Program

* Program subject to change

Sun May 77:00 AM - 5:00 PMISPOR 2023 Registration Hours8:00 AM - 12:00 PMShort Course Morning SessionsDeveloping Decision-Grade Real-World EvidenceLevel: IntermediateTrack: Real World Data & Information Systems

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

Jeremy Rassen, ScD

Aetion, Inc., New York, NY, USA

Jeremy A. Rassen, MS, ScD is a pharmacoepidemiologist with 25 years of academic and industry experience. He is co-founder and president at Aetion, a healthcare technology company that delivers real-world evidence for life sciences companies, payers, and regulatory agencies. Prior to founding Aetion, Dr. Rassen was Assistant Professor of Medicine at Harvard Medical School, where he focused on methods to improve the quality and validity of real-world data studies. He also worked in Silicon Valley in a variety of tech companies. Dr. Rassen received his bachelor’s degree in Computer Science from Harvard College and his master’s and doctorate degrees in Epidemiology from the Harvard T.H. Chan School of Public Health.

Sebastian Schneeweiss, MD, ScD

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

Sebastian Schneeweiss, MD, ScD, is a Professor of Medicine and Epidemiology at Harvard Medical School and Chief of the Division of Pharmacoepidemiology, Department of Medicine, Brigham and Women’s Hospital. His research focuses on assessing the effectiveness and safety of biopharmaceuticals in clinical practice. He has developed analytic methods to improve the accuracy of estimating causal treatment effects of new drugs using complex digital healthcare databases. His work is published in >500 articles and is used for regulatory and coverage decision making around the globe. He is funded by NIH, PCORI, IMI, and FDA where he is also a voting consultant. He is Principal Investigator of the FDA Sentinel Innovation Center and co-leads the RCT-DUPLICATE initiative to understand when and how real-world evidence studies can reach causal conclusions.

Introduction to the Design & Database Analysis of Observational Studies of Treatment Effects Using Retrospective Data SourcesLevel: IntroductoryTrack: Study Approaches

Retrospective studies require strong principles of epidemiologic study design and complex analytical methods to adjust for bias and confounding. This course will provide an overview of the structures of commonly encountered retrospective data sources with a focus on large administrative data, as well as highlight design and measurement issues investigators face when developing a protocol using retrospective observational data. Approaches to measure and control for patient mix, including patient comorbidity and the use of restriction and stratification, will be presented. Linear multivariable regression, logistic regression, and propensity scoring analytic techniques will be presented and include examples using SAS code that can later be used by participants. This course is an introductory course designed to prepare participants to take intermediate and advanced observational research courses.

Faculty Member

Benjamin M. Craig, PhD

University of South Florida, Tampa, FL, USA

Benjamin M. Craig, PhD, is an associate professor of Economics at the University of South Florida. He received his MS in Economics at the University of Texas at Austin in 1999 and his PhD in Population Health from the University of Wisconsin in 2003. Trained as an econometrician, his research focuses on health preference research and the economics of cancer prevention, detection, and control. He is an active member of the International Society for Pharmacoeconomics and Outcomes Research (ISPOR), the International Society for Quality of Life Research (ISOQOL), the International Academy of Health Preference Research (IAHPR), and the EuroQol Group.

Bradley Martin, PharmD, RPh, PhD

University of Arkansas for Medical Sciences, Little Rock, AR, USA

Dr. Bradley Martin is currently professor and was the founding head of the Pharmaceutical Evaluation and Policy (PEP) Division at the University of Arkansas for Medical Sciences College of Pharmacy. The Pharmaceutical Evaluation and Policy Division offers graduate and professional instruction and conducts research in pharmacoeconomics, patient reported outcomes, pharmaceutical economics, and large health claims data base analysis. Dr. Martin received his PharmD from the University of Illinois and earned his PhD in Pharmacy Care Administration from the University of Georgia. Dr. Martin’s research efforts have focused on conducting retrospective observational comparative effectiveness and economic analyses using large administrative data sets and national health surveys. He conducts policy analyses, and develops cost effectiveness models and has contributed to the understanding of the opioid epidemic. Dr. Martin has over 90 peer-reviewed manuscripts published, which have been collectively cited over 4000 times, and his work has been funded by NIH, AHRQ, VA, and a variety of research foundations as well as partnerships with the pharmaceutical industry. Dr. Martin is contributing to national policy research on opioids and health care financing and has recently lead an international effort to improve the conduct and reporting of CER observational research organized by three national associations: ISPOR, NPC, AMCP.

