Tue May 13
7:00 AM - 6:00 PM
Registration Hours
Session Type: General Meeting
8:00 AM - 12:00 PM
A Health Economics Approach to US Value Assessment Frameworks
Session Type: Short Course
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
Session Type: Short Course
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
Session Type: Short Course
Topics: Methodological & Statistical Research
Level: Introductory
Separate registration required.
The rapid advancement in generative artificial intelligence (GenAI) presents an opportunity for transformative potential in the field of health economics and outcomes research (HEOR). This course provides an introductory understanding of generative AI models with a particular focus on large language models (LLMs), which are transforming the field of HEOR. Participants will be provided with an overview of the most appropriate ways to access LLMs, going beyond the use of chatbots. Further, they will be given insights into how to use prompt engineering, retrieval-augmented generation (RAG) and agents to conduct scientific research and gain an understanding on issues pertaining to privacy and security when using GenAI for HEOR. Participants will further explore specific applications of these models for conducting robust scientific HEOR research in, for example, systematic literature reviews (SLR) and economic evaluation. The course aims to equip participants with the knowledge to begin to use generative AI techniques for specific HEOR contexts and to appreciate how these innovative approaches can enhance HEOR activities. Practical exercises using Python and relevant AI frameworks will be incorporated for participants to follow along.
PREREQUISITES: Students should have a general understanding of common HEOR concepts such as SLRs and cost-effectiveness models. Knowledge of Python or similar programming languages such as R is considered a benefit but not required.
Speakers
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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
Session Type: Short Course
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
Session Type: Short Course
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
Petros Pechlivanoglou, PhD is a senior scientist at the Hospital for Sick Children, an associate professor at the Institute for Health Policy Management and Evaluation at the University of Toronto and an adjunct ICES scientist. His research focuses on the use of decision analysis and statistical modeling in estimating the long-term health economic consequences of disease or treatment exposure, with a focus in early childhood.
Advanced Patient-Reported Outcomes
Session Type: Short Course
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).
12:00 PM - 1:00 PM
Break (Coffee Service, Lunch on Own)
Session Type: General Meeting
1:00 PM - 5:00 PM
Using RWE to Inform the Value and Affordability Assessment of Cell and Gene Therapies
Session Type: Short Course
Topics: Real World Data & Information Systems
Level: Intermediate
Separate registration required.
This short course explores the role of real-world evidence (RWE) in supporting the economic evaluation of cell and gene therapies (CGTs). Many CGTs are one-time therapies that have the potential to offer transformative sustained benefits for patients with severe conditions. In many situations, the ‘do-nothing’ alternative is the norm, so the need for a control arm may be futile yet reducing the options for patients to be included in allegedly active arms. However, at launch there is often resistance from payers to reimburse these potentially transformative therapies due to the limited validity of the supporting evidence (small, single arm trials, etc) which leads to uncertainty regarding: the size and heterogeneity of the patient population eligible for CGTs; the definition of standard of care and natural disease progression, given CGTs may unlock treatment possibilities of previously deemed untreatable and rare diseases; the novel therapy’s duration of benefit; and the relative effectiveness of the novel therapy compared to the current standard of care, particularly, as cell and gene therapies are often only supported by a single arm trial.
Payer concerns with these uncertainties in the evidence are heightened by the typically high up-front costs associated with cell and gene therapies and the consequence for their affordability. While there is generally not a good understanding of the effect sizes and costs of standard of care.
This course will provide an overview of the potential contribution, planning and use of RWE to help address these concerns. We will assume payer archetypes that are focused on one or more of relative effectiveness and cost-effectiveness (value), and budget impact (affordability). Within these archetypes, we will discuss the role and acceptability of RWE to inform payment and policy with emphasis on eligibility, appropriate comparators, durability of benefit, spending for patients that meet criteria for eligibility and the development of appropriate outcome-based agreements. A strong focus will be brought on validity (internal and external) of the existing data. We will further provide participants with real-world examples of using RWE to inform policy making. This course will target a wide range of participants, from medical operations to HEOR, interested in understanding the depth of issues to consider when balancing access with payment for CGTs.
PREREQUISITE: This course requires familiarity with basic economic evaluation and HTA concepts and methodologies of pharmaceuticals.
Speakers
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Daniel Gladwell, 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 B McQueen, BA, MA, 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. He is active in ISPOR through contributions to short courses, workshops, issue panels, and research presentations.
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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
Session Type: Short Course
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
Session Type: Short Course
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
Session Type: Short Course
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
Session Type: Short Course
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
Session Type: Short Course
Topics: Real World Data & Information Systems
Level: Advanced
Separate registration required.
Innovative causal inference and target trial emulation methods are needed for the design and analysis of big real-world observational data and pragmatic trials. This course will introduce the principles of causation in comparative effectiveness research, the use of causal diagrams (directed acyclic graphs; DAGs) and focus on causal inference methods for time-independent confounding (multivariate regression, propensity scores) and time-dependent confounding (g-formula, marginal structural models with inverse probability of treatment weighting, and structural nested models with g-estimation). The “target trial” concept and a counterfactual approach with “replicates” will be used to apply causal methods to big real-world datasets with case examples from oncology, cardiovascular disease, HIV, nutrition and obstetrics. The course will consist of lectures, case examples drawn from the published literature and interactive discussion. The intended audience includes researchers from all substance matter fields, statisticians, epidemiologists, outcome researchers, health economists and health policy decision makers interested either in methods of causal analysis or causal interpretation of results based on the underlying method.
