermatology, multiple sclerosis, cardiology, orthopedics, and asthma. His research has been presented at professional conferences and published in peer-reviewed journals. He is also a co-author of the book “Budget-Impact Analysis of Health Care Interventions: A Practical Guide.”

Stephanie Earnshaw, PhD, MS

RTI Health Solutions, Pittsboro, NC, USA

Stephanie Earnshaw is senior vice president of Health Economics at RTI Health Solutions (RTI HS). She received her PhD in Industrial Engineering at North Carolina State University and has performed health outcomes and health services research for over 30 years, 24 of which have been with RTI-HS. 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 is the current Educational Council Chair. 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.” Dr. Earnshaw’s research focus is in applying decision-analysis techniques to industry-related issues and health care problems. Her areas of specialization include mathematical programming (constrained optimization), network optimization, and Markov, simulation, and other state transition modeling. 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. Therapeutic areas include cardiovascular disease, gastrointestinal disorders, respiratory disease, acute care, infectious disease, osteoporosis, vaccines, and oncology. She is a member of ISPOR and the Institute for Operations Research and the Management Sciences. She has presented her work at professional conferences and has published in several peer-reviewed journals.

C. Daniel Mullins, PhD

University of Maryland School of Pharmacy, Baltimore, MD, USA

C. Daniel Mullins, PhD 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. He received his BS in Economics from M.I.T. and his PhD in Economics from Duke University. His research and teaching focus on comparative effectiveness research (CER) and patient-centered outcomes research (PCOR). Dr. Mullins has received funding as a Principal Investigator from AHRQ, FDA, NHLBI, NIA, NIMHD, Patient-Centered Outcomes Research Institute (PCORI) and various patient advocacy organizations and pharmaceutical companies. He is the lead for the Community & Collaboration (C&C) Core of the University of Maryland Institute for Clinical and Translational Research (ICTR) and co-lead of the C&C Core for Johns Hopkins’ CTSA. Professor Mullins is 1 of 2 editors-in-chief for Value in Health and is author of over 325 peer-reviewed articles and book chapters. 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. He is a past recipient of the Dr. Daniel D. Savage Memorial Science Award, the Association of Black Cardiologists’ most prestigious annual award, and the ISPOR Marilyn Dix Smith Leadership Award.

Estimating Health-State Utility for Economic Models in Clinical Trials and Real-World StudiesLevel: IntroductoryTrack: Patient-Centered Research

Separate registration required.

Health state utility (HSU) estimates are among the most important and uncertain data inputs in cost-utility models which are increasingly being used to inform health technology assessment, pricing, and reimbursement decisions in many countries. This course will provide an in-depth consideration of best practice in the collection of health utility data in clinical trials, real-world and other studies, to provide high quality HSU estimates appropriate for economic modeling. Centered on the ISPOR Outcomes Research Guideline, Collecting Health-State Utility Estimates for Economic Models in Clinical Studies (Wolowacz et al., 2016), the course will address key challenges surrounding study design, data collection and analysis. This will include how to anticipate and address common issues that may affect data quality, alignment with the needs of economic model, acceptability to the model audience, and how to apply good research practices for HSU estimation in future research. The course will also address issues associated with collection of utility data for rare diseases and from special populations including cognitively impaired and pediatric populations. The course will be of value for researchers actively involved in the design or implementation of HSU data collection or analysis, those involved in patient-reported outcomes research, economic modeling, economic evaluation, or health technology assessment.

The course will not cover in any depth the fundamentals of utility theory, development of generic or condition-specific preference-based multi-attribute utility instruments, or how to perform time trade-off or standard gamble experiments. Nor will it cover statistical methods for mapping/cross-walking from a condition-specific HRQL measure. Although these topics will be touched on in overview, the focus of this course will be on optimizing the collection of utility data to provide HSU estimates for economic models.

Faculty Member

Lynda Doward, MRes

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.

Emma Hawe, MSc

RTI Health Solutions, Manchester, United Kingdom

Emma Hawe, MSc, is Head of Data Analytics and Design Strategy at RTI-HS. She has over 20 years of experience as a statistician within consulting, regulatory, and academic environments. Ms. Hawe is experienced in the application of novel and standard statistical methodologies to large medical/biological data sets in diverse therapeutic areas. Her role at RTI-HS includes planning, executing, performing, and interpreting the analysis of a variety of studies, including systematic literature reviews, meta-analysis, epidemiology, health economics, and clinical trials. Prior to joining RTI-HS, Ms. Hawe was Head of Statistics at the Office of Health Economics, where she managed a variety of different projects, including burden-of-illness studies, multicriteria decision analysis, and policy-orientated projects for pharmaceutical companies, pharmaceutical trade associations, and overseas governments. Ms. Hawe has conducted many types of statistical analyses, including network meta analysis, survival analysis, factor analysis, analysis of utilities including mapping, multivariate modeling, and database analysis including the analysis of Hospital Episode Statistics (HES). She has successfully led and managed projects for a variety of different clients and contributed to many more. In addition, Ms. Hawe has experience with a variety of different statistical packages and programming languages, including R, STATA, SAS, and SQL. Ms. Hawe is author of the Office of Health Economics guide to UK health and health care statistics, a comprehensive guide to health statistics in the UK, and author of more than 75 publications in peer-reviewed journals. Previous positions have involved the statistical analysis of the combined effects of genetics and the environment on cardiovascular disease, and the study of births and infant mortality data in England and Wales over a 20-year period.

Andrew Lloyd, PhD

Acaster Lloyd Consulting Ltd, London, United Kingdom

Sorrel Wolowacz, PhD

RTI Health Solutions, Manchester, United Kingdom

Sorrel Wolowacz, PhD, is Head of European Health Economics at RTI-HS, with 22 years of experience in health economics research and consulting. Her research focuses primarily on economic modelling, health utility estimation, observational studies, and health technology appraisal submissions. Dr. Wolowacz is a member of the editorial board for the Journal of Comparative Effectiveness Research and was co-chair of the ISPOR Good Research Practices Task Force addressing Measurement of Health State Utility Values for Economic Models in Clinical Studies and is a member of the ISPOR Oncology Special Interest Group.

Statistical Methods for Health Economics & Outcomes ResearchLevel: IntermediateTrack: Economic Evaluation

Separate registration required.

This course will provide an introduction to statistical concepts with an emphasis on the use of techniques commonly employed in health economics and outcomes research. Faculty will begin by defining statistics, then introducing the concept of random variables and probability before proceeding to discuss the foundations of statistical inference (estimation and the testing of hypotheses). This is followed by bootstrapping, statistics in cost-effectiveness analysis and generalized linear modeling (for cost and utility outcomes). The differences between a classical (frequentist) approach to statistics and a Bayesian view of probability will also be outlined.

This course is intended for participants with little (or rusty!) statistical training.

Faculty Member

Derrick Bennett, MSc, PhD, CStat

University of Oxford, Headington, Oxford, United Kingdom

Derrick Bennett is Associate Professor in Medical Statistics and Epidemiology. He has a BSc (Hons) in Mathematics and Statistics, an MSc in Medical Statistics, and a PhD in Epidemiology/Statistics. He has been a Royal Statistical Society accredited Chartered Statistician (CStat) since 2005. His research is interdisciplinary, integrative and collaborative and has focused on using large-scale observational studies and randomized trials to generate reliable evidence for prevention of premature deaths and disability from chronic diseases. He co-leads the Statistical Group in the China Kadoorie Biobank (CKB) a large prospective study of 0.5M Chinese adults recruited from 10 regions (five urban and five rural) in China. His work involves applying statistical, epidemiological, computational, and genetic tools to understand associations of exposures with chronic diseases, to drive improvements in population health via identification of novel treatment targets and implementation of precision strategies for primary and secondary prevention of major disease outcomes (such as cardiovascular disease, stroke, diabetes, and cancer). He is responsible for developing and implementing a portfolio of CKB research themes (such Aging, Cardiovascular and Adiposity), ensuring robust, appropriate, and deliverable methodological input to study design, research conduct, and securing grant income as lead statistical co-investigator. He is a co-lead for the Principles of Data Science module of the MSc in Global Health Science and Epidemiology and is leading the curriculum development for data science teaching, in addition to training and supervision of both undergraduate and postgraduate students (currently supervising three MSc projects and 8 DPhil projects). He has also contributed chapters to four textbooks and was named as a Highly Cited Researcher for 2018 for highly cited papers that rank in the top 1% in his field of research. In 2022 he was listed amongst the top 1000 scientists in the UK in the Research.com Medicine rankings.

Jim Lewsey, PhD, CStat

University of Glasgow, Glasgow, United Kingdom

Jim Lewsey, PhD, is a reader in Medical Statistics and joined the University of Glasgow in 2007 having previously held posts at the London School of Hygiene and Tropical Medicine (2003-2007), University of Otago (2001-2003), Eastman Dental Institute-UCL (1998-2001), and University of Glasgow (1996-1998). He was awarded Chartered Statistician status from the Royal Statistical Society in 2010 and Chartered Scientist from the Science Council in 2012. His personal research interests stem from methodological challenges faced when analyzing observational and experimental medical data and have included prognostic model development in the presence of missing data, continuous outcome monitoring of long-term outcomes, modelling dental caries data, and design of cluster randomized trials. His current methodological interests include multi-state survival analysis and modelling of data from natural experiments, and in his applied research he is developing a portfolio of alcohol research. Jim leads the Analysis of Linked Health Data (ALDA) program within HEHTA and is deputy lead of the IHW research theme 'Data Science - Using routine administrative data and record linkage for research'. Jim is program director and teaches on the MSc in Health Technology Assessment. He also teaches and coordinates a medical statistics course on the Masters in Public Health.

8:00 - 17:00Short Course Full Day SessionReimbursement Systems for Pharmaceuticals in EuropeLevel: IntermediateTrack: Health Policy & Regulatory

Separate registration required.

Unlike marketing authorization for pharmaceuticals, mainly regulated at the European level by EMA, pricing and reimbursement decisions in Europe are managed by individual member states. Health care services are generally covered by a single public health insurer operating under the Ministry of Health supervision. As a monopoly buyer, this situation provides a leading position for the public health insurer to set reimbursement conditions. Therefore, based on each country’s set of regulations, processes, and values, wide variations exist in pricing and reimbursement decisions of pharmaceuticals. Using up-to-date governmental regulation sources and the ISPOR Global Health Care Systems Roadmap, this course will discuss health technology decision-making processes for reimbursement decisions for pharmaceuticals in France, Germany, Hungary, Italy, Poland, Spain, Sweden, and the UK. The course will describe these reimbursement systems, as well as compare, and bring into contrast their key characteristics.

This course is designed for individuals with intermediate experience within a single healthcare system wishing to broaden their appreciation of other reimbursement systems.

Faculty Member

Mondher Toumi, MD, PhD, MSc

Aix Marseille University, Marseille, France

Professor Mondher Toumi is an MD by training and holds two MSc in Biostatistics, and in Biological Sciences (option pharmacology) and a PhD in Economic Sciences. He is a professor of Public Health at Aix-Marseille University. After working for 12 years as a research manager in the Department of Pharmacology at the University of Marseille, he joined the Public Health Department in 1993. In 1995, he entered the pharmaceutical industry and worked there for 13 years. Mondher Toumi was appointed global vice president at Lundbeck A/S in charge of health economics, outcome research, pricing, market access, epidemiology, risk management, governmental affairs, and competitive intelligence. In 2008, he founded Creativ-Ceutical, an international consulting firm dedicated to support health industries and authorities in strategic decision-making. In February 2009, he was appointed professor at Lyon I University in the Department of Decision Sciences and Health Policies. He launched the first European University Diploma of Market Access (EMAUD) an international course already followed by more than 500 students. Additionally, he recently created the Market Access Society to promote research and scientific activities around market access, public health and health economic assessment. He is chief editor of the Journal of Market Access and Health Policy (JMAHP). Since September 2014, he joined the research unit EA3279 of the Public Health Department, at Aix-Marseille University (France) as Full Professor. Mondher Toumi is also visiting professor at Beijing University (Third Hospital). In June 2022 Mondher Toumi founded InovIntell an international venture dedicated to AI in life sciences. He is a recognized expert in health economics and an authority on market access and risk management. He published more than 200 scientific publications and authored or co-authored several books predominantly in the fields of market access and health economics.