Elements of Pharmaceutical/Biotech PricingLevel: IntroductoryTrack: Health Policy & Regulatory

This course will give participants a basic understanding of the key terminology and issues involved in pharmaceutical pricing decisions. It will cover the tools to build and document product value including issues, information and processes employed (including pricing research), the role of pharmacoeconomics, and the differences in payment systems that help to shape pricing decisions. These tools will be further explored through a series of interactive exercises. This course is designed for those with limited experience in the area of pharmaceutical pricing and covers topics within a global context.

PREREQUISITE: Attendance at this course or equivalent knowledge is a prerequisite to attending the course "Case Studies in Pharmaceutical/Biotech Pricing II" at ISPOR 2023.

Faculty Member

Jack M. Mycka

MME, an Indegene PRMA Business, Montclair, NJ, USA

As Vice President of the PRMA & Emerging Biotech Commercialization division at Indegene, Jack provides critical global support for strategic marketing and pricing decisions to clients in the biotech and pharmaceutical industries. As a recognized expert consultant since 2001, he has successfully completed engagements encompassing many product classes and therapeutic areas centered on value and its interaction with pricing, payers, reimbursement, and marketing in general at both MME and predecessor organizations. During his tenure at Roche Laboratories Inc., Jack established that company’s Pharmaceutical Pricing and Contracting Department. As the director of this group, he successfully increased the size and scope of the group’s activities dramatically to cover a multitude of strategic, tactical, and operational issues involving pricing, reimbursement, and discounting in both the US and other major global markets. Market segments covered globally include market access/managed care, biologics, hospital, oncology, government, as well as emerging pricing and reimbursement issues. Previously, Jack spent ten years as a commercial banker in corporate lending, managing relationships for customers ranging in size from multibillion-dollar organizations to entrepreneurial firms and not-for-profit organizations. Jack received a BS in Finance from Lehigh University.

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

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.

Faculty Member

Devin Incerti, PhD

EntityRisk, Inc., San Francisco, CA, USA

Jeroen Jansen, PhD

PRECISIONheor and University of California, San Francisco, CA, USA

A Health Economics Approach to US Value Assessment FrameworksLevel: IntroductoryTrack: Health Technology Assessment

This short course will focus on the recent ISPOR Special Task Force Report, “A Health Economics Approach to US Value Frameworks.” It will begin with an overview of recent US value assessment frameworks, with emphasis on the importance of perspective and decision context in the construction and use of value frameworks. It will then review how a health economics approach from a societal or health plan perspective leads to use of cost-effectiveness analysis (CEA) to help guide efficient resource allocation.

There will be in-depth discussion of how measuring some aspects of the value of health benefits could augment the standard cost-per-quality-adjusted-life-year metric for CEA. Elements such as value of insurance, value of “hope,” real option value, severity of illness, and several others, have the potential to better capture how patients and/or society value the benefits of some treatments; each one is based on some research findings and some case examples will be shown.

The course will then review how budget considerations, cost-effectiveness thresholds, and opportunity costs enter CEA-based decision-making. Next faculty will review broader approaches to cost-benefit aggregation and value-based decision-making, including extended CEA, augmented CEA (introduced by this Report), and multi-criteria decision analysis (MCDA), with an overview of issues and new approaches to MCDA. It then discusses the strengths and weaknesses of recent US value assessment frameworks from this health economic perspective and closes with a review of the high-level recommendations of this Special Task Force.

Faculty Member

Lou Garrison, PhD

CHOICE 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. Prior to this, he has worked in non-profit policy research (13 years) and the pharmaceutical industry (12 years). Dr. Garrison received a PhD in Economics from Stanford University. He has more than 180 peer-reviewed publications. His research interests include a wide range of national and international health policy issues. Dr. Garrison was elected as ISPOR President for 2016-2017. He is currently serving as co-chair of ISPOR’s Policy Outlook Committee for the Health Science Policy Council.

Charles Phelps, MBA, PhD

University of Rochester, Rochester, NY, USA

Charles E Phelps, PhD, a health economist, has developed key models of cost-effectiveness analysis that provide the intellectual foundations for its practice. He was given the Victor R Fuchs Award for Lifetime Achievement in the Field of Health Economics in 2019, and has been a member of the National Academy of Medicine since 1991. His leading textbook, Health Economics is now in its 6th Edition. His recent interests have expanded to the use of multi-criteria decision analysis (MCDA), particularly in its proper use when the “decision-maker” is a group.

Richard Willke, PhD

ISPOR, Lawrenceville, NJ, USA

Dick became ISPOR’s first chief science officer in April 2016, following nearly 25 years in the pharmaceutical industry with Pfizer and its legacy companies. In his CSO role at ISPOR, Dick’s responsibilities are to develop, lead, support, and direct strategic initiatives related to research, scientific, and content priorities to accomplish the organization’s mission to promote health economics and outcomes research excellence to improve decision making for health globally. While with Pfizer, his final position was Vice President, Outcomes & Evidence, lead for Cardiovascular /Metabolic, Inflammation & Immunology, the last in a succession of HEOR group lead roles. He received a PhD in economics from Johns Hopkins University in 1982, concentrating in econometrics and labor economics. Prior to joining Pfizer’s legacy company Upjohn in 1991, he was a member of the economics faculty at Ohio State University as well as a senior economist at the American Medical Association Center for Health Policy Research. Dick has served on the ISPOR Board of Directors (2007-09), was chair of the ISPOR Institutional Council in 2010, and was co-chair of the ISPOR Good Research Practices Task Force on Cost-Effectiveness Analysis in Randomized Clinical Trials in 2003-2005 as well as its 2014-15 reprise to revise and update that Report. He has co-taught many ISPOR short courses on this topic as well as on “Transferability of Cost-Effectiveness Data between Countries.” He was also a member of the Health Outcomes Committee of PhRMA from 1998-2009, having been its chair from 2002-2004. He has served as a co-editor for Value in Health, on the editorial board for Farmeconomia, on AHRQ, NIH, and PCORI project review study sections, and is a member of the Ohio State University Economics Advisory Board. Prior to joining industry, Dr Willke served as department director in the Center of Health Policy Research at the American Medical Association and held research and teaching positions at The Ohio State University. Dr Willke earned a PhD and MA in economics from Johns Hopkins University. He has authored more than 80 scholarly publications that examine the science and methodologies of health economics and outcomes research.

The Delphi Panel—From Discord to Actionable HEOR InsightsLevel: IntroductoryTrack: Study Approaches

Delphi Panels, originally developed by The RAND Corporation in the 1950s, have recently been used by health economics and outcomes research (HEOR) professionals in situations where unanticipated questions arise, and information is needed quickly. This methodology is beneficial when real-world evidence may not be available or easily assembled; or in situations where there a lack of expert consensus regarding definitions, health care resource utilization (HCRU), or diagnostic or treatment guidelines. Delphi Panels provide actionable HEOR insights without requiring the lengthy timeline of some traditional study methodologies.

Faculty Member

Meghan Hufstader Gabriel, PhD

RTI Health Solutions, Research Triangle Park, NC, USA

Anna Hundt Golden, PhD

RTI Health Solutions, Research Triangle Park, NC, USA

Mark Price, MS

RTI Health Solutions, Research Triangle Park, NC, USA

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.

John D. Seeger, PharmD, DrPH

Optum, Boston, MA, USA

Dr. John Seeger is a pharmacoepidemiologist and chief scientific officer at Optum Epidemiology. He is also adjunct assistant professor in Epidemiology at the Harvard School of Public Health. Dr. Seeger has conducted dozens of studies that have addressed regulatory drug safety issues across a wide range of drugs and disease conditions. Most of this work has involved the use of health insurance claims databases as platforms for pharmacoepidemiology, so Dr. Seeger's methodological expertise focuses on research issues encountered in such settings. He has worked extensively with propensity scores and related methods that mitigate confounding by collapsing covariates. Additionally, he is a co-instructor in courses on propensity scores and is the past president of the International Society for Pharmacoepidemiology (ISPE).

Introduction to Patient-Reported Outcomes Assessment: Instrument Development & EvaluationLevel: IntroductoryTrack: Patient-Centered Research

Patient-reported outcome (PRO) measures are used to quantify the impact of interventions from the patients' perspective. This course is designed to familiarize participants with the range and scope of what PRO measures are used for, how they are developed and evaluated, what they measure, and how PRO data can be used in clinical trial, or clinical care applications. We will discuss the properties of a good PRO measure. Participants will be able to identify steps researchers generally go through to develop and test a new PRO measure, including item generation, qualitative cognitive testing, and quantitative psychometric evaluation.

This is an entry level course which assumes only a passing familiarity with patient-reported outcomes.

Faculty Member

Christina K Zigler, PhD, MSEd

Duke University School of Medicine, Durham, NC, USA

8:00 AM - 5:00 PMFull Day Short CourseIntroduction to Health Economics and Outcomes ResearchLevel: IntroductoryTrack: Economic Evaluation

This course is designed to teach clinicians and new researchers how to incorporate health economics into study design and data analysis. Participants will first review the basic principles and concepts of health economic evaluations, then discuss how to collect and calculate the costs of different alternatives, determine the economic impact of clinical outcomes, and how to identify, track, and assign costs to different types of healthcare resources used. Different health economic models and techniques will be demonstrated including cost-minimization, cost-effectiveness, cost-benefit, cost-utility, and budget impact analysis. Decision analysis, sensitivity analysis, and discounting will all be demonstrated and practiced.

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

Faculty Member

Lorne E. Basskin, PharmD

Strategic Economics Ltd., Cary, NC, USA

Lorne Basskin received his Bachelor's degree in business at the University of Toronto and worked as an accountant with a national firm and subsequently developed his own consulting business. He later received his PharmD from the University of the Pacific and completed a post-doctoral residency with Valley Medical Center in Seattle in 1995. Dr. Basskin went on to serve as an Associate Professor in Clinical Practice at two different schools of pharmacy in the United States, and was the Director of Post-Graduate and Continuing Education there for seven years. In 2002, Dr. Basskin started his own Medical Education firm, specializing in education for pharmacists and other health care professionals. From 2005 to 2011 he held various positions with HealthSouth Corporation, a for-profit group of 100 rehabilitation and long-term acute care hospitals. Most recently he served as their National Director of Pharmacy Clinical and Information Services and was involved in implementing the Cerner system of electronic medical records throughout the network. After a two year period with Wingate University College of Pharmacy as their Regional Dean, he moved to Asheville, NC, where he carries on a consulting practice specializing in education about health care technology and outcomes research. Dr. Basskin has written and spoken extensively on the topics of Pharmacoeconomics and Outcomes Research, and published a book on the topic in 1998. He has over 40 peer-reviewed publications and has made over 120 presentations on both clinical and research related matters. He is on the Editorial Board of several National Pharmacy and Medical publications and serves as a peer reviewer for several professional organizations. He has written continuing education programs including that of diabetes, asthma, and Medicare reimbursement. Additionally, he has conducted over 100 one and two day workshops on the meaning and use of pharmacoeconomics for health care decision makers and health care researchers.

12:00 PM - 1:00 PMBreakLunch on own.1:00 PM - 5:00 PMShort Course Afternoon SessionsCase Studies in Pharmaceutical/Biotech Pricing IILevel: IntermediateTrack: Health Policy & Regulatory

Case studies will be employed to lead participants through the key steps of new product pricing, with focus on the need to thoroughly analyze the business environment and its constraints and opportunities, and the need to closely integrate the pricing, reimbursement, and pharmacoeconomic strategy for the new product with the clinical development and marketing strategies. Practical exercises will allow participants to consolidate the concepts delivered in the “Elements” introductory session and expanded here. Areas covered will include the post-launch issues of reimbursement and pricing maintenance as a part of life-cycle management in a global environment.

This course is designed for those with limited experience in the area of pharmaceutical pricing and covers topics within a global context.

PREREQUISITE: Attendance at "Elements of Pharmaceutical/Biotech Pricing" at ISPOR 2023 or equivalent knowledge is a prerequisite to attending this course.

Faculty Member

Jack M. Mycka

MME, an Indegene PRMA Business, Montclair, NJ, USA

Benefit-Risk Assessment in Medical Product DevelopmentLevel: IntermediateTrack: Study Approaches

Quantitative assessments of benefits and harms of medical products can inform drug and device developers, regulators, health technology assessors, and other health professionals to make better health-related decisions. Quantitative benefit-risk assessment differs from qualitative assessments by incorporating explicit outcome weighting into the analysis. This course will introduce multi-criteria decision analysis (MCDA) based methods for quantitative benefit-risk assessment with real-life examples. We will describe the history and go through emerging good research practices of benefit-risk assessment, including how patient preference data can be incorporated. The course will explain step by step how to develop quantitative benefit-risk model with a case study. This course is based on the principles of the ISPOR Benefit Risk Assessment Emerging Good Practices Task Force Report.

Faculty Member

Martin Ho, MS

Biostatistician, San Francisco, CA, USA

Tommi Tervonen, PhD

Kielo Research, Zug, ZG, Switzerland

Dr Tervonen is the Chief Scientist of Kielo Research and key opinion leader in patient preferences and benefit-risk assessment. His expertise influences decision maker opinion and he has been consulted by agencies such as the US Food and Drug Administration (FDA) and UK National Institute of Health and Care Excellence (NICE). Dr Tervonen co-chairs the ISPOR Task Force on Good Practice in Quantitative Benefit-Risk Assessment and has served as principal investigator in dozens of patient preference studies, including an IMI PREFER industry case study, and studies used in regulatory filings.

Core Concepts and Approaches to Early-Stage Health Technology AssessmentLevel: IntroductoryTrack: Health Technology Assessment

As the cost of bringing a new health technology to market continues to climb, more and more firms, developers, and investors are searching for tools to prioritize their efforts on the technologies with the greatest potential for clinical impact and market viability. While health economic analysis has long been established as a necessity to inform decision making for market access and reimbursement, it is increasingly being used at earlier stages of product development for healthcare and life sciences to increase the access rate of R&E and efficiently prioritize data collection. The number of available methods for this field has continued to expand.

This course aims to demystify the objectives of early-stage health technology assessment and the methods of translational health economics. Students in the course will gain a thorough understanding of available methods for early-stage technology assessment, the specific challenges and solutions, and a clear sense of how to implement this in the complexity of health technology development, funding, regulation, pricing, and reimbursement. The course will utilize real-world examples and students will have the opportunity to strategize about the creation of a research plan for their purposes.

PREREQUISITE: Attendance at "Introduction to HTA" or equivalent knowledge is a prerequisite to attending this course.

Faculty Member

William Canestaro, PhD, MSc

Washington Research Foundation, Seattle, WA, USA

Erik Landaas, PhD, MPH

Cook Medical, Ponte Vedra, FL, USA

Lotte Steuten, PhD

Office of Health Economics, London, United Kingdom

Risk-Sharing/Performance-Based Arrangements for Drugs and Other Medical ProductsLevel: IntermediateTrack: Health Policy & Regulatory

During the recent years, Managed Entry Agreements (MEAs) have become instrumental in ensuring the access of the innovative medicines. This course is designed for health care 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 Central-Eastern European 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 in CEE countries. 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

Josh J. Carlson, MPH, PhD

University of Washington, Seattle, WA, USA

Dr. Carlson is a Professor in the The Comparative Health Outcomes, Policy, and Economics (CHOICE) Institute in the School of Pharmacy at the University of Washington and an affiliate faculty member at the Fred Hutchinson Cancer Research Center. He graduated with his PhD from the Institute for Public Health Genetics in the School of Public Health and Community Medicine at the University of Washington in 2007 and conducted his postdoctoral training in health economics and outcomes research in the Pharmaceutical Outcomes Research and Policy Program (now the CHOICE Institute) at the University of Washington from 2007-2009. He was awarded the ISPOR Bernie J. O’Brien new investigator award in 2014. Dr. Carlson’s research seeks to inform healthcare decision making using economic modeling, evidence synthesis, preference assessment, and health policy evaluation. This work spans many diseases, topics, and methodologies, but specific focus areas include economic analysis, precision medicine, and performance-based risk sharing arrangements. He has diverse formal training in decision modeling, discrete choice experiments, comparative effectiveness, outcomes research, and public health genetics.

Lou Garrison, PhD

CHOICE Institute, School of Pharmacy, University of Washington, Seattle, WA, USA

Adrian Towse, MA, MPhil

Office of Health Economics, London, United Kingdom

Professor Adrian Towse is director emeritus and senior research fellow of the Office of Health Economics in the UK. Adrian’s current research includes incentives for new drugs and vaccines to tackle Antimicrobial Resistance, the use of 'risk-sharing' arrangements between healthcare payers and pharmaceutical companies, including value-based pricing approaches; the economics of pharmacogenetics for healthcare payers and the pharmaceutical industry; economic issues that affect both R&D for and access to treatments for diseases prevalent in the developing world; the economics of medical negligence; and measuring productivity in healthcare. A visiting professor at the London School of Economics and a senior researcher at the Nuffield Department of Population Health at the University of Oxford, Adrian also has been a visiting professor at the University of York. For ten years, he served as the non-executive director of the Oxford Radcliffe Hospitals NHS Trust, one of the UK’s largest hospitals. Adrian was president of ISPOR, for the 2014-15 term. Adrian joined the OHE in 1993 and served as director for 25 years. He holds an MA (Hons) in Politics, Philosophy and Economics from Keble College, Oxford; an MPhil in Management Studies from Nuffield College, Oxford, and the Oxford Centre for Management Studies; and is a member of the Chartered Institute of Management Accountants.

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

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

Jeroen Jansen, PhD

PRECISIONheor and University of California, San Francisco, CA, USA

Advanced Decision Modeling for Health Economic EvaluationsLevel: ExperiencedTrack: Methodological & Statistical Research

During this course, the key aspects and new developments of decision modeling for economic analysis will be considered. In particular, we will explore how the limitations of Markov models can be overcome using various modelling techniques including different options for introducing time-dependency into state transition models. How models can be made probabilistic to capture parameter uncertainty (including rationale, choosing parameter distributions, and types of uncertainty) will be covered. A taxonomy of modelling types will place the techniques described in this course within the broader universe of modelling methods. Participants should have an understanding of decision analysis.

PREREQUISITE: Attendance at "Pharmacoeconomic Modeling-Applications" (6-7 June) or equivalent knowledge is a prerequisite to attending this course.

Faculty Member

Andrew Briggs, DPhil

Avalon Health Economics, Morristown, NJ, USA

Andrew Briggs, DPhil, has extensive experience conducting economic evaluation analyses globally, and developing cost-effectiveness models across health systems. Andrew has a DPhil in Health Economics and MSc in Applied Statistics, both from the University of Oxford. He currently holds the William R Lindsay Chair of Health Economics at the University of Glasgow and has acted as Advisor to the UK Department of Health, the UK National Institute of Health & Care Excellence (NICE), and a number of pharmaceutical companies. He has published extensively on the topic of cost-effectiveness analysis and economic evaluation with over 200 publications in the peer-reviewed literature. He has served on numerous committees on economic evaluation methodology and reporting, including five ISPOR Task Forces. He is an Editor at the journal Health Economics, and has previously served on the editorial boards of Value in Health and Medical Decision Making. He is also lead author of the widely cited book Decision Modelling for Health Economic Evaluation (with Karl Claxton and Mark Sculpher; Oxford University Press 2006). Following a sabbatical at Center for Health Policy & Outcomes, Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center (MSKCC), with Dr. Peter Bach, Andrew continues to work half-time at MSKCC as a Visiting Investigator.

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 ha

ISPOR 2023

May 7-10, 2023

Program