Tue May 13
8:00 AM - 12:00 PM
A Health Economics Approach to US Value Assessment Frameworks
Topics: Health Technology Assessment
Level: Introductory
Separate registration required.
This short course will focus on the ongoing evolution of US value assessment frameworks. We trace this by beginning with the highly cited ISPOR Special Task Force Report (2018), “A Health Economics Approach to US Value Frameworks.” We will provide an overview of recent US value assessment frameworks from the ISPOR Value Flower, through to Generalized and Risk-Adjusted Cost-Effectiveness (GRACE) valuation methodology, and on to Generalized CEA (GCEA), introducing new concepts involving “stacked cohorts” of beneficiaries and the consequences of patent expiry. We also emphasize the importance of perspective and decision context in the construction and use of value frameworks. We will discuss how a health economics approach from a societal or health plan perspective leads to the use of GCEA to help guide efficient resource allocation.
The course will provide 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 also review broader approaches to cost-benefit aggregation and value-based decision-making, including augmented CEA (introduced by the ISPOR Task Force Report), GCEA, and multi-criteria decision analysis (MCDA), with an overview of issues and new approaches to MCDA. The discussion will incorporate new approaches that combine various CEA frameworks with formal social welfare functions (SWFs), focusing on those that respect individuals’ own evaluations of their well-being and the Pareto principle.
Speakers
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Richard Willke, PhD
Scintegral Health Economics, Soddy Daisy, TN, United States
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Lou Garrison, PhD
University of Washington, Seattle, WA, United States
Lou Garrison, PhD, is professor emeritus in The Comparative Health Outcomes, Policy, and Economics Institute in the School of Pharmacy at the University of Washington, where he joined the faculty in 2004.
For the first 13 years of his career, Dr. Garrison worked in non-profit health policy at Battelle and then the Project HOPE Center for Health Affairs, where he was the Director from 1989-1992. Following this, he worked as an economist in the pharmaceutical industry for 12 years. From 2002-2004, he was vice president and head of Health Economics & Strategic Pricing in Roche Pharmaceuticals, based in Basel, Switzerland.
Dr. Garrison received a BA in Economics from Indiana University, and a PhD in Economics from Stanford University. He has more than 150 publications in peer-reviewed journals. His research interests include national and international health policy issues related to personalized medicine, benefit-risk analysis, and other topics, as well as the economic evaluation of pharmaceuticals, diagnostics, and other technologies.
Dr. Garrison was elected as ISPOR President for July 2016-June 2017, following other leadership roles since 2005. He recently co-chaired the ISPOR Special Task Force on US Value Frameworks. He was selected in 2017 by PharmaVOICE as being among “100 of the Most Inspiring People” in the industry. He recently received the PhRMA Foundation and Personalized Medicine Coalition 2018 Value Assessment Challenge First-Prize Award as lead author on a paper on “A Strategy to Support the Efficient Development and Use of Innovations in Personalized and Precision Medicine.”
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Charles E Phelps, MBA, PhD
University of Rochester, Pittsford, NY, United States
Charles Phelps, PhD is professor and provost emeritus at the University of Rochester. He previously held appointments in the departments of economics and political science and served as the director of the Public Policy Analysis Program and chair of the Department of Community and Preventive Medicine in the School of Medicine and Dentistry. Earlier, Dr. Phelps served as a senior staff economist and the director of the Program on Regulatory Policies and Institutions at the RAND Corporation. Dr. Phelps’s research cuts across the fields of health economics, health policy, health technology assessment, and related topics, and he is the author of Health Economics (now in its sixth edition), among other books. He has testified before US congressional committees on health policy and intellectual property issues. He is a fellow of the National Bureau of Economic Research and serves on the board of directors of the Health Care Cost Institute. He has served as the chair of the Board of Directors of VirtualScopics, Inc., and as a consultant to Gilead Sciences, Inc., CardioDx, and Kaiser Permanente of Northern California. He received his BA in mathematics from Pomona College, an MBA in hospital administration, and a PhD in business economics from the University of Chicago. He is a member of the National Academy of Medicine.
Using Nontraditional Digital Health Platforms: A Novel Source of Real-World Evidence
Topics: Real World Data & Information Systems
Level: Intermediate
Separate registration required.
The reliance on data from electronic medical records (EMR) still predominantly demonstrates the effectiveness of health technologies. However, in the era of digital transformation, new data sources emerge, potentially serving as complementary or alternative sources of real-world evidence (RWE). Digital health platforms (DHPs), including wearables, mobile applications, and phone cameras, represent a burgeoning class of healthcare solutions. They not only offer novel avenues for healthcare platforms but also stand as potential sources of evidence for assessing the effectiveness of pharmaceuticals, medical devices, and healthcare services. Are we prepared to embrace digital solutions as standard healthcare platforms and as new sources of effectiveness data?
This course will initially introduce participants to various types of digital solutions, explore critical aspects of value assessment, and delve into how DHPs can constitute a fresh source of RWE applicable for pricing and reimbursement decision making. Through preselected case studies encompassing pharmaceuticals and medical devices, participants will examine practical methodologies for leveraging digital solutions as sources of RWE across diverse countries and healthcare systems. Interactive discussions will engage participants in considering the integration of innovative data sources into healthcare decision making, while accounting for varied stakeholder perspectives. The overarching objective is to advocate for the inclusion of data collected by DHPs in health economics and outcomes research.
Moreover, the course aims to stimulate discourse on adapting economic evaluation methods to effectively capture the complexities associated with adopting DHPs (such as intervention complexity, outcome complexity, and causal pathway complexity) as the new frontier of RWE.
In this course, participants will familiarize themselves with different types of digital solutions, consider critical aspects of value assessment, and finally how and in which therapeutic areas they can constitute a new source of RWE applicable for pricing and reimbursement decision making. The course will discuss the advantages/disadvantages of including data collected by DHPs into health economics and outcomes research and will recommend/demonstrate how methods of economic evaluation might be adapted to better capture the complexity associated with the adoption of DHPs as the new source of RWE.
Speakers
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Katarzyna Kolasa, PhD
Kozminski University, Warsaw, Poland
Driven with passion to improve healthcare, Katarzyna has focused her academic and business career on health economics.
She has been working with multiple pricing and 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 an academic teacher and supervisor for over 30 MBA and PhD students. 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 6 months educational program designed for digital transformation leaders working in the healthcare sector. Katarzyna developed an innovative Master Program Health Economics & Big Data (HEBDA) with the first edition being 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” for ISPOR, The Professional Society for Health Economics and Outcomes Research. She is currently a member of the ISPOR Education Council and a previous member of the ISPOR Health Science Policy Council 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. Since January 2022, she is the leader of AI special interest group at the Polish Chamber of Physicians. With the patronage of the Polish Parliamentary Commission for Innovation & Digitalization, 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 has presented her research at more than 60 international scientific conferences. As of 2022, Google Scholar reports over 730 citations to her work.
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Carl V Asche, BA, MBA, MSc, PhD
University of Utah, Salt Lake City, UT, United States
Carl V. Asche, MBA, MSc, PhD, is currently a Research Professor in the Department of Pharmacotherapy at the University of Utah Health College of Pharmacy in Salt Lake City and Executive Director of the Department's Pharmacotherapy Outcomes Research Center. He also serves as the Director of the Post-Doctoral Fellowship Program in the Department of Pharmacotherapy along with appointments as Research Service WOC employee, Veteran's Affairs, Salt Lake City Healthcare System and Associate Member, Cancer Control and Population Science Research Program at the Huntsman Cancer Institute. His Research focuses on the use of comparative effectiveness research and cost-effectiveness analysis in health care decision making. His academic work has comprised of authoring and co-authoring over 150 peer-reviewed publications appearing in medical and economic literature. He serves on numerous national and international health economics-focused boards and committees, including editorial, grant review and advisory bodies. Dr. Asche's current research is funded by a variety of federal agencies and pharmaceutical companies. He earned his PhD (Economics) from the University of Surrey, MSc (Health Economics) from the University of York, and MBA from the City University of Seattle.
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Brian Seal, MBA, RPh, PhD
Germantown, MD, United States
Current AVP HEOR at Organon with 40 years’ experience in healthcare from managerial, financial, research, policy and pharmacy perspectives. Brian has spent 25 years in pharma mostly in HEOR and is a former member of Medicare Evidence Development & Coverage Advisory Committee (MEDCAC 2010-2012).
He is an adjuvant professor at the Philadelphia College of the Sciences Graduate School of Business (2002-2010), and has been an ISPOR member since 2001, a task force co-leader for pricing and drug standards (2008), a member of the data and registries group (2015-2017), and the Digital Health group since 2018 serving as chair in 2025.
Brian’s education includes a BS in Pharmacy (5 year), MBA, and PhD all from The University of South Carolina with over 100 peer-reviewed publications and hundreds of abstracts at congresses.
Introduction to Applied Generative AI for HEOR
Topics: Methodological & Statistical Research
Level: Introductory
Separate registration required.
The rapid advancement in generative artificial intelligence (GenAI) presents an opportunity for transformative potential in the field of health economics and outcomes research (HEOR). This course provides an introductory understanding of generative AI models with a particular focus on large language models (LLMs), which are transforming the field of HEOR. Participants will be provided with an overview of the most appropriate ways to access LLMs, going beyond the use of chatbots. Further, they will be given insights into how to use prompt engineering, retrieval-augmented generation (RAG) and agents to conduct scientific research and gain an understanding on issues pertaining to privacy and security when using GenAI for HEOR. Participants will further explore specific applications of these models for conducting robust scientific HEOR research in, for example, systematic literature reviews (SLR) and economic evaluation. The course aims to equip participants with the knowledge to begin to use generative AI techniques for specific HEOR contexts and to appreciate how these innovative approaches can enhance HEOR activities. Practical exercises using Python and relevant AI frameworks will be incorporated for participants to follow along.
PREREQUISITES: Students should have a general understanding of common HEOR concepts such as SLRs and cost-effectiveness models. Knowledge of Python or similar programming languages such as R is considered a benefit but not required.
Speakers
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Sven L Klijn, MSc
Bristol Myers Squibb, Utrecht, Netherlands
Sven Klijn is Director at Bristol Myers Squibb in the Global HEOR team, where he leads the innovative modeling agenda in hematology and cell therapy. In addition, Sven has an active role in providing modeling education and masterclasses at international congresses. He has widely published on innovative methods, especially in the fields of survival extrapolation and Generative AI. Sven has a training in public health and health economics and previously held various roles in CROs.
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William Rawlinson, MPhysPhil
Estima Scientific, London, United Kingdom
Will is a senior health economist at Estima Scientific holding a degree in Physics and Philosophy from the University of Oxford. Will has 4 years’ experience developing cost-utility models and has specialized in applications of generative AI to health economic modelling. Will has published on the automation of R modelling using large language models (LLMs), and more recently has focused on applications of LLMs to Excel modelling and model reporting.
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Tim Reason, MSc
Estima Scientific, London, United Kingdom
Tim Reason is co-founder of Estima Scientific and specializes in AI and evidence synthesis, having spent 15 years in the field of HEOR and technology. Tim is managing director of Estima, driving business activities, innovation and strategy for the company. Tim’s specializes in the intersection of HEOR, software development and AI to drive better outcomes for patients. Tim is the lead author on 2 seminal papers in AI for HEOR, showing that AI can be used to automate health economic modelling and NMA.
Cost-Effectiveness Analysis Alongside Clinical Trials
Topics: Economic Evaluation
Level: Introductory
Separate registration required.
The growing number of prospective clinical/economic trials reflects both widespread interest in economic information for new technologies and the regulatory and reimbursement requirements of many countries that now consider evidence of economic value along with clinical efficacy. This course will present the design, conduct, and reporting of cost-effectiveness analyses alongside clinical trials based on, in part, "Good Research Practices for Cost-Effectiveness Analysis alongside Clinical Trials: The ISPOR RCT-CEA Task Force Reports". Trial design, selecting data elements, database design and management, analysis, and reporting of results will all be presented. Trials designed to evaluate effectiveness (rather than efficacy), as well as clinical outcome measures, will also be discussed, including how to obtain health resource use and health state utilities directly from study subjects and economic data collection fully integrated into the study. Analyses guided by an analysis plan and hypotheses, an incremental analysis using an intention to treat approach, characterization of uncertainty, and standards for reporting results will be presented. Familiarity with economic evaluations will be helpful.
Speakers
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Federico Augustovski, MSc, PhD, MD
University of Buenos Aires, Buenos Aires, 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).
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Scott Ramsey
Fred Hutchinson Cancer Research Center, Lake Forest Park, WA, United States
Dr. Ramsey is a general internist and health economist. He is a professor and director of the Hutchinson Institute for Cancer Outcomes Research, a multidisciplinary team devoted to cancer outcomes research. Dr. Ramsey is also a professor in the Schools of Medicine and Pharmacy at the University of Washington.
Trained in Medicine and economics, Dr. Ramsey’s research focuses on outcomes research and cancer care delivery. His studies on financial toxicity issues faced by cancer patients are widely cited. He leads the Value in Cancer Care initiative, a statewide quality and cost reporting program aimed at improving oncology care. His other research interest includes cancer care delivery research, pragmatic trial design, cost-effectiveness analysis, and stakeholder engagement.
Dr. Ramsey is co-chair of the National Cancer Institute’s Cancer Care Delivery Research Steering Committee and a co-chair of SWOG’s Cancer Care Delivery Committee. He is past president of the Professional Society for Health Economics and Outcomes Research (ISPOR) and has served on the National Academy of Science’s Cancer Policy Forum. He is co-principal Investigator for the Coordination and Communications Center of the National Cancer Institute’s Cancer Screening Research Network.
Health Economic Modeling in R: A Hands-On Introduction
Topics: Economic Evaluation
Level: Introductory
Separate registration required.
This highly practical course will outline the computational and transparency advantages of using R, for those used in 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.
Speakers
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Felicity Lamrock, PhD
Queen's University Belfast, Belfast, Ireland
Dr. Felicity Lamrock is a senior lecturer in Data Analytics at Queen’s University Belfast. 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/pharmacoeconomic assessment.
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Howard Thom, MSc, PhD
University of Bristol, Bristol, United Kingdom
Howard Thom has worked for over 10 years developing health economic models in R. These have been in many disease areas, including heart disease, stroke, physiotherapy, mental health, rheumatology, dermatology, and oncology. His methodological interests are structural uncertainty, value of information analysis, and the use of R for efficient modelling. He founded and co-chairs the R for Health Technology Assessment (HTA) scientific committee, organizing annual workshops on the use of R in HTA. He currently works at both the University of Bristol and at Clifton Insight, giving him the perspective of both commercial consulting and academia.
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Rose Hart, PhD
Dark Peak Analytics, Sheffield, United Kingdom
Rose Hart has been a director and health economist at Dark Peak Analytics since February 2025, specialising in researching, consulting and teaching health economics in R. She is experienced in developing bespoke health economic models and value tools in both Excel and R, with further experience developing models into web-based user interfaces and software to improve stakeholder engagement with models. Previously, she was a Principal Health Economist at Lumanity, and part of the Health Economics Analysis team for 8 years and researched for her PhD at the University of Sheffield.
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Petros Pechlivanoglou, MSc, PhD
The Hospital for Sick Children, Toronto, ON, Canada
Advanced Patient-Reported Outcomes
Topics: Patient-Centered Research
Level: Advanced
Separate registration required.
This course provides an in-depth discussion of the steps needed to successfully implement patient-reported outcomes (PRO) measurement within the drug development program to generate data to support patient-centered value messages. Formulation of a successful PRO strategy requires an understanding of PRO instrument selection, psychometric evaluation, data capture, and interpretation to negotiate regulatory, reimbursement, and market access drug development hurdles. Judging PRO instrument quality and appropriateness can be challenging.
The course will present the key elements to consider at each step in reviewing and selecting PRO measures and determining the need for new instruments. In addition, participants will gain a better understanding of regulatory expectations for qualitative and quantitative evidence to support the quality of PRO measures and aspects to consider when interpreting meaningful change. The course will include interactive discussions of PRO success stories and common pitfalls to watch out for during PRO implementation in clinical trial programs.
Participants will gain the knowledge and skills required to take on a more active and confident role in the PRO strategy and implementation process.
PREREQUISITE: This course assumes that participants will have a basic knowledge of key PRO-related concepts (eg, health-related quality of life, symptoms, impacts, a general knowledge of the PRO development steps, and a working knowledge of PRO measurement within clinical programs.)
Speakers
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Ari Gnanasakthy, MBA, MSc
RTI Health Solutions, Succasunna, NJ, United States
Ari Gnanasakthy is head of Patient-Reported Outcomes at RTI-HS. Prior to RTI-HS.
Mr. Gnanasakthy was the executive director and head of the Patient-Reported Outcomes Center of Excellence at Novartis Pharmaceuticals. He has almost 25 years of experience in the pharmaceutical industry. At Novartis, he worked in several departments, including Biostatistics, Health Economics, Pricing, and Outcomes Research. After receiving his bachelor's degree in mathematics, statistics, and computing, Mr. Gnanasakthy joined Rothamsted Experimental Station (UK), where he was responsible for the statistical analysis of survey data of agricultural soil in England and Wales. He then joined the Milk Marketing Board (UK), where he was a part of the team responsible for modeling lactation curves of dairy cows. Mr. Gnanasakthy's extensive experience in the field of statistics and outcome research has resulted in numerous abstracts and almost 40 publications. Throughout his career, Mr. Gnanasakthy has developed and validated over a dozen patient-reported outcomes instruments and currently serves in the editorial board of Cancer Clinical Trials and a reviewer for many professional journals, including Value in Health.
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Rebecca Crawford, MA
RTI Health Solutions, Manchester, United Kingdom
Ms. Crawford has 13 years of experience providing consultative support to pharmaceutical companies with a focus on the development of patient-reported outcome (PRO) measurement strategies to best meet the needs of their clinical trial programs.
Ms. Crawford has developed, culturally adapted, and validated clinical outcome assessment measures, including PROs for several different therapeutic areas. Ms. Crawford has expertise in research design and in the application of both traditional and innovative qualitative research methods, including the collection and analysis of social media data to provide insights into the patient disease and treatment experience.
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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.
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Nicholas J. Rockwood, PhD
RHI Health Solutions, Bend, OR, United States
Nicholas Rockwood, PhD, is a senior psychometrician in the Patient-Centered Outcomes Assessment group with RTI Heath Solutions and has been working on psychometric evaluations of clinical outcome assessments. Prior to joining RTI-HS, Dr. Rockwood was an assistant professor within the School of Behavioral Health at Loma Linda University, where he conducted quantitative research, taught doctoral-level statistics courses, and provided statistical consulting services to medical and behavioral health faculty and researchers. His statistics and psychometrics research, which has been published in top psychometrics journals such as Psychometrika and Multivariate Behavioral Research, broadly focuses on the development and evaluation of generalized latent variable modeling methods (eg, item response theory, multilevel modeling, structural equation modeling).
1:00 PM - 5:00 PM
Using RWE to Inform the Value and Affordability Assessment of Cell and Gene Therapies
Topics: Real World Data & Information Systems
Level: Intermediate
Separate registration required.
This short course explores the role of real-world evidence (RWE) in supporting the economic evaluation of cell and gene therapies (CGTs). Many CGTs are one-time therapies that have the potential to offer transformative sustained benefits for patients with severe conditions. In many situations, the ‘do-nothing’ alternative is the norm, so the need for a control arm may be futile yet reducing the options for patients to be included in allegedly active arms. However, at launch there is often resistance from payers to reimburse these potentially transformative therapies due to the limited validity of the supporting evidence (small, single arm trials, etc) which leads to uncertainty regarding: the size and heterogeneity of the patient population eligible for CGTs; the definition of standard of care and natural disease progression, given CGTs may unlock treatment possibilities of previously deemed untreatable and rare diseases; the novel therapy’s duration of benefit; and the relative effectiveness of the novel therapy compared to the current standard of care, particularly, as cell and gene therapies are often only supported by a single arm trial.
Payer concerns with these uncertainties in the evidence are heightened by the typically high up-front costs associated with cell and gene therapies and the consequence for their affordability. While there is generally not a good understanding of the effect sizes and costs of standard of care.
This course will provide an overview of the potential contribution, planning and use of RWE to help address these concerns. We will assume payer archetypes that are focused on one or more of relative effectiveness and cost-effectiveness (value), and budget impact (affordability). Within these archetypes, we will discuss the role and acceptability of RWE to inform payment and policy with emphasis on eligibility, appropriate comparators, durability of benefit, spending for patients that meet criteria for eligibility and the development of appropriate outcome-based agreements. A strong focus will be brought on validity (internal and external) of the existing data. We will further provide participants with real-world examples of using RWE to inform policy making. This course will target a wide range of participants, from medical operations to HEOR, interested in understanding the depth of issues to consider when balancing access with payment for CGTs.
PREREQUISITE: This course requires familiarity with basic economic evaluation and HTA concepts and methodologies of pharmaceuticals.
Speakers
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Daniel Gladwell, PhD
Lumanity, London, United Kingdom
Dan Gladwell is the chief scientific officer for Lumanity HE&HTA. A health economist by background, he has a particular passion for demonstrating the value of highly innovative therapies that make a transformative difference to patient outcomes. Dan supported one of the first CAR T-cell therapies to be assessed by NICE. Since that appraisal Dan has been continuously engaged in supporting patient access to cell and gene therapies through engaging in HEOR evidence generation planning efforts at the Global, Regional and National levels; and informing efforts to shape the HTA policy context for cell and gene therapies.
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Robert Brett McQueen, PhD
University of Colorado Skaggs School of Pharmacy and Pharmaceutical Science, Denver, CO, United States
R. Brett McQueen is the director for the Center for Pharmaceutical Value (pValue) at the University of Colorado Skaggs School of Pharmacy and Pharmaceutical Sciences, where he is an associate professor in the Department of Clinical Pharmacy. Brett’s work includes comparative effectiveness research, cost-effectiveness applications and methods development, multi-criteria decision analysis, outcomes-based contracting, and patient preferences research.
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Oriol Solà-Morales, MSc, PhD, MD
Fundacio HITT, Barcelona, Spain
Oriol has built a career in the planning, policy and decision-making environment (Regional HTA Agency director (2007-2011); Innovation and Strategy Director in several hospitals, member of the Regional Research Advisory Council and policy advisor to 2 Health Ministers). In 2011, he founded HITT, which transformed in 2019 into the HiTT Foundation to strive for innovation in sustainable healthcare.
He is an assistant professor in Pharmacology and Health Economics at Universitat Internacional de Catalunya, teaching several courses nationally and internationally and a Research Fellow at the OHE (office for Health Economics). Oriol is an MD specialized in Internal Medicine, has earned an MSc from the London School of Economics and Political Science (LSE) and the London School of Hygiene and Tropical Medicine (LSHTM), and a PhD from Universitat Rovira i Virgili (URV).
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Marina Richardson
ICER, Boston, MA, United States
Marina Richardson is an associate director, Health Technology Methods and Health Economics with the Institute for Clinical and Economic Review (ICER). In her role, Marina leads and oversees the development of economic models to inform pricing and reimbursement decision-making and identifies and executes opportunities to enhance ICER's methodology and processes within Health Technology Assessment (HTA) and Health Economics. Prior to joining ICER, Marina led and contributed to reimbursement review reports and recommendations at Canada's Drug Agency (CDA-AMC), formerly CADTH. Marina has a PhD in Health Services Research from the University of Toronto and is an active contributor to the field including as a deputy editor for the International Journal of Technology Assessment in Health Care (IJTAHC), a member of the Ontario Immunization Advisory Committee (OIAC) in Ontario, Canada, and as a co-chair of the International Scientific Program Committee for Health Technology Assessment International (HTAi) 2025.
Applied Cost-Effectiveness Modeling With R
Topics: Methodological & Statistical Research
Level: Intermediate
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.
PREREQUISITE: Participants who wish to gain hands-on experience are required to bring their laptops. 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.
Speakers
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Jeroen Jansen, PhD
PRECISIONheor and University of California, San Francisco, CA, United States
Jeroen P. Jansen, PhD, is a methodologist working at the intersection of evidence synthesis, biostatistics, and health economics. He is an associate professor in the Department of Clinical Pharmacy in the School of Pharmacy at the University of California, San Francisco, and chief scientist, Health Economics & Outcomes Research at the Precision Medicine Group.
For the past 15 years, Dr. Jansen has worked on research to understand the clinical and economic value of healthcare interventions. His research has frequently been conducted in the context of health technology assessment (HTA) with a focus on comparative effectiveness and cost-effectiveness. Prompted by the challenges encountered in applied research projects, he has performed methodological research. Notable contributions are the development of novel statistical methods to overcome the typical challenges in model-based cost-effectiveness evaluations characterized by gaps in the evidence base and complex evidence structures. Furthermore, Dr. Jansen led initiatives to develop guidance for consumers and producers of network meta-analysis studies. He has promoted a more transparent and credible approach to model-based health economic evaluations and led the development of open-source simulation models to illustrate its feasibility.
Dr. Jansen has been involved in the ongoing development of an R software package to develop simulation models for health economic evaluations. His current research interests are the clinical and economic value of precision medicine, incorporating health disparities in health economic modeling studies, and statistical methods for evidence synthesis. He has published extensively in his areas of expertise and is widely cited. He is co-author of a textbook on network meta-analysis for decision-making and was associate editor for the Journal for Research Synthesis Methods. Dr. Jansen has a PhD in epidemiology from the Erasmus University in the Netherlands
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Devin Incerti, PhD
EntityRisk, Inc., San Francisco, CA, United States
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.
Valuation of Innovative Drugs
Topics: Health Policy & Regulatory
Level: Intermediate
Separate registration required.
The value of medical innovation depends on a stakeholder's perspective in different decision contexts. In the context of registration, authorities (EMA, FDA) mainly consider the clinical value of medical innovation. In the context of coverage decisions, national health authorities may adopt a broader perspective by including clinical, economic criteria, and sometimes even other criteria such as equity and social values. In the context of pricing and reimbursement, "value-based pricing" is the most widely accepted approach across countries, but it can vary from a narrow concept based on the incremental cost-effectiveness ratio (ICER) threshold to broader societal or holistic approaches. Value-based pricing determines the maximum price from the national payer perspective. In the context of the investment decision, this price should exceed the minimum price for the investor acting in the international financial market to make a financial valuation. Furthermore, there are numerous other stakeholders--eg, patients, physicians, healthcare insurers, and employers--with their specific assessment of the value of medical innovation including, for example, patient and family quality of life, real-world effectiveness, budget impact, and the costs of lost productivity. This course offers an overview of the perspectives of the relevant stakeholders, their respective data requirements, and their methods and processes for the value assessment of innovative drugs. The course will then describe an in-depth description of the various value-based pricing methods--eg, the ICER, multicriteria decision analysis (MCDA), comparative effectiveness research (CER), and relative effectiveness (RE). We include examples of orphan drugs and advanced therapy medical products (ATMPs) which are the 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.
Speakers
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Lou Garrison, PhD
University of Washington, Seattle, WA, United States
Lou Garrison, PhD, is professor emeritus in The Comparative Health Outcomes, Policy, and Economics Institute in the School of Pharmacy at the University of Washington, where he joined the faculty in 2004.
For the first 13 years of his career, Dr. Garrison worked in non-profit health policy at Battelle and then the Project HOPE Center for Health Affairs, where he was the Director from 1989-1992. Following this, he worked as an economist in the pharmaceutical industry for 12 years. From 2002-2004, he was vice president and head of Health Economics & Strategic Pricing in Roche Pharmaceuticals, based in Basel, Switzerland.
Dr. Garrison received a BA in Economics from Indiana University, and a PhD in Economics from Stanford University. He has more than 150 publications in peer-reviewed journals. His research interests include national and international health policy issues related to personalized medicine, benefit-risk analysis, and other topics, as well as the economic evaluation of pharmaceuticals, diagnostics, and other technologies.
Dr. Garrison was elected as ISPOR President for July 2016-June 2017, following other leadership roles since 2005. He recently co-chaired the ISPOR Special Task Force on US Value Frameworks. He was selected in 2017 by PharmaVOICE as being among “100 of the Most Inspiring People” in the industry. He recently received the PhRMA Foundation and Personalized Medicine Coalition 2018 Value Assessment Challenge First-Prize Award as lead author on a paper on “A Strategy to Support the Efficient Development and Use of Innovations in Personalized and Precision Medicine.”
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Marlene Gyldmark, MPhil
BeiGene, Basel, Switzerland
In her current role, Marlene leads the EU HTA organizational readiness at BeiGene in the Global Value, Access, and Pricing group.
Marlene’s prior life science industry experience includes vice president global head Access Evidence at Idorsia, Switzerland; global head Health Policy and Outcomes Research at Roche Diabetes Care, Switzerland; global head Modelling, Outcomes Research, Statistics and Epidemiology, Roche Pharma, Switzerland; health economist at Pfizer Denmark, and Pricing and Economic Analyst at Novo Nordisk, Denmark. Before joining the life science industry, she worked as a researcher in the Danish Hospital Institute, Denmark and at University of Copenhagen, Denmark.
Since 1996 Marlene has been an external lecturer at University of Copenhagen, Denmark.
Other work experiences include serving as a member of the board of directors (2000-2012) at EASE Consulting, Denmark and member of the board of the Institute of Neurodiversity (2021- 2025). She has been a long-term member of ISPOR and served as member of the Board of Directors between 2021-2024. Currently, Marlene also acts as a Copenhagen Goodwill ambassador.
She holds a master’s in economics and policy sciences from University of Copenhagen, Denmark, and a MPhil in health economics from York University, UK.
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Mark Nuijten, MBA, PhD, MD
Ben Gurion University, North Holland, Netherlands
Mark Nuijten is a medical doctor, health economist, valuation economist, and healthcare publicist. He is a visiting professor at Ben-Gurion University in Israel, setting up the department on Clinical and Economic Valuation of Medical Innovation. He has become a leading health policy and economics expert over the last 2 decades, reflected in more than 200 publications and leading positions in scientific societies and editorial boards. Dr. Nuijten was board director of ISPOR (2002-2004) and chair of the Management Board of Value in Health (2002-2004). He was a member of the Editorial Advisory Board of Value in Health. He obtained his PhD in health economics (2003) on the thesis “In search for more confidence in health economic modelling” at the Erasmus University, Rotterdam.
Mark Nuijten is founder of A2M (Ars Accessus Medica) and founding partner of the Minerva International Health Economic Network. He was trained as a physician and worked in clinical research before obtaining his international MBA from Erasmus University, Rotterdam, where he later was a senior staff member. Prior to setting up Ars Accessus Medica, Dr. Nuijten was the founding managing director of the IQVIA Quintiles office in the Netherlands, which included European responsibility for the policy and health economic division.
He is a pioneer in the field of healthcare innovation in biotechnology and has been the first classical health economist successfully applying and developing Discounted Cash Flow methodologies for valuation of biotechnology innovation (eg, a pricing model to assess prices of expensive orphan drugs from an investor’s perspective—published in a Nature journal). He also developed an integrated valuation model, an interactive dynamic tool for the economic valuation of R&D projects, which can be used to optimize the initial clinical program (eg, indication, comparator, outcomes, and study design), and the associated pricing and market access pricing strategy.
Using LLMs to Simplify Real-World Evidence Research
Topics: Real World Data & Information Systems
Level: Intermediate
Separate registration required.
This course explores the transformative role of Al in advancing real-world evidence (RWE) research, covering essential applications and innovations.
We begin with an introduction to how Al is applied to medical records, detailing the foundational challenges that this technology seeks to address. The first hour dives into practical applications, demonstrating how Al can extract and analyze insights from complex, longitudinal medical records, as well as system issues such as data access and patient privacy that must be considered when working with this data. The second hour examines technical challenges and explores the intriguing complexities that come with deploying Al in healthcare settings. In the third hour, we focus on safety and validation systems, emphasizing the importance of rigorous standards to ensure accuracy and reliability in Al-driven RWE research. In the final hour, we discuss impactful results and emerging opportunities, highlighting how Al-driven advancements can propel RWE research and support meaningful developments in patient care and regulatory support.
PREREQUISITE: This course assumes that participants are familiar with the standing challenges and opportunities for RWE in research.
Speakers
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Dan Drozd, MSc, MD
PicnicHealth, San Francisco, CA, United States
Daniel R. Drozd, MD, MSc, is the chief medical officer at PicnicHealth. Prior to joining PicnicHealth he was on faculty at the University of Washington in the Department of Allergy & Infectious Diseases where he led research into the use of electronic health record data to power observational research and enhance the understanding of the chronic burden of HIV infection. At PicnicHealth he oversees scientific collaborations with PicnicHealth’s industry and academic partners and works extensively with both the product and commercial teams. Prior to attending medical school, he worked for numerous technology start-ups as an engineer and at the University of Washington in the Clinical Informatics Research Group where he led the development of a large EHR data integration platform used to power HIV real-world research.
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Troy Astorino
PicnicHealth, San Francisco, CA, United States
Troy Astorino is the co-founder and chief technology officer at PicnicHealth. With deep AI expertise from MIT and SpaceX, Troy co-founded PicnicHealth to make it easier to capture patient-centered data and improve healthcare. As the CTO, he leads product development, overseeing engineering, product, and design. Troy's expertise lies in AI-driven observational research and data quality. He has developed a system that continuously audits and improves data accuracy, ensuring that research insights generated by PicnicHealth address research questions with the highest level of reliability.
Valuing Health: The Generalized Risk Adjusted Cost-Effectiveness (GRACE) Model
Topics: Economic Evaluation
Level: Intermediate
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.
Speakers
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Charles E Phelps, MBA, PhD
University of Rochester, Pittsford, NY, United States
Charles Phelps, PhD is professor and provost emeritus at the University of Rochester. He previously held appointments in the departments of economics and political science and served as the director of the Public Policy Analysis Program and chair of the Department of Community and Preventive Medicine in the School of Medicine and Dentistry. Earlier, Dr. Phelps served as a senior staff economist and the director of the Program on Regulatory Policies and Institutions at the RAND Corporation. Dr. Phelps’s research cuts across the fields of health economics, health policy, health technology assessment, and related topics, and he is the author of Health Economics (now in its sixth edition), among other books. He has testified before US congressional committees on health policy and intellectual property issues. He is a fellow of the National Bureau of Economic Research and serves on the board of directors of the Health Care Cost Institute. He has served as the chair of the Board of Directors of VirtualScopics, Inc., and as a consultant to Gilead Sciences, Inc., CardioDx, and Kaiser Permanente of Northern California. He received his BA in mathematics from Pomona College, an MBA in hospital administration, and a PhD in business economics from the University of Chicago. He is a member of the National Academy of Medicine.
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Darius Lakdawalla, PhD
University of Southern California, Los Angeles, CA, United States
Darius Lakdawalla is a widely published, award-winning researcher and a leading authority on health economics and health policy. He holds the Quintiles Chair in Pharmaceutical Development and Regulatory Innovation at the University of Southern California, where he sits on the faculties of the School of Pharmacy, the Sol Price School of Public Policy, and the Leonard D. Schaeffer Center for Health Policy and Economics, one of the nation’s premier health policy research centers.
His academic research has focused primarily on the economics of risks to health, the value and determinants of medical innovation, the economics of health insurance markets, and the industrial organization of healthcare markets. Dr. Lakdawalla serves as associate editor at the Journal of Health Economics and has previously served in this role at the American Journal of Health Economics and the Review of Economics and Statistics. His academic work has appeared in leading peer-reviewed journals of economics, health policy, and medicine, including the American Economic Review, Quarterly Journal of Economics, Health Affairs, the Journal of Health Economics, and the New England Journal of Medicine. In addition, his work has been featured by prominent popular press outlets, such as the Wall Street Journal, National Public Radio, Forbes, and the New York Times. Dr. Lakdawalla has also received the PhRMA Foundation Value Assessment Challenge Award, designed to encourage innovative approaches to defining and measuring value in health care, in 2019 (third place) and 2020 (first place), along with the ISPOR Excellence in Research Methodology Award, the Garfield Prize, and the Milken Institute Award for Distinguished Economic Research.
Causal Inference and Causal Diagrams in Big, Real-World Observational Data and Pragmatic Trials
Topics: Real World Data & Information Systems
Level: Advanced
Separate registration required.
Innovative causal inference and target trial emulation methods are needed for the design and analysis of big real-world observational data and pragmatic trials. This course will introduce the principles of causation in comparative effectiveness research, the use of causal diagrams (directed acyclic graphs; DAGs) and focus on causal inference methods for time-independent confounding (multivariate regression, propensity scores) and time-dependent confounding (g-formula, marginal structural models with inverse probability of treatment weighting, and structural nested models with g-estimation). The “target trial” concept and a counterfactual approach with “replicates” will be used to apply causal methods to big real-world datasets with case examples from oncology, cardiovascular disease, HIV, nutrition and obstetrics. The course will consist of lectures, case examples drawn from the published literature and interactive discussion. The intended audience includes researchers from all substance matter fields, statisticians, epidemiologists, outcome researchers, health economists and health policy decision makers interested either in methods of causal analysis or causal interpretation of results based on the underlying method.
PREREQUISITE: Students are expected to have a basic knowledge in epidemiologic studies and methods (including the concept of confounding).
Speakers
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Uwe Siebert, MD, MPH, ScD
UMIT TIROL - University for Health Sciences and Technology, Tirol, Austria
Uwe Siebert, MD, MPH, MSc, ScD is a physician by training and professor of Public Health, Medical Decision Making & Health Technology Assessment, chair of the Dept. of Public Health, Health Services Research and HTA, and director of HTADS Continuing Education (www.htads.org) at UMIT TIROL, and adjunct professor of Epidemiology and Health Policy & Management at the Harvard Chan School of Public Health, Boston, MA, USA. He is currently a member of several Boards of Directors, European Commission Expert Groups, and he advises several HTA/government agencies in different countries. In the past, he was a member of the ISPOR Board of Directors, ISPOR Annual Meeting chair, and president of the Society for Medical Decision Making (SMDM).
His research interests include applying evidence-based quantitative and translational methods from health economics, health services & outcomes research, public health, epidemiology, artificial intelligence, modeling, causal inference from real-world data, and health data & decision science in the framework of health care policy advice and HTA as well as in the clinical context of routine health care, public health policies and patient guidance. He teaches courses for these topics at several universities and for industry in Europe, USA, South America, and Asia. He has worked with several HTA Agencies in Europe, Brazil, US and Canada and he advises public and government agencies, academic institutions, and industry regarding the conduction of HTAs and their impact on policy and reimbursement decisions. He has authored more than 400 publications (> 30,000 citations, H index > 80) including HTA reports, textbook chapters, scientific articles, policy briefs and editorials, and is editor of the European Journal of Epidemiology and editorial board member of several scientific journals.
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Douglas Faries, PhD
Alma, AR, United States
Doug Faries has a PhD in Statistics from Oklahoma State University. He spent 34 years as a statistician in the pharmaceutical industry, retiring as a vice president of Real-World Access and Analytics at Eli Lilly and Company where he led the development of real-world analytical capabilities for the business. Doug has extensive experience with the design and analysis of observational research including comparative effectiveness analyses and sensitivity analysis for unmeasured confounding. He remains active in the statistical community with over 150 peer-reviewed manuscripts, authoring books and book chapters on analysis of observational data, and teaching short courses on causal inference at national meetings.