13:00 - 17:00Short Course Afternoon SessionsEarly Health Technology AssessmentLevel: IntermediateTrack: Health Technology Assessment

Separate registration required.

This intermediate level course is for industry, researchers, advisory, regulatory, and funding agencies, governments, payers, clinicians, patients, and others who have a stake in improving care and services. The course focuses on Health Technology Assessment (HTA) concepts and methodologies in the early stages of product development (ie, early HTA). The research and development of a new medical technology is generally an expensive process; information about the potential clinical impact of a product—and its adoption and implementation into practice—at an early stage can justify the investment and guide further decision making all along the line. A major challenge is how to generate this information when no or only limited data is available.

This course provides an overview of the importance and constraints of early HTA, the evaluation and decision frameworks of different stakeholders, relevant research methodologies and the potential impact of the analyses. Using real-world case studies, we will present the process of working with stakeholders to frame the analysis, to gather evidence and to produce careful insights regarding potential new health technologies. Through a breakout exercise and group discussions, course participants will work on framing a product development decision and identify appropriate data collection and analysis methods.

PREREQUISITE: Attendance at short courses "Introduction to Health Technology Analysis", "Cost-Effectiveness Analysis Alongside Clinical Trials” and/or equivalent concepts and methodologies is prerequisite to attending this course.

Faculty Member

Janet Bouttell, MSc, PhD

Nottingham University Hospitals Trust, Nottingham, United Kingdom

Janet is a health economist at the University of Glasgow. From a background in chartered accountancy with KPMG, Janet joined the staff at the Health Economics and Health Technology Assessment (HEHTA) department in 2015. Janet completed her PhD in methods of Health Technology Assessment (HTA) for developers of diagnostic technologies in 2021. The PhD was funded by the Glasgow Molecular Pathology Node; an MRC funded collaboration between NHS Greater Glasgow and Clyde, the University of Glasgow and industry partners. Since 2021, Janet has worked on a Knowledge Transfer Partnership introducing health economics and business modelling concepts to a small developer of molecular pathology tests. https://www.gla.ac.uk/researchinstitutes/healthwellbeing/staff/janetbouttell/

Sara Graziadio, PhD

York Health Economics Consortium, York, United Kingdom

Dr Sara Graziadio is a Project Director at YHEC since 2020. Sara has a PhD in Neuroscience and an MPhil in Statistics from the Newcastle University. She led systematic and pragmatic reviews to inform the design of clinical studies, for publications and health technology assessment submissions. She developed statistical and early economic models in multiple clinical areas and analysed care pathways. She has more than 15 years’ experience of analysis of complex qualitative and quantitative datasets and 10 years’ experience of leading successful projects.

Janneke Grutters, PhD

Radboud Institute for Health Sciences, Nijmegen, GE, Netherlands

Janneke Grutters, PhD, is associate professor at the department for Health Evidence, Radboud University Medical Center, the Netherlands. She holds an MSc in health sciences and a PhD in Health, Medicine, and Life Sciences, both from Maastricht University. She is a member of several scientific and societal committees and is initiator and chair of the HTAi Working Group on Early Health Technology Assessment. Her key research interest lies in the early evaluation of innovations in healthcare. By assessing the (potential) value of an innovation in early stages of its development, she aims to contribute to more accountable decisions with regard to the development, research, and use of these innovations, leading to more efficient use of resources, and better healthcare. Learning from other fields of research, she develops, uses, and teaches methodology that enables such an early evaluation, and acknowledges all relevant uncertainties.

Ties Hoomans, PhD

London School of Economics and Political Science, London, United Kingdom

Ties has a background in in health economics and management science. His work focuses on the organization and delivery of health and social care services, with a particular interest in organizational behavior. Commonly combining quantitative and qualitative methods, Ties has done influential studies of the implementation and impact of new care approaches and guidance in everyday practice. Through his research, Ties has contributed to methodology for studying complex interventions, including implementation strategies. He is experienced in engaging stakeholders in research processes, and works closely with local governments, care providers and other organizations within the health and care system.

Lotte Steuten, PhD

Office of Health Economics, London, Greater London county, United Kingdom

Lotte Steuten, PhD, is Deputy Chief Executive of the not-for-profit Office of Health Economics (OHE) and the scientific and business lead for its international research-led work program—maintaining its reputation for objective, innovative, and high-quality research, and meeting its charitable goals. She is also an Honorary Visiting Professor at City, University of London (UK) contributing to its teaching programmes in health economics. For more than 20 years, Lotte has worked in academic, research, and consulting HEOR roles with one focus — improving healthcare decision-making through high-quality research and analysis. To achieve that, she has collaborated with HTA authorities, pharmaceutical and medical device companies, patients, payers, policymakers, academic researchers, clinical specialists, and venture capitalists. She has gained broad HEOR expertise of various technologies: precision medicine, oncology, vaccines, antibiotics, diagnostics, digital health, and medical devices. Lotte’s career has been based in the United States, the Netherlands, and the UK. Collaborations with HEOR experts in Southeast Asia, Africa, and Latin America have provided her with deep insights into the differences and commonalities between the role of HEOR in different healthcare systems, cultures, and societies. With this background, she has: led diverse international teams; developed strategies and delivered on program and organisational missions, values, and objectives; acquired research funding and managed budgets; and been responsible for executive decision-making as well as legal and fiduciary matters. As an active ISPOR member since 2004, Lotte has served on various Taskforces and Committees, delivered Short Courses, was co-Chair of ISPOR EU 2021, and is currently a member of the Board of Directors, and an Associate Editor for Value in Health. She aims to be a role model for diversity and played an active role in the 'Women in HEOR' initiative. Before joining OHE, Lotte worked in Seattle (US) as an Associate Professor at the University of Washington and at the Fred Hutch Cancer Research Center. She graduated cum laude with her PhD from Maastricht University (NL) and then worked at Brunel University (UK) and Twente University (NL).

Applied Cost-Effectiveness Modeling with RLevel: IntermediateTrack: Methodological & Statistical Research

Separate registration required.

Historically, economic models for cost-effectiveness analyses have been developed with specialized commercial software (such as TreeAge) or more commonly with spreadsheet software (almost always Microsoft Excel). But more recently there has been increasing interest in using R and other programming languages for cost-effectiveness analysis which can offer advantages regarding the integration of input parameter estimation and model simulation, the evaluation of structural uncertainty, and the quantification of decision uncertainty, among others. Programming languages such as R also facilitate reproducibility of model-based cost-effectiveness analysis which is more relevant than ever given recent calls for increased transparency. While these tools are still relatively new, there is an increased interest in learning opportunities as evidenced by recent tutorials, workshops, and development of open-source software.

In this short course, participants will learn how to use R to develop a number of different types of economic models to perform cost-effectiveness analysis. Economic models will include time-homogeneous and time-inhomogeneous Markov cohort models, partitioned survival models, and semi-Markov individual patient simulations. The underlying assumptions of each model type will be summarized and the implementation in R will be presented in an accessible manner. Participants will be asked to modify the models in R (eg, adding health states, use of alternative time-to-event distributions) and run analyses (eg, cost-effectiveness analysis, probabilistic sensitivity analysis, evaluating structural uncertainty, and value of information analysis). To make this interactive aspect of the course as efficient as possible, all participants will have access to the GitHub repository prior to the course. It will contain R code to run the economic models and R Markdown files to explain and reproduce the analyses covered in the course. Participants who wish to gain hands-on experience are required to bring their laptops with R packages and scripts available. To get the most out of the course, it is important that registrants are able to do some R programming. Special instructions will be provided before the course.

Faculty Member

Devin Incerti, PhD

EntityRisk, Inc., San Francisco, CA, USA

Devin Incerti is the head of Data Science at EntityRisk with experience spanning health economics, biostatistics, and software engineering. Previously, Dr. Incerti was a Principal Data Scientist at Genentech working on statistical methodology for real-world and observational data. In his research, he developed approaches for causal inference in hybrid and external control studies and for prediction modeling with linked clinical and genomic data. Prior to Genentech, he was a senior economist at Precision Health Economics and the lead economist for the Open-Source Value Project at the Innovation and Value Initiative (IVI), where he performed research and developed software related to the value of medical technologies. He has developed software in a variety of languages (eg, Python, R, C++) and is an active contributor to the open source and health economics communities, including the development of hesim—a software tool for cost-effectiveness modeling and analysis. Dr. Incerti received BA degrees in Mathematics/Economics and Political Science from the University of California, San Diego, and a PhD in Public Policy from Princeton University.

Jeroen Jansen, PhD

University of California – San Francisco, San Francisco, CA, USA

Valuation of Innovative DrugsLevel: IntermediateTrack: Health Policy & Regulatory

Separate registration required.

The value of medical innovation depends on the perspective. Registration authorities (EMA, FDA) mainly consider the clinical value of the medical innovation, whereas national health authorities take a broader perspective by including clinical, economic criteria, and potential other criteria like equity and social values. Value-based pricing is the most widely accepted approach in the pricing and reimbursement process in Europe, which varies from the narrow concept based on the incremental cost-effectiveness ratio (ICER) threshold to broader approaches. Value-based pricing determines the maximum price from the national payer perspective. This price should exceed the minimum price for the investor acting in the international financial market, which is based on economic valuation theory. Finally, there are other stakeholders, eg, patients, physicians’ healthcare insurers, employers, with their specific assessment of the value of medical innovation varying from, respectively, quality of life, effectiveness, budget impact, and costs of lost productivity. This course offers an overview of the perspectives of the relevant stakeholders and their respective data requirements for value assessment of innovative drugs. The course will then describe in-depth description of the various value-based pricing methods, eg, ICER, multicriteria decision analysis (MCDA), comparative effectiveness research (CER), and relative effectiveness (RE). We include examples of orphan drugs and ATMPs which are most striking to illustrate the concepts, but we also include value assessment for more traditional innovative drugs in broad indications. Familiarity with health economic evaluation is desirable, but the course assumes little or no familiarity with economic valuation theory.

Faculty Member

Afschin Gandjour, MD, PhD, MA, MBA

Frankfurt School of Finance & Management, Frankfurt, Germany

Afschin Gandjour is a medical doctor, health economist, and philosopher. His research focuses on cost-effectiveness analysis, decision modeling, and value-based pricing of pharmaceuticals. Gandjour received an MD from Hannover Medical School in Germany, an MBA from Duke University, a PhD in health economics from the University of Cologne in Germany, and an MA in philosophy from the University of Düsseldorf in Germany. He held faculty positions at the University of Cologne Medical School, Baylor College of Medicine, and Louisiana State University Pennington. In terms of research productivity, he ranks among the top professors in business administration in Germany (#20 in 2022 based on Wirtschaftswoche magazine).

Lou Garrison, PhD

The Comparative Health Outcomes, Policy, and Economics Institute, School of Pharmacy, University of Washington, Seattle, WA, USA

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. Dr. Garrison has worked in non-profit, industry, and academic settings. He received a PhD in Economics from Stanford University and has more than 200 publications in peer-reviewed journals. Dr. Garrison was elected as ISPOR President for 2016-2017, and currently serves as co-chair of ISPOR’s Policy Outlook Committee for the Health Science Policy Council. In September 2022, he was announced as the recipient of the 2022 Avedis Donabedian Outcomes Research Lifetime Achievement Award from ISPOR.

Marlene Gyldmark, MPhil

Idorsia Pharmaceuticals, Allschwill, BS, Switzerland

Marlene is a senior leader with several years’ experience in health service research, academia, and life science industry from both developing as well as developed countries. Work experience includes building state-of-the art HEOR teams at Idorsia AG, Switzerland, at Roche Diabetes Care, Switzerland, and Roche Pharma global headquarters in Switzerland, as well as holding various positions within the field of Market Access, Pricing and HEOR at Roche Pharma, Novo Nordisk, and Pfizer, Denmark. Prior to the experience in industry, Marlene worked for more than 7 years in health service research in Denmark, Nepal and Tanzania. In addition, Marlene also has many years of experience as an external lecturer in health economics at Copenhagen University, as well as leading an executive course in “Market Access for Pharmaceuticals” under Copenhagen University life-long learning. Marlene’s interest from her early days at York University is to strengthen and support good decision making in healthcare and to foster collaboration and solutions across all stakeholders in the healthcare sector. Marlene is a member of the Board of Directors at ISPOR, and also supports the patient organization Institute of Neurodiversity (ION). Marlene is educated as Cand Polit from Copenhagen University, and Health Economist from University of York, UK.

Mark Nuijten, MBA, PhD, MD

Ben Gurion University, Be'er Sheva, Israel

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.

Fred W. Sorenson, MSc

Cencora, Basel, Switzerland

Fred Sorenson is assistant director, Global Health Economics, Outcomes Research (HEOR) & Market Access at Xcenda, the consulting division of AmerisourceBergen where his work includes comparative effectiveness research, retrospective database studies, prospective studies and chart reviews, systematic literature reviews, global value dossiers and contributing to posters and publications. Mr. Sorenson also has experience, most predominantly in Europe, in developing strategy and gathering payer insights through payer interviews and advisory panels to inform HEOR initiatives and guide market access at the affiliate level. Mr. Sorenson has more than 35 years of experience in the healthcare industry, working in numerous therapeutic areas including cardiology, endocrinology, dermatology, oncology, neurology, autoimmune diseases, virology, and infectious disease. Fred received his BS in both Psychology and Philosophy from the University of Southern Colorado and did his post-graduate studies in Sociology and Economics (master’s thesis on “Registration of Vital Birth Statistics in Nepal”) at the University of Basel in Switzerland.

Going Beyond the Standard: Exploring Advanced Survival Modeling TechniquesLevel: IntermediateTrack: Methodological & Statistical Research

Separate registration required.

Survival modeling techniques are commonly used to extrapolate clinical trial outcomes like overall survival to a time horizon that is appropriate for health economic evaluations. Standard parametric distributions, such as the exponential and Weibull, have been the de-facto standard for conducting such extrapolations but, with the advent of novel potentially curative therapies, these standard parametric distributions fail to capture the underlying survival trend. Newer techniques like response based landmark models, parametric mixture models, and mixture cure models provide novel ways to capture these more complex survival patterns. The purpose of this course is to enable participants to identify which methods are most appropriate in a specific context, considering underlying structural assumptions, and discuss how modeling choices propagate into health economic evaluations. To gain a more in-depth understanding of the impact of the choice for a specific method, there will be walkthroughs of exercises which participants will be able to practice in their own time.

Faculty Member

Elisabeth Fenwick, PhD

OPEN Health Evidence & Access, Oxford, OXF, United Kingdom

Elisabeth Fenwick is Deputy Chief Scientific Officer in Evidence & Access at Open Health, based in Oxford in the UK. Liz provides scientific and strategic support to HE projects globally. She has extensive experience in economic evaluation and health economic modeling having worked in the field for over 20 years. She has worked on a variety of projects in a wide range of disease areas including oncology, respiratory, infectious diseases, cardiology, ophthalmology, and orphan diseases. Liz has also contributed to methods in the field, in particular relating to decision analytic modeling and simulation methods, probabilistic decision analytic modeling and value of information analysis. Liz was a member of the ISPOR joint task force on good research practices in modeling and a co-author on the joint taskforce paper on uncertainty and co-chaired/co-authored the recent ISPOR task force assessing emerging good practice in value of information analysis for research decisions. Liz has a PhD and MSc in Health Economics as well as an MSc in Operations Research and joined Open Health from ICON plc where she led the modeling team for the global HE group. Prior to her consultancy career, Liz spent over 15 years as an academic working at University of York, McMaster University, and most recently University of Glasgow.

Sven Klijn, MSc

Bristol-Myers Squibb, Utrecht, ZH, Netherlands

Sven Klijn is director at Bristol Myers Squibb in the HEOR Economic & Predictive Modeling group, where he leads the innovative modeling agenda in hematology. 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. Sven has a training in public health and health economics and previously had various roles in CROs related to health-economic modeling.

Claire Simons, PhD, MSc, MMATH

OPEN Health Group, York, NYK, United Kingdom

The Role of Digital Endpoints in the Value Generation for Health TechnologiesLevel: IntermediateTrack: Health Policy & Regulatory

In this short course, participants will learn about new endeavors for the value generation in the patient's centric digital era. With the exponential growth of the market of digital health with digital therapeutics, digital sensors, or mobile app we can understand better the unmet patients’ needs and identify new opportunities for healthcare system’s efficiency gains. The plethora of new digital endpoints enters clinical trials arena and helps to enrich the value propositions for medicines. It is the highest time for HEOR to expand its frontier to capture these new opportunities with growing variety and veracity of digital data from the patient’s perspective. Participants will first be familiarized with the key changes in the healthcare system in the digital era and then learn how to utilize the digital endpoints in the process of the clinical and economic value generation while ensuring the methodological rigor required for evidence-based decision making with a patient-centric approach. Participants who wish to gain hands-on experience must bring personal laptop.

PREREQUISTE: Participants should possess the basic skills and understanding of cost effectiveness and budget impact models.

Faculty Member

Jochen Klucken, MD

University of Luxembourg, Luxembourg, N/A, Luxembourg

Prof. Dr. Med. Jochen Klucken is a neurologist, neuroscientist, full professor and the FNR-PEARL chair of Digital Medicine and head of the Digital Medicine research group (dMed) at the LCSB (Luxembourg Center for Systems Biomedicine) of the University of Luxembourg, the LIH (Luxembourg Institute of Health) and the CHL (Centre Hospitalier de Luxembourg). Digital transformation in medicine utilizes better objective real-world data and smarter algorithms ("artificial intelligence") tailored to patients’ and healthcare providers’ needs and requires a profound understanding of data-driven medicine (procedures) integrated into existing medical workflows and patients’ everyday life behaviour and its disease-dependent limitation. Translational Research in Digital Medicine includes engineering and data-research, IT-requirements, but also clinical knowledge, societal expectations in ethics, acceptance, and regulation in order to enlighten the abilities of digitalization in medicine, and to avoid the downsides coming with an unheard level of transparency. The dMed research focuses on 1) shaping and innovating personalized digital healthcare solutions, and 2) evaluating the medico-socio-economic benefit of new digital medical devices and services. Prof. Klucken is also co-leading the EU Taskforce for Harmonized Evaluation of Digital Medical Devices with a strong focus on Digital Medical Devices and their innovative clinical evaluation frameworks. Future digital medicine ecosystems will provide real-world data for continuous quality monitoring of existing healthcare procedures and innovative evaluation concepts providing real-world evidence for digital medicine.

Katarzyna Kolasa, PhD

Kozminski University, Warsaw, MZ, Poland

Alison Ritchie, PhD

Parexel, Gamston, England, United Kingdom

Alison is the global head of Sensor Solutions at Parexel, and also supports real-world data sales and operational delivery. Alison has worked at Parexel for over 20 years and has over 24 years’ experience within the clinical trial industry. She also plays a key role by selecting and implementing real-world data and connected sensor device solutions for clinical trial use. Alison has a broad range of expertise within the technology area of Clinical Trials phase 1-4, with a background within multiple technology areas, including operations, product delivery and client management. She is also passionate about diversity, equity and inclusion whilst advancing technology within Clinical Trials and as a result advancing patients care and acts within the Parexel Committee, as well as being an active enterprise advisor.

Reporting Economic Evaluations: How to Use CHEERS 2022Level: IntroductoryTrack: Economic Evaluation

Separate registration required.

Economic evaluations make up a large proportion of the literature in health economics and outcomes research. These studies are increasingly used in healthcare decision making and it is critical that they are reported correctly. This course is intended to familiarize participants with the rational for, and content of, the important reporting items in economic evaluations. The Consolidated Health Economic Evaluation Reporting Standards (CHEERS) are an EQUATOR guideline and represent the state of art for reporting economic evaluations. CHEERS consists of 28 reporting items relating to the introduction and design of economic evaluations, their methods, and the reporting of results. The rationale for the various items will be given, along with illustrative examples explaining their content. Participants will learn how to use CHEERS in reporting their own economic evaluations, and in reading evaluations conducted by others. In addition, key issues relating to the use of CHEERS will be discussed.

Faculty Member

Federico Augustovski, MD, MSc, PhD

Institute for Clinical Effectiveness and Health Policy (IECS), Buenos Aires, B, Argentina

Federico Augustovski is the current director of Health Economic Evaluations and Technology Assessment at the Institute for Clinical Effectiveness and Health Policy (IECS), an independent non-profit organization affiliated to the University of Buenos Aires, a CONICET (National Scientific and Technical Research Council) center, and one of the few INAHTA Health Technology Assessments agencies in Latin America. He is the director of the WHO Collaborating Centre in Health Technology Assessment and Economic Evaluations at IECS. He is a professor of Public Health at the School of Public Health of the University of Buenos Aires, where he teaches courses for graduate and postgraduate students in Decision Sciences; Patient Reported Outcomes (PRO) Development in Health as well as Health Economic Evaluations. He was elected president 2017-2020 of ISPOR (The Professional Society for Health Economics and Outcomes Research). He is also the founding editor-in-chief for Latin America of Value in Health Regional Issues (ViHRI), the ISPOR peer-reviewed journal for Latin America, Asia, and Central & Eastern Europe and Africa. He is the director of the PAHO affiliated PROVAC Center of Excellence for decision making in vaccines. He leads a multidisciplinary team devoted to clinical and economic evaluations of new and existing preventive, diagnostic and therapeutic technologies that works doing research, education, and technical support with public and private health decision makers in Latin America. He got his medical degree with honors at the University of Buenos Aires (1986-1991), and he is a specialist in family medicine. He practiced family medicine and was a staff physician for more than 20 years at the Family and Community Medicine Division of the Hospital Italiano de Buenos Aires (the leading academic non-profit hospital in Argentina). He got his MSc in Epidemiology (Harvard School of Public Health, 1997-1999). He was an Alban Scholar of the European Union in Health Economics (2003-2004) getting research and training experience at the Centre for Health Economics at York University in the UK. His research production and publication in international peer-reviewed journals (with more than 160 PubMed indexed papers), concentrates on health technology assessments, health economic evaluations (ie, multi-country studies in Latin America, both model-based and individual patient level piggyback studies, PRO and preference status measures and validation (ie, derivation of Argentine, Uruguay and Peruvian weights for the EQ-5D, Argentine SF-36 validation, and discrete choice experiments).

Nathorn Chaiyakunapruk, PharmD, PhD

Department of Pharmacotherapy, College of Pharmacy, University of Utah, Salt Lake City, UT, USA

Dr.Chaiyakunapruk (Or Nui) is a Professor in the College of Pharmacy at The University of Utah. earned his PharmD from University of Wisconsin-Madison and PhD from University of Washington. His expertise is in Health Technology Assessment. He applied his methods in health economics, real world data analysis, and evidence synthesis to support national and global policy, especially his contributions to the World Health Organization and Centers for Disease Control. His current research works have been focused on health economics and health equity. He is a co-author of CHEERS 2022 (Consolidated Health Economic Evaluation Reporting Standards Statement) and WHO guide for standardization of economic evaluations of immunization programmes, 2nd edition. Dr.Chaiyakunapruk has an H-index of 55 and is an author of more than 300 international publications in peer-reviewed journals.

Michael Drummond, PhD

University of York, Lichfield, Staffordshire, United Kingdom

Michael Drummond, BSc, MCom, DPhil is professor of Health Economics and former Director of the Centre for Health Economics at the University of York. His particular field of interest is in the economic evaluation of health care treatments and programmes. He has undertaken evaluations in a wide range of medical fields including care of the elderly, neonatal intensive care, immunization programmes, services for people with AIDS, eye health care and pharmaceuticals. He is the author of two major textbooks and more than 700 scientific papers, and has acted as a consultant to the World Health Organization and the European Union. He has been President of the International Society of Technology Assessment in Health Care, and the International Society for Pharmacoeconomics and Outcomes Research. In October 2010 he was made a member of the National Academy of Medicine in the USA. He has advised several governments on the assessment of health technologies and chaired one of the Guideline Review Panels for the National Institute for Health and Care Excellence (NICE) in the UK. He is currently Co-Editor-in-Chief of Value in Health and has been awarded 3 honorary doctorates, from City University (London), Erasmus University (Rotterdam) and the University of Lisbon.

Budget Impact Analysis II: Applications and Design IssuesLevel: IntermediateTrack: Economic Evaluation

Separate registration required.

This course covers the concrete application of the 6-step approach for developing budget impact analyses and provides hands-on learning with two different budget impact models programmed in Excel. The course will review the basics of budget impact analysis, interpretation of results, simplicity versus accuracy and face validity, and how budget impact analyses are used by payers and other decision makers. Technical topics will include static versus dynamic budget impact models, considerations for device and diagnostic technologies, and realistic features such as patient copayments and use of generics. The instructors will walk through 2 different budget impact analyses programmed in Excel (one static and one dynamic) and work with participants during hands-on exercises to enhance these models. The instructors will also review good practices for building budget impact models and provide a number of Excel tips. The Excel-based budget impact models used for the course will be provided to participants in advance of the presentation. This course is designed for those who have basic knowledge of budget impact analyses and desire exposure to these analyses in Excel. Participants who wish to gain hands-on experience must have Microsoft Excel for Windows installed on their computers.

Faculty Member

Thor-Henrik Brodtkorb, PhD

RTI Health Solutions, Ljungskile, O, Sweden

Anita Brogan, PhD, MSc

RTI Health Solutions, San Diego, CA, USA

Anita Brogan is vice president of Decision Analytic Modeling within the Health Economics division at RTI Health Solutions (RTI-HS). She holds a PhD in Operations Research from the University of North Carolina and has been with RTI-HS for 20 years. 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). Dr. Brogan has held an adjunct professorship in the Fermanian School of Business at Point Loma Nazarene University. She is also a co-author of the book “Budget-Impact Analysis of Health Care Interventions: A Practical Guide.” In her role at RTI-HS, Dr. Brogan uses analytical techniques to assess and present the health and economic impact of emerging pharmaceutical and biotechnology interventions. She leads development of 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 procedures, including Markov and other stochastic 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, Ebola, influenza, cystic fibrosis, bone health, mental health, women’s health, oncology, osteoporosis, 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.

Ashley Davis, PhD, MSc

RTI Health Solutions, Research Triangle Park, NC, USA

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.

Stephanie Earnshaw, PhD, MS

RTI Health Solutions, Pittsboro, NC, USA

Unveiling the EU-HTA Regulation: A Deep Dive Into the Joint Clinical Assessment (JCA)Level: IntermediateTrack: Health Policy & Regulatory

Separate registration required.

In January 2022, a significant milestone was reached in the field of Health Technology Assessment (HTA) with the enforcement of the EU-HTA regulation. This regulation aims to harmonize the HTA process across the EU and improve efficiency by reducing duplication of efforts for national HTA authorities. Replacing the existing voluntary network of national HTA agencies and the EU-funded Joint Actions (EUnetHTA), the EU-HTA regulation introduces a permanent framework for collaborative work. To this end, it covers horizon scanning, joint scientific consultations, joint clinical assessments, and voluntary cooperation on non-clinical aspects of HTA which remains a national responsibility. From 2025 onwards, the regulation will be gradually implemented, starting with cancer treatments and advanced therapy medicinal products (ATMPs), followed by orphan drugs in 2028 and all other drugs in 2030. In this interactive course, we will discuss the methodological deliverables, procedural guidelines and templates produced by EUnetHTA 21, a consortium of EU-HTA agencies in charge of the key deliverables. We will focus on the latest developments around the joint clinical assessment, aiming to produce one single assessment of the relative clinical benefit of the new drug that is the basis for all EU member states. This assessment starts with a survey among the member states asking for the patient/population, intervention, comparison and outcomes (PICOs) they need. The course will also address the challenges associated with the position of the joint clinical assessment alongside the EMA assessment and the national market access processes, and the involvement of manufacturers and patient representatives.

In the final segment of this course, we will examine the potential implications and future prospects of the EU-HTA regulation. We will discuss how this regulation could potentially reshape the landscape of HTA in the EU, and what this means for stakeholders, including healthcare providers, patients, and pharmaceutical companies. We will also consider the potential challenges and opportunities that may arise as the regulation is progressively implemented. This will include a discussion on how to navigate the transition period and how to prepare for the full implementation of the regulation.

To ensure a practical understanding of these concepts, we will divide the classroom into smaller groups for a portion of the course. These groups will work on a practical exercise involving a hypothetical cell or gene therapy, using evidence from single-arm studies. By the end of this course, participants will have gained a comprehensive understanding of the EU-HTA regulation and will be equipped with the knowledge and tools to navigate this new era of health technology assessment in the EU. Join us as we unravel the complexities of the EU-HTA regulation and its impact on the future of HTA in the EU.

PREREQUISTE: Participants who wish to gain hands-on experience are required to bring their laptops.

Faculty Member

Karin Becker, MSc, PhD

Boehringer Ingelheim GmbH, Ingelheim, Germany

Maureen Rutten-van Mölken, PhD

Erasmus University Rotterdam, Erasmus School of Health Policy and Management (ESHPM) and Institute for Medical Technology Assessment (IMTA), Rotterdam, Netherlands

Maureen Rutten-van Mölken is full professor of Economic Evaluation of Innovations for Health at the Erasmus School of Health Policy & Management, where she is head of the Health Technology Assessment department. She is also scientific director of the Institute for Medical Technology Assessment, a company fully owned by the Erasmus University Holding. She holds an MSc in health sciences and a PhD in health economics, both from the University of Maastricht. She teaches Health Technology Assessment and Pharmaceutical Pricing and Market Access in the Master-program Health Economics Policy and Law and in the European Master in Health Economics and Management.Her expertise includes cost-effectiveness analysis alongside clinical trials and observational studies, probabilistic decision analytic modeling, health economic outcomes research and innovative payment models. She worked in many disease areas, including respiratory diseases (COPD, asthma), rheumatology, diabetes, cardiovascular disease, and Pompe disease. She has a special interest in the cost-effectiveness, and financing and payment of complex multi-faceted interventions that involve system-level changes (e.g., integrated care programs, disease management programs, hospital at home programs, outpatient rehabilitation programs, remote patient monitoring). She also has an interest in the health economics of personalized and precision medicine. She was the coordinator of SELFIE, a Horizon2020 project on multi-criteria decision analysis of integrated care programmes for patients with multi-morbidity. She was a principal investigator in Horizon2020 project HEcoPerMed that developed guidance on health economic modelling of personalised medicine and applied this guidance to various pharmacogenetic interventions. She also coordinates the Medical Delta program From Prototype to Payment.

Christophe Sauboin, MSc

Boehringer Ingelheim GmbH, Ingelheim, Germany

Frederick Thielen, PhD

Erasmus University Rotterdam, Erasmus School of Health Policy and Management (ESHPM), Rotterdam, Netherlands

Causal Inference and Causal Diagrams in Big, Real-World Observational Data and Pragmatic TrialsLevel: ExperiencedTrack: Real World Data & Information Systems

Separate registration required.

Innovative causal inference methods are needed for the design and analysis of big real-world observational data and pragmatic trials used for outcomes research and health technology assessment. 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 “cloning – censoring – weighting” 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 consists of lectures, practical training exercises, case examples drawn from the published literature which will be used to comprehend the use of causal inference in health technology assessment bodies (eg, NICE , IQWiG), and an interactive discussion with Q&A. The intended audience includes all stakeholders in medical and public health decision making and healthcare, and researchers from all substance matter fields, statisticians, epidemiologists, outcome researchers, health economists, modelers and health policy decision makers interested either in methods of causal analysis or causal interpretation of results based on the underlying method. Course material includes all session handouts, exercises with solutions, a comprehensive background reading library, and software recommendations.

PREREQUISITE: Students are expected to have a basic knowledge in epidemiologic studies and methods (including the concept of confounding).

Faculty Member

Douglas E. Faries, PhD

Eli Lilly and Company, Indianapolis, IN, USA

Doug Faries graduated from Oklahoma State University with a PhD in Statistics in 1990 and joined Eli Lilly and Company later that year. Doug’s early research interests included development and implementation of novel clinical trial designs to improve and accelerate decision making for drug development and neuroscience clinical trials. Over the past 15 years, Doug has focused his research interests on statistical methodology for real world data. Specific research interests include causal inference, unmeasured confounding, and use of real world data for personalized medicine. Currently, Doug is a research fellow at Eli Lilly, leading the Real World Analytics team. In this role, Doug is involved with the design and analysis of observational research including comparative effectiveness analyses and the development of real world analytical capabilities. He has authored or co-authored over 100 peer-reviewed manuscripts, edited a textbook “Analysis of Observational Healthcare Data Using SAS”, and is active in the statistical community as a publication reviewer, speaker, workshop organizer, in industry working groups, and teaching short courses.

Felicitas Kuehne, MSc

Pfizer Pharma GmbH, Berlin, 0, Germany

Felicitas Kuehne is an outcomes research manager at Pfizer Pharma GmbH in Germany. She is conducting epidemiological, economic, and health service research using real-world data as well as decision modelling studies. Further, Felicitas is a senior scientist in decision-analytic modeling and epidemiology at the Department of Public Health, Health Services Research and Health Technology Assessment at UMIT in Hall i.T., Austria. She is leading the Program on Causal Inference in Science and is the Coordinator of the HTADS course “Causal Inference for Assessing Effectiveness in Real World Data and Clinical Trials: A Practical Hands-on Workshop”. At the Institute, she conducts decision-analytics as well as epidemiological studies in several disease areas and teaches epidemiology classes at several universities in Europe as well as at international conferences. Felicitas completed her Master of Science in Health Policy and Management at the Harvard School of Public Health in 2001. From 2001 to 2011 she worked as a consultant for pharmaceutical companies, conducting several cost-effectiveness analyses in a variety of disease areas. She joined UMIT in 2011 and Pfizer Pharma in 2022. Her research interests include evaluating public health intervention by applying evidence-based quantitative methods from epidemiology, comparative effectiveness research, health services and outcomes research, economic evaluation, and decision sciences. Her current substantive research focuses on identifying synergies of causal inference and decision science. The main disease areas are pneumococcal disease, cardiovascular diseases, cancer, and infectious diseases including HIV/AIDS and hepatitis C. Her studies at Harvard were partly sponsored by complementary scholarships of the Carl Duisberg Gesellschaft (1 year) and the Boehringer Ingelheim Stiftung (2 years). In 2013, Felicitas received with her team the third German research award for general medicine of the Dr. Lothar Beyer Foundation with a shared decision-making project in the cardiovascular disease area. Felicitas Kuehne was awarded three Tyrolean Science Fund (TWF) grants in 2016, 2020 and 2022 for causal inference projects.

Uwe Siebert, MD, MPH, MSc, ScD

ISPOR Europe 2023

12 - 15 November

Short Courses

All short courses require a separate registration fee.

ISPOR–The Professional Society for
Health Economics and Outcomes Research