PREREQUISITE: Students are expected to have a basic knowledge in epidemiologic studies and methods (including the concept of confounding).
Speakers
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Uwe Siebert, 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
Consultant, Alma, AR, United States
Doug Faries has a PhD in Statistics from Oklahoma State University. He spent 34 years as a statistician in the pharmaceutical industry, retiring as a vice president of Real-World Access and Analytics at Eli Lilly and Company where he led the development of real-world analytical capabilities for the business. Doug has extensive experience with the design and analysis of observational research including comparative effectiveness analyses and sensitivity analysis for unmeasured confounding. He remains active in the statistical community with over 150 peer-reviewed manuscripts, authoring books and book chapters on analysis of observational data, and teaching short courses on causal inference at national meetings.
Wed May 14
7:00 AM - 8:30 AM
Morning Coffee Service
Session Type: General Meeting
Don't miss the start of the day with the Plenary Session. Enjoy your morning coffee as you listen to dynamic presentations intended to inspire and empower. Provided by ISPOR.
7:00 AM - 5:00 PM
Registration Hours
Session Type: General Meeting
8:30 AM - 9:45 AM
Welcome & First Plenary Session
Session Type: Plenary
9:30 AM - 7:00 PM
Exhibit Hall Hours
Session Type: General Meeting
9:45 AM - 10:15 AM
Wednesday Morning Coffee and Connect (Exhibit Hall)
Session Type: General Meeting
Head to the exhibit hall to connect with fellow attendees and exhibitors over a steaming cup of coffee.
10:15 AM - 11:15 AM
The Role of Patient-Reported Outcomes and Patient Preference Information in Regulatory and HTA Decision-Making
Session Type: Research Podiums
Patient-reported outcomes (PROs) and patient preference information (PPI) are increasingly considered by regulatory and HTA bodies. This session will examine the role of PROs and PPI in regulatory approvals and HTA decision-making, highlighting current trends, key challenges, and opportunities to enhance patient-centered decision-making.
Inclusion of Health-Related Quality of Life (HRQoL) and Other Patient-Reported Outcomes (PROs) in Reimbursement Reviews From the Canadian Agency for Drugs and Technologies in Health (CADTH)
OBJECTIVES: CADTH incorporates patient input during the reimbursement review process to gain insights into patient needs and experiences. Patient involvement aids in identifying outcomes that hold significant importance to patients, ensuring their measurement in clinical trials of new medicinal products. This study aims to describe the outcomes measured and reported in products assessed in CADTH reimbursement reports for asthma, non-small cell lung cancer (NSCLC), and rheumatoid arthritis (RA).
METHODS: Reimbursement reviews detailing a specific intervention for asthma, NSCLC, or RA were identified from the CADTH website. Information on outcomes reported by pivotal trials was extracted from these reviews and summarized descriptively.
RESULTS: A total of 63 clinical reports (13 for asthma, 42 for NSCLC, and 10 for RA) described 117 unique trials across 44 treatments. Most trials across all indications reported at least one HRQoL outcome (84.2% for asthma, 80.0% for NSCLC, and 83.3% for RA). Other PROs were commonly reported for asthma (92.1%) and RA (95.8%), but less so for NSCLC (18.2%). PROs were rarely primary outcomes; all NSCLC trials used clinical outcomes focused on survival or response measured by standard criteria, while all RA trials focused on multidimensional outcomes combining patient-reported data with clinical data, like the American College of Rheumatology 20/50/70 Response Criteria and Disease Activity Score. Clinical outcomes were the primary endpoint in most (89.5%) asthma trials, with a few focused on HRQoL (5.3%) or another PRO (5.3%).
CONCLUSIONS: The selection of primary and secondary/exploratory outcomes varies significantly based on the disease area, with diseases like RA showing a higher inclination towards incorporating patient-reported data in primary outcomes, reflecting the close relationship between treatment efficacy and patient experience. This patient-focused approach can enhance the assessment of treatment impact and patient well-being in clinical practice, and should be considered in the evaluation of new medicinal products.
Requirements for Patient-Reported Outcome and Data Analytics in Health Technology Assessment in England, France and Germany, and Opportunities for Methods Harmonization across European Markets
OBJECTIVES: To compare methods for collection, reporting, and analysis of patient-reported outcome (PRO) data in health technology assessment (HTA) in France, Germany, and England and identify opportunities for HTA harmonization across European markets.
METHODS: Interviews with key opinion leaders (KOLs) with HTA- and PRO-related expertise in Europe were conducted to gather feedback on PRO data collection, analysis, and reporting preferences in HTA.
RESULTS: KOLs from England (n=4), France (n=3), and Germany (n=5) were interviewed. All KOLs from Germany gave the highest rating regarding their perceived impact of PRO data on HTA decision-making. KOLs highlighted that PROs are particularly impactful in highly symptomatic and burdensome conditions. The availability of PRO data collection, analysis, and reporting guidance in HTA varies among HTAs. Most guidance, where available, is country-specific and, therefore, lacks harmonization across markets. HTAs in included markets require validated instruments to collect PRO data. Preferred instruments for HTA are specified in England (EQ-5D-3L) and France (EQ-5D-5L). There is a <30% allowance for missing data in HTA in Germany. Transparency is lacking for the missing data threshold accepted in England and France. Minimal clinically important differences (MCIDs) for PROs are specified in Germany (≥15% of the PRO scale range), while other markets have non-standardized MCIDs reflecting disease-specific expectations. Post-progression data collection is expected for oncology submissions in Germany and England.KOLs reported that cross-market PRO standards could be supported by Joint European HTA regulation, but uncertainties and challenges remain.
CONCLUSIONS: There is a lack of transparency and harmonization regarding the requirements for PRO data collection, analysis, and reporting for HTA in key European markets. Enhanced transparency of HTA requirements will help harmonization efforts and may be supported by Joint Clinical Assessment.
From Research to Policy: Incorporating Patient Preferences for Colorectal Cancer Treatments Into Health Technology Assessment
OBJECTIVES: There is growing interest to integrate patient preferences into health technology assessment (HTA) for drug reimbursement recommendations. However, approaches remain unexplored. The Patient Values Project aims to explore how to incorporate quantitative patient preferences for colorectal cancer treatments in a systematic manner into Canadian HTA.
METHODS: We developed a preference survey that included two discrete choice experiments (DCEs; DCE1: quality-of-life versus survival; DCE2: value of treatment attributes) and one best-worst scaling (BWS; treatment side effects) to estimate preferences for colorectal cancer treatments. The survey was administered across Canada to metastatic colorectal cancer patients (n=104), caregivers (n=57) and adults from the general population (n=441). Data were analyzed using mixed logit (DCEs) and count-based analysis (BWS). Results were then used as case examples to explore how to effectively incorporate preferences into HTA.
RESULTS: We observed preference heterogeneity across samples. DCE1 showed patients prioritize survival over quality-of-life more than the general population. DCE2 revealed caregivers prioritize avoiding side effects more than patients or the general population. BWS indicated similar rankings of most and least tolerable side effects for all samples. The following aspects were identified as essential for integrating patient preferences into HTA: (1) whose preferences should be included (e.g., preference heterogeneity), (2) when and how often should these data be collected (e.g., different treatment points), (3) how to include these data explicitly and operationally into HTA, (4) which attributes should be included for HTA (e.g., align with clinical trial endpoints or the most important), and (5) how can the results be generalizable across other cancer types.
CONCLUSIONS: The Patient Values Project is the first step in developing a systematic and structured approach for incorporating patient preferences into HTA alongside clinical and economic evidence. The novelty and relevance of this research can ultimately change how policymakers use patient preferences in patient-oriented decision-making.
The Role of Patient-Reported Outcomes in US FDA Novel Drug Approvals and Reimbursement Decisions (2020-2024)
OBJECTIVES: 1. Analysis of PROs in FDA novel drug & Reimbursement approvals & from 2020 to 2024 along with key examples
METHODS: A retrospective analysis of FDA approval summaries, payer policy documents, and Health Technology Assessment (HTA) reviews (e.g., ICER) was conducted
RESULTS: PRO Influence 2020: FDA : 53 novel drugs, with 18% (10 drugs). Reimbursement : 60 total approvals, with 15% (9 approvals). Rinvoq (AbbVie) - PRO data showed improved quality of life in rheumatoid arthritis, contributing to $2.3 billion . Zolgensma (Novartis) - Caregiver-reported outcomes 2021:FDA: 50 drugs, with 22% (11 drugs) Reimbursement : 75 total approvals, with 25% (19 approvals) . Zeposia (Bristol-Myers Squibb) - PROs on fatigue reduction generated $500 million. Imcivree (Rhythm Pharmaceuticals) - PRO data supported FDA approval 2022: FDA : 37 drugs, with 30% (11 drugs) Reimbursement : 85 total approvals, with 35% (30 approvals) Adbry (LEO Pharma) - PROs on itch reduction generated $90 million . Camzyos (Bristol-Myers Squibb) - Symptom relief PROs were key 2023: FDA : 49 drugs, with 33% (16 drugs) Reimbursement 95 total approvals, with 45% (43 approvals. Leqembi (Eisai/Biogen) - FDA approval and Medicare conditional reimbursement for Alzheimer’s disease leveraged PROs on cognitive function improvements, generating $200 million/ Jaypirca (Eli Lilly) - Patient-reported symptom relief supported FDA and payer decisions for mantle cell lymphoma. 2024:: 52 drugs, with 40% (21 drugs) . : 105 total approvals, with 55% (58 approvals) Example: Vowst (Seres Therapeutics) - PROs on quality-of-life improvements C. difficile infections, leading to $125 million in revenue. Example: Veozah (Astellas Pharma) - PRO data on symptom reduction in menopausal vasomotor conditions
CONCLUSIONS: The inclusion of PROs in FDA novel drug approvals increased from 18% in 2020 to 40% in 2024, while their influence on reimbursement decisions rose from 15% in 2020 to 55% in 2024.
Healthcare Price Transparency: Is It Working?
Session Type: Issue Panel
Topics: Health Policy & Regulatory, Clinical Outcomes, Economic Evaluation
Level: Introductory
For several decades, health policy makers have argued for greater transparency of prices and quality. The US Department of Health and Human Services mandated hospitals to post list prices, or chargemasters, for services as of January 1, 2019. As a result of legislation that began in early 2021, hospitals are required to post payer-specific negotiated charges and discounted cash prices in machine-readable files and to disclose these charges for 300 “shoppable” services, 70 of which were specified by the Center for Medicare & Medicaid Services (CMS). While some may hypothesize that elevated prices correlate with enhanced quality and improved patient outcomes, empirical evidence suggests otherwise. For example, the higher price of a pancreatectomy at one NCI-Designated Cancer Center is justified if the complication and readmission rates are substantially lower. Instead, Sankaran et al. join others and suggest that factors, such as geographic location and market dynamics, play a more significant role in price determination, overshadowing any potential link between price and quality. These findings hold profound implications for various stakeholders within the healthcare ecosystem. Patients, often tasked with navigating the complexities of healthcare pricing, must recognize that higher costs do not necessarily translate to better outcomes. Similarly, payers, armed with insights from this study, are urged to reevaluate their negotiation strategies and prioritize value-based contracting to ensure optimal resource allocation. The need for future research underscores the evolving nature of healthcare pricing dynamics and the imperative to continually reassess policy interventions. As we strive to optimize the intersection of affordability and quality in healthcare delivery, rigorous investigation and evidence-based policymaking remain paramount.
Moderator
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Schelomo Marmor, PhD
Minneapolis, MN, United States
Speakers
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Hari Nathan, MD
University of Michigan Medical School, Ann Arbor, MI, United States
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Andrew Loehrer, MD
Dartmouth Hitchcock Medical Center and Clinics, Lebanon, NH, United States
Lost in Translation: Disseminating Family Spillover Effects to Value and Affordability Assessment Decision-Makers
Session Type: Issue Panel
Topics: Health Technology Assessment, Health Policy & Regulatory, Patient-Centered Research
Level: Intermediate
ISSUE: There is increasing awareness of the impact of diseases and treatments on family members and informal (or unpaid) caregivers, or family spillover effects. The Centers for Medicare and Medicaid Services (CMS), State-based Prescription Drug Affordability Boards (PDABs), and the updated value assessment framework from the Institute for Clinical and Economic Review (ICER) have all cited the need and consideration of evidence on family spillover effects in affordability and value assessments. However, there is heterogeneity both in capturing and disseminating information on family spillover effects to inform both quantitative and qualitative components of value and affordability assessments. The purpose of this workshop is to share and debate approaches to collect, distill and communicate relevant evidence on family spillover effects to policy makers in a way to can be incorporated into value and affordability assessments. OVERVIEW: Workshop attendees will obtain a working knowledge of approaches for collecting and disseminating family spillover effects for health technology assessment bodies and policy makers conducting value and affordability assessments. R. Brett McQueen will lead the discussion and provide an overview of how ICER and PDABs may incorporate family spillover effects into value and affordability assessments. Jason Resendez will present key types of evidence messages on family spillover effects used by the National Alliance for Caregiving in advocacy activities. Stacey Kowal will present a quantitative example of the impact of family spillover effects on treatment-related economic and patient-centered outcomes from Spinal Muscular Atrophy (SMA). Finally, Andrew York will present how this information may be used in the policy arena through the Inflation Reduction Act or State PDABs. The discussion leader will engage with discussants and workshop attendees through ISPOR polling software to debate key approaches to include family spillover effects into value and affordability assessments.
Moderator
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Robert B McQueen, BA, MA, 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. He is active in ISPOR through contributions to short courses, workshops, issue panels, and research presentations.
Speakers
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Jason Resendez, BA
National Alliance for Caregiving, Washington, DC, United States
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Stacey Kowal, BS, MSc
Genentech, Alameda, CA, United States
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Andrew York, JD, PharmD
Maryland Prescription Drug Affordability Board, Baltimore, MD, United States
How Much Do We Already Know? Building a Stated-Preference Evidence Base for Regulatory, Product-Development, and Clinical-Decision Applications
Session Type: Workshop
Topics: Patient-Centered Research, Study Approaches, Methodological & Statistical Research
Level: Introductory
PURPOSE: Evaluations of multiple clinical-study data quantity and quality routinely are used to assess weight of evidence. The maturation of health-preference research is indicated by the number of published studies that have accumulated in some therapeutic areas. It is possible to begin thinking of preference data in terms of evidence bases, similar to clinical data. However, combining data from multiple preference studies poses several challenges, including differences in definitions of common attributes, inclusion criteria, sample sizes, and analytical techniques. This workshop will focus on how to access both published and primary study data and how to use meta-analytical and data-fusion methods to obtain consensus values for benefit-risk tradeoff preferences. Participants will learn how to assess the robustness of preference evidence bases to support regulatory, product-development, and clinical decision-making. DESCRIPTION: Workshop attendees will obtain a working knowledge of available methods for combining and applying data from multiple preference studies. The workshop will review a) how evidence bases are used for clinical data, b) how familiar methods can be adapted for preference applications, and c) how an evidence base was developed for a recent health application. Dr. Janssen will chair the session and introduce the topic in the context of clinical evidence-base construction and applications (10 min.), Jui-Chen Yang will discuss methods for harmonizing differences in study designs for different uses (15 min.), and Reed Johnson will illustrate how these methods were applied to combine primary inflammatory-bowel-disease preference data in a fusion model to estimate consensus maximum acceptable risk. (15 min.). Audience participation will include identifying problems and solutions for a case study in diabetes (20 min). This interactive and informative workshop will help patient-centered researchers make patient-preference evidence available for a wider range of decision-making applications.
Moderator
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Ellen M Janssen, BA, PhD
Janssen Research & Development, LLC, Baltimore, MD, United States
Speakers
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Reed Johnson, PhD
Duke Clinical Research Institute, Durham, NC, United States
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Jui-Chen Yang, MEM
Duke University, Durham, NC, United States
New Approaches to Sustainable Healthcare: How Can Environmental Impact Data Contribute to Whole Health?
Session Type: Issue Panel
Topics: Health Technology Assessment, Economic Evaluation, Health Policy & Regulatory
Level: Introductory
ISSUE: Climate change has the potential to disrupt our pursuit of whole health via multiple dimensions. It threatens to undo decades of progress in health and healthcare through adverse impacts on food and water security, frequency of extreme weather events, air quality, mental health, and communicable diseases. This highlights the direct impact of the environment on our health; it is a critical social determinant of health and component of whole health. As a result of these environmental impacts, health care needs will increase with climate change, further intensifying financial and capacity pressures on healthcare systems. This highlights the impact of environmental factors on healthcare, another pilar of whole health. Given emissions from healthcare systems contribute heavily to climate change and thus impact our pursuit of whole health, several questions must be explored: is there a role for considering environmental impacts within the concept of whole health? If so, how could and should this be operationalised (including, do we need to update the ISPOR value flower?)? What other changes would this mean for health economics and outcomes research? What are the potential unintended consequences?The objectives of the panel are to debate the inclusion of environmental impact in whole health and in value assessment, explore new ways of calculating and presenting the environmental and economic impact of new health technologies, and to discuss if and how these new results should be considered by healthcare decision makers internationally. OVERVIEW: Following a brief introduction to the issues by the moderator (Grace Hampson, Associate Director, Office of Health Economics, UK) (4 mins), the panel will debate the questions above. Panellists will each speak for 12 minutes, providing their perspectives on whether and how environmental impact data could be beneficial in our pursuit of whole health. 20 minutes will be reserved for audience discussion.
Moderator
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Grace Hampson
Office of Health Economics, London, United Kingdom
Speakers
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Andrew Briggs, DPhil
London School of Hygiene & Tropical Medicine, London, United Kingdom
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Deirdre DeJean
CDA-AMC, Ottawa, ON, Canada
Global Impact of JCA: Evaluating the Implications of the New EU HTA Regulation
Session Type: Workshop
Topics: Health Policy & Regulatory, Health Technology Assessment, Economic Evaluation
Level: Intermediate
PURPOSE:This workshop discusses the ripple effects of the EU health technology assessment (HTA) Regulation, with a key focus on the recently implemented Joint Clinical Assessment (JCA) on HTA in non-EU countries. It will feature perspectives from industry, HTA community, and international public health agency. DESCRIPTION:The initiation of EU JCA is a major topic within the HTA and payer communities in 2025. It was designed to enhance efficiency and harmonize the evaluation of new treatments across EU member states. While it garners significant attention in the EU, its influence is expected to extend globally, impacting HTA and payer decision-making in both established and emerging non-EU HTA markets.This workshop will evaluate the broader implications of JCA, including the harmonization of standards, development of HTA methodologies, and fostering of cross-border collaboration. The panel will provide an international perspective on the complexities, opportunities, and shifts arising from JCA implementation.Dr. Yeh (moderator) will set the stage with an overview of the JCA, emphasizing the challenges and opportunities associated with leveraging HTA evidence across borders. Dr. Vidal will discuss the impact of JCA on global pharmaceutical strategies, sharing findings from a recent survey examining its anticipated effects on the U.S. and 13 other non-EU countries. Dr. O'Rourke will bring insight from a global HTA community perspective on the EU HTA Regulation, including Joint Scientific Consultations, horizon scanning, and voluntary cooperation. He will also share lessons learned from JCA discussions with payers and policymakers worldwide. Ms. Canuto is representing the Pan American Health Organization. She will highlight how EU policies have influenced regulatory and reimbursement decisions in Latin America and the projected impact of JCA in the region.The workshop will include audience engagement/interaction to explore potential ripple effects further.
Moderator
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Danny Yeh, PhD
Aesara, Burlingame, CA, United States
Speakers
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Anouchka Vidal
Roche Products Ltd, Basel, Switzerland
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Brian O'Rourke, BSc, PharmD
Brian O'Rourke Health Care Consulting Inc., Ottawa, ON, Canada
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Vania Santos, MS
Pan American Health Organization, Washington, DC, United States
Health Care Resource Utilization in Real World Data
Session Type: Research Podiums
This session features studies examining resouce use and costs of care for a broad range of diseases in oncology, cardiovascular health, and cognitive health. Collectively they provide real-world evidence on the economic impact of these conditions to help guide resource allocation.
What is the societal cost of Alzheimer's Disease: A Cross-Sectional study in Malaysia
OBJECTIVES: Alzheimer’s disease is expected to bring huge impact towards resource use and economic consequences along with population ageing. This study aims to investigate the annual economic burden of Alzheimer’s disease along with underlying cost drivers.
METHODS: Patient with AD (PWAD) aged 65 and above accompanied with primary caregivers were recruited in 6 tertiary care hospitals. A structured interview was conducted to collect sociodemographic, clinical and resource use information using adapted questionnaire. Direct medical cost(DMC), direct non-medical cost (DNMC) and indirect cost (IDC) were annualised and categorized by severity level. Generalized linear models were applied to investigate predictors of costs.
RESULTS: From 135 patient-caregiver dyads, the annual economic burden of AD from societal perspective was USD 8618.83 ± USD 6740.79 per capita. The societal cost of severe PWAD (USD11943.19 ± USD6954.17) almost doubled those in mild AD (USD6281.10 ± USD6879.83). IDC was the major cost driver (77.7%) which represented the impact of productivity loss due to informal care. Besides disease severity, time spent in informal care, caregivers’ employment and use of special accommodation were predictors of AD cost. AD is estimated to impose a burden of USD1.9 billion in 2022, which represented 0.47% of Malaysia GDP.
CONCLUSIONS: This study provided real-world empirical cost estimates of AD burden in Malaysia. Informal care is a significant contributor to societal cost of AD. Novel interventions targeting AD progression delay could potentially lead to substantial cost savings for society.
Long Term Healthcare Costs and Utilization Among Patients with Non Obstructive Hypertrophic Cardiomyopathy
OBJECTIVES: There is limited evidence on the economic burden for patients with non-obstructive hypertrophic cardiomyopathy (nHCM). We analyzed cumulative healthcare resource utilization (HRU) and costs for patients with nHCM over a 5-year follow-up period.
METHODS: Retrospective cohort study of adults (≥18 years) diagnosed with nHCM (January 2013- December 2021) in Optum’s claims and electronic medical record data. Patients had ≥2 claims (first= index date) with a diagnosis code for nHCM (ICD-9/10) at least 30 days apart, 6-months pre index and 5-years follow-up. Cardiovascular (CV)-related cumulative HRU and costs (CPI 2022) were reported as mean [SD], including medical (ambulatory: office visit, outpatient [OP] visits; emergency room [ER] visit; inpatient admissions (IA); length of stay [LOS]; other medical costs) and pharmacy.
RESULTS: Among 3,652 nHCM patients (46% female; mean age 60.6 ± 16.2 years; 74.2% non-Hispanic White; 50% commercial insurance), 89.1% had an ambulatory visit (80.3% office visit, 53.5% OP visits) and 38.0% had a prescription fill. Almost a quarter of patients (23.2%) had an ER visit and 29.6% of patients had an IA over the 5-year follow-up. Cumulative 5-year mean ambulatory visits were 11.2 [13.9] (office visits: 7.3 [9.4], OP visits: 4.0 [8.6]), ER visits 0.5 [1.5], IA 0.7 [2.3], and LOS 7.8 [38.2] days. This translated to a cumulative 5-year total mean CV cost (medical + pharmacy) of $43,533 [$101,631]. Medical costs (total= $43,328 [$101,600]) included total mean ambulatory $9,703 [$25,527] (office visit: $1,447 [$3,752]; OP visit: $8,256 [$24,721]), ER visits $488 [$2,057], IA $27,298 [$88,547], and other medical costs $5,839 [$18,544]. Pharmacy cost over 5-years was $205 [$927].
CONCLUSIONS: Patients with nHCM experience significant HRU leading to increased costs of care, with almost a quarter of patients having an ER visit and IA. Innovative treatment options to reduce this economic burden and improve patient outcomes are urgently needed for patients with nHCM.
Healthcare Resource Utilization (HCRU) and Cost among Patients with Metastatic Melanoma Receiving Nivolumab + Relatlimab (NIVO+RELA) or Nivolumab + Ipilimumab (NIVO+IPI) in the Optum Database
OBJECTIVES: An indirect-treatment-comparison suggested NIVO+RELA may have similar efficacy and numerically reduced treatment-related adverse event rates compared with NIVO+IPI in patients with advanced melanoma. Despite these insights, there is no claims-based cost comparison between these treatments. Therefore, this analysis aimed to compare claims-based HCRU and costs among patients with metastatic melanoma treated with first-line NIVO+RELA or NIVO+IPI in Optum’s Clinformatics Data Mart, which contains 84 million patients from all 50 US states.
METHODS: Inclusion criteria included patients aged ≥12 years diagnosed with metastatic melanoma between March 18, 2022 (date of NIVO+RELA FDA approval), to March 31, 2024, and treated with first-line NIVO+RELA or NIVO+IPI. HCRU, calculated per patient per month (PPPM), included number of inpatient admissions, as well as outpatient, telehealth, and emergency room (ER) visits. Medical costs, calculated PPPM, included inpatient, outpatient, and ER costs. Drug costs included pharmacy- and physician-administered drugs. Separate multivariable generalized linear models compared HCRU and costs with NIVO+RELA versus NIVO+IPI and included the following covariates: age, sex, insurance type, geographical region, and Charlson Comorbidity Index.
RESULTS: We identified 108 patients treated with NIVO+RELA and 239 treated with NIVO+IPI, median age 78.5 and 70.0 years, respectively. Median follow-up [range] from diagnosis was 7.8 [3.0-18.0] months for NIVO+RELA and 8.8 [3.0-23.8] months for NIVO+IPI. Compared with NIVO+IPI, NIVO+RELA was associated with 12% lower total HCRU (RR, 0.88; 95% CI, 0.79-0.98), 33% lower medical costs (RR, 0.67; 95% CI, 0.54-0.82), and 18% higher drug costs (RR, 1.18; 95% CI, 1.02-1.36). Total medical-plus-drug costs were similar (RR, 1.01; 95% CI, 0.89-1.14).
CONCLUSIONS: In this claims-based comparison, these dual immunotherapy regimens had similar medical-plus-drug costs, suggesting the higher drug costs with NIVO+RELA versus NIVO+IPI may be offset by fewer HCRU and medical costs with NIVO+RELA. Limitations included a short median duration of follow-up and possible patient-selection biases in treatment choice.
Economic Burden of Recurrence among Patients with High-Risk Non-Muscle-Invasive Bladder Cancer who Received Bacillus Calmette-Guérin in the United States: A SEER-Medicare Study
OBJECTIVES: This study assessed the impact of recurrence on healthcare resource utilization (HCRU) and costs in patients with high-risk non-muscle-invasive bladder cancer (HR-NMIBC) who received Bacillus Calmette-Guérin (BCG).
METHODS: A retrospective cohort study was conducted using SEER-Medicare data (2007-2020). Patients with HR-NMIBC (TisN0M0, T1N0M0, or high-grade TaN0M0) who received BCG were stratified into recurrence (i.e., patients with NMIBC recurrence, muscle-invasive bladder cancer progression, or distant metastasis) and non-recurrence cohorts. In the recurrence cohort, the index date was defined as 30 days before the first recurrence to capture recurrence-related HCRU before recurrence; in the non-recurrence cohort, the index date was randomly assigned to match the time from BCG initiation to recurrence in the recurrence cohort. Post-index all-cause HCRU, including inpatient (IP) admissions, outpatient (OP) visits, emergency department (ED) visits and skilled nursing facility (SNF) visits, and associated costs (2023 USD) were summarized on a per-patient-per-month (PPPM) basis and compared between cohorts using a generalized linear regression model.
RESULTS: The study included 2,164 and 2,586 patients in recurrence and non-recurrence cohorts, respectively (median follow-up: 23.82 and 26.23 months). Significantly higher proportions of patients incurred ≥1 all-cause HCRU in recurrence vs. non-recurrence cohorts (IP: 66.2% vs. 47.9%, OP: 99.6% vs. 97.1%, ED: 54.6% vs. 45.2%, SNF: 20.7% vs. 18.0%; all p<0.05). Among patients who incurred HCRU, mean numbers of OP and ED visits PPPM were significantly higher in the recurrence cohort (OP: 2.93 vs. 1.88, ED: 0.17 vs. 0.12; both p<0.05). All-cause PPPM healthcare costs were also higher in the recurrence cohort (total: $5,058 vs. $2,207; IP: $2,472 vs. $980; OP: $1,548 vs. $504; ED: $80 vs. $41, SNF: $270 vs. $177; others: $687 vs. $505; all p<0.05).
CONCLUSIONS: Recurrence following BCG was associated with significantly higher HCRU and costs, highlighting the need for more effective therapies that may potentially reduce economic burden.
From General to HEOR-Specific: Transforming LLMs Into Reliable Research Tools
Session Type: Other Breakout Session
Topics: Study Approaches, Health Technology Assessment, Economic Evaluation
Level: Advanced
Large Language Models are powerful tools that have transformed how we interact with information, but foundational models are not designed for conducting scientific research. Given the critical implications of HEOR research on healthcare decision-making, understanding both the capabilities and limitations of these LLM is paramount for their effective use. This session presents a structured approach, divided into two parts. The first part examines the fundamental capabilities and limitations of LLMs in HEOR contexts, discussing critical considerations such as data quality, reproducibility, and validation requirements. The second part features an interactive demonstration comparing basic LLM usage versus advanced research design through a real-world example of disease burden analysis. Audience members will help define the research context, allowing for immediate illustration of key concepts. This session will particularly benefit researchers, analysts, and decision-makers who are interested in leveraging AI tools while maintaining scientific integrity in their work. Participants will leave with practical knowledge of how to design and implement LLM-enhanced research workflows that meet HEOR's rigorous methodological standards. Proposed Session Flow (rough timing): Introduction (5 mins) Part 1: LLMs in HEOR Research (15 mins) - Core capabilities and limitations - Specific challenges in HEOR applications - Best practices and safeguards Part 2: Interactive Demonstration (25 mins) - Case study: Disease burden analysis - Audience input on context/parameters - Comparison of: - Basic LLM approach (direct ChatGPT use) - Advanced research design (structured prompts, function calls, etc.) - Discussion of quality differences and implications Q&A (15 mins)
Moderator
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J. Jaime Caro, MD
Evidera, Lincoln, MA, United States
Speakers
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Apoorva Ambavane, MPH
Evidera, London, United Kingdom
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Baris Deniz, MSc
GlaxoSmithKlein, Chapel Hill, NC, United States
Baris Deniz is a seasoned expert in Health Economics and Outcomes Research (HEOR) and market access, with over 20 years of experience. His expertise spans integrated evidence strategies, health economic evaluations, evidence synthesis, and technology assessments. Baris has a deep understanding of the strategic role HEOR plays in bridging regulatory approvals with patient access, while generating robust evidence to demonstrate the value of medical interventions. Recently, his work has been in exploring innovative technologies and their applications in the HEOR domain to drive more effective outcomes and data-driven decision-making. He is the founder of AIde Solutions LLC, which focuses on leveraging GenAI in HEOR and scientific research.
What Causal Inference Teaches Us About the Limitations of Indirect Treatment Comparisons for Health Technology Assessment
Session Type: Workshop
Topics: Methodological & Statistical Research, Health Technology Assessment, Study Approaches
Level: Intermediate
PURPOSE: Indirect treatment comparisons (ITCs) are essential in HTA when direct head-to-head trials are unavailable. However, ITCs are susceptible to biases threatening their validity. This workshop will introduce attendees to the key principles of causal inference and treatment effect heterogeneity and explain how these principles can improve our understanding of the limitations of ITCs within the framework of HTA. Participants will learn why ITCs are “essentially observational findings across trials” (Cochrane Handbook) and how to critically evaluate their validity.
DESCRIPTION: Dr. Siebert will introduce the session giving an overview on the key principles of causality and causal diagrams (8min) followed by presentations from the three speakers and discussion/questions (10min). The audience will be asked (real-time polling) to consider when, and to what extent, evidence from ITCs analyses should be considered by HTA agencies. Dr. Chatton will begin by establishing a formal definition of causal effects using the potential-outcomes framework, emphasizing counterfactuality and the estimand as central concepts. He will review the crucial assumptions necessary for valid causal inference (exchangeability, positivity, consistency and noninterference) and the main types of causal estimators available within the context of an externally controlled single-arm trial (14min). It’s often acknowledged that “the choice of effect measure may have a considerable impact on [one’s] analysis, and also on the degree of observed heterogeneity” (EUnetHTA). Through the lens of causal inference, Dr. Webster-Clark will explain how the choice of effect measure also determines the set of variables upon which one must adjust to maintain external validity (14min). Dr. Campbell will demonstrate how these principles translate to ITCs, clarifying the concepts of transportability, non-collapsibility, the relevance of marginal, conditional and population-average estimands, and the impact of failing to adjust for prognostic variables (14min).
Moderator
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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.
Speakers
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Arthur Chatton, PhD
Université Laval, Québec, QC, Canada
Arthur Chatton is a postdoctoral researcher in Biostatistics at the Department of Social and Preventive Medicine of Laval University, QC. His research focuses on using machine learning in both causal inference and dynamic prediction in health. Through his research program, Dr. Chatton contributes to evaluating, comparing, and developing new biostatistical methods.
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Michael Webster-Clark, PharmD, PhD
McGill University, Montreal, QC, Canada
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Harlan Campbell
University of British Columbia, Rossland, BC, Canada
How Should Health Economists and Health Policymakers Measure the Costs of Inequality?
Session Type: Issue Panel
Topics: Economic Evaluation, Health Technology Assessment
Level: Intermediate
ISSUE: Traditional cost-effectiveness focuses on efficiency, relegating equity to the background. In recent years, growing interest in equity has encouraged researchers to measure the cost of inequality, but important issues remain unsettled. Nearly a century ago, John Harsanyi showed that societal decisions respect the “Pareto principle” – that what is good for society must also be good for all its citizens -- only if social policy maximizes a weighted sum of individual utilities. However, decades later, Peter Diamond, another Nobel Laureate economist, pointed out that this utilitarian approach can produce unfair outcomes, even though it respects individual preferences. This tradeoff binds on health economics, because summing up utilities means summing up QALYs. When QALYs are simply summed, unequal QALY distributions fail to affect social welfare. This counter-intuitive property has caused health economists to propose and debate multiple paths forward: 1) distributional cost-effectiveness analysis (DCEA) departs from utilitarianism, and the Pareto principle, by layering “inequality aversion” onto individual preferences; 2) “rank-dependent” welfare functions enable utilitarian approaches by threading a needle that considers only those policies that preserve the relative rank of each individual in society; and 3) Generalized Risk-Adjusted Cost-Effectiveness (GRACE) allows for utilitarian approaches that nonetheless imply costs to inequality.
OVERVIEW: Lakdawalla will provide an overview of the challenges faced by health economists quantifying inequality (5 mins). Jansen will present the case for DCEA that incorporates inequality-aversion (15 mins). Davis will compare and contrast rank-dependent welfare approaches with GRACE for measuring the costs of inequality (15 mins). Phelps will make the case for GRACE as a strategy for utilitarian approaches to measuring inequality (15 mins). There will be ten minutes allotted for fielding of questions and discussion.
Moderator
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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.
Speakers
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Ian J Davis, MA
University of Southern California, Los Angeles, CA, United States
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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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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.
What’s Next? Year 1 Learnings of Evidence Planning for IRA Drug Price Negotiation
Session Type: Issue Panel
Topics: Health Policy & Regulatory
Level: Intermediate
ISSUE: Two years following the passing of the Inflation Reduction Act, the Centers for Medicare and Medicaid Services (CMS)?released?the maximum fair prices (MFPