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.
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.
Charles Phelps, PhD
University of Rochester, Pittsford, 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, In 2023, he received ISPOR's Avedis Donabedian Lifetime Acheivement Award. He 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 include the use of multi-criteria decision analysis (MCDA), particularly in its proper use when the “decision-maker” is a group, and development of the Generalized Risk Adjusted Cost-Effectiveness (GRACE) methodology for valuing health gains.
Richard Willke, PhD
The International Society for Pharmacoeconomics and Outcomes Research, Lawrenceville, NJ, USA
Dick is currently Senior Scientific Advisor and Chief Science Officer (CSO) Emeritus for ISPOR, after becoming the first CSO for ISPOR in 2016 and serving in that role until mid-2023. Dick’s responsibilities have been to develop, lead, and support strategic initiatives related to research, scientific, and content priorities. Prior to joining ISPOR he was employed for 25 years in the pharmaceutical industry with Pfizer and its legacy companies, where he retired as a vice president in the HEOR group. He received a Ph.D. in economics from Johns Hopkins University, has been a member of the economics faculty at Ohio State University (OSU), and senior economist at the American Medical Association. He has served as a co-editor for Value in Health, on AHRQ, NIH, and PCORI project review study sections, is past chair of the OSU Economics Advisory Board, and has over 100 scholarly publications.
Separate registration required.
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 Jenny Lo-Ciganic, PhD, MSPharm, MS
Health Research Scientist Geriatric Research Education and Clinical Center (GRECC), 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.
Introduction to Health Technology Assessment
Level: Introductory
Track: 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
Uwe Siebert, MD, MPH, MSc, ScD
UMIT - University for Health Sciences Medical Informatics and Technology Hall in Tirol, Austria and Harvard Chan School of Public Health Harvard University, Boston, MA, USA
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.
Developing Decision-Grade Real-World Evidence
Level: Intermediate
Track: 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
Jessica M. Franklin, PhD
Optum, Boston, MA, USA
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, president, and chief technology officer at Aetion, a healthcare technology company that delivers real-world evidence for life sciences companies, payers, and regulatory agencies. Prior to founding Aetion, Dr. Rassen was assistant professor of medicine at Harvard Medical School, where he focused on methods to improve the quality and validity of real-world data studies. He also worked in Silicon Valley in a variety of tech companies. Dr. Rassen received his bachelor’s degree in computer science from Harvard College and his master’s and doctorate degrees in Epidemiology from the Harvard T.H. Chan School of Public Health.
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.
1:00 PM - 5:00 PM
Short Course Afternoon Sessions
Handling Uncertainty in Health Technology Assessment Processes
Level: Intermediate
Track: Health Technology Assessment
Separate registration required.
Due to scarce resources, decisions must be made regarding which interventions to reimburse in the healthcare sector. In many countries, model-based economic evaluations are used as part of the Health Technology Assessment (HTA) process to systematically assess the magnitude and tradeoffs of the expected health effects and costs of decision options considered. Such assessment is based on incomplete information, often resulting in uncertainty, which in the extreme can result in suboptimal decision making. Consequently, an economic evaluation for HTA purposes should be performed using a coherent framework to properly structure the decision-making process and should carefully assess the uncertainty surrounding the expected outcomes and the decision being addressed. This course will provide participants with 1) a taxonomy of the types of uncertainty that should be considered when preparing and assessing economic evaluations for HTA purposes; 2) a more in-depth understanding of different methods to appropriately assess the underlying uncertainty and make more informed decisions based on economic evaluations; and 3) guidance on how to report uncertainty using the latest ISPOR good-practice guidelines. Further, the participants will practice with several of these methods and interpretation of their results in hands-on exercises.
PREREQUISITE: This course requires familiarity with basic economic evaluation and HTA concepts and methodologies.
Faculty Member
Elisabeth Fenwick, PhD
OPEN Health Evidence & Access, Oxford, United Kingdom
Elisabeth Fenwick is Chief Scientific Officer for HEOR & Market 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.
Natalia Kunst, PhD
University of York, York, United Kingdom
Lotte Steuten, PhD
Office of Health Economics, London, 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).
Estimating Health-State Utility for Economic Models in Clinical Trials and Real-World Studies
Level: Introductory
Track: Economic Evaluation
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.
Network Meta-Analysis in Relative Effectiveness Research
Level: Intermediate
Track: 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.
PREREQUISITE: 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
Chief Scientist, PRECISIONheor, Oakland, 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.
Causal Inference and Causal Diagrams in Big, Real-World Observational Data and Pragmatic Trials
Level: Experienced
Track: Real World Data & Information Systems
Separate registration required.
Innovative causal inference and target trial emulation methods are needed for the design and analysis of big real-world observational data and pragmatic trials. This course will introduce the principles of causation in comparative effectiveness research, the use of causal diagrams (directed acyclic graphs; DAGs) and focus on causal inference methods for time-independent confounding (multivariate regression, propensity scores) and time-dependent confounding (g-formula, marginal structural models with inverse probability of treatment weighting, and structural nested models with g-estimation). The “target trial” concept and a counterfactual approach with “replicates” will be used to apply causal methods to big real-world datasets with case examples from oncology, cardiovascular disease, HIV, nutrition and obstetrics. The course will consist of lectures, case examples drawn from the published literature and interactive discussion. The intended audience includes researchers from all substance matter fields, statisticians, epidemiologists, outcome researchers, health economists and health policy decision makers interested either in methods of causal analysis or causal interpretation of results based on the underlying method.
PREREQUISITE: Students are expected to have a basic knowledge in epidemiologic studies and methods (including the concept of confounding).
Faculty Member
Douglas E. Faries, PhD
Consulting Services, Alma, AR, USA
Doug Faries has a PhD in Statistics from Oklahoma State University. He spent 34 years as a statistician in the pharmaceutical industry, retiring as a Vice President of Real-World Access and Analytics at Eli Lilly and Company where he led the development of real-world analytical capabilities for the business. Doug has extensive experience with the design and analysis of observational research including comparative effectiveness analyses and sensitivity analysis for unmeasured confounding. He remains active in the statistical community with over 150 peer-reviewed manuscripts, authoring books and book chapters on analysis of observational data, and teaching short-courses on causal inference at national meetings.
Uwe Siebert, MD, MPH, MSc, ScD
UMIT - University for Health Sciences Medical Informatics and Technology Hall in Tirol, Austria and Harvard Chan School of Public Health Harvard University, Boston, MA, USA
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.
Valuing Health: The Generalized Risk Adjusted Cost-Effectiveness (GRACE) Model
Level: Intermediate
Track: Economic Evaluation
Separate registration required.
This course will present to participants a complete picture of the Generalized Risk Adjusted Cost Effectiveness (GRACE) model for health technology evaluation. The course will begin by discussing current uses of standard cost-effectiveness analysis (CEA) and concerns raised by that model. The GRACE methodology will be discussed along with its mathematical foundations. This workshop will also discuss what is necessary to incorporate the GRACE methodology into standard CEA as well as some important ethical implications of GRACE. This intermediate level course requires participants to have a working knowledge of basic calculus.
Faculty Member
Darius Lakdawalla, PhD
USC Leonard D. Schaeffer Center for Health Policy and Economics, Los Angeles, CA, USA
Darius Lakdawalla is a widely published, award-winning researcher and leading authority on health economics and health policy. He holds the Quintiles Chair in Pharmaceutical Development and Regulatory Innovation at the University of Southern California, where he sits on the faculties of the School of Pharmacy and Sol Price School of Public Policy. He is also the Director of Research at the USC Leonard D. Schaeffer Center for Health Policy and Economics, one of the nation’s premier health policy research centers. His research has focused primarily on the economics of risks to health, the value and determinants of medical innovation, the economics of health insurance markets, and the industrial organization of healthcare markets.
Charles Phelps, PhD
University of Rochester, Pittsford, 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, In 2023, he received ISPOR's Avedis Donabedian Lifetime Acheivement Award. He 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 include the use of multi-criteria decision analysis (MCDA), particularly in its proper use when the “decision-maker” is a group, and development of the Generalized Risk Adjusted Cost-Effectiveness (GRACE) methodology for valuing health gains.
Valuation of Innovative Drugs
Level: Intermediate
Track: 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
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.
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, 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.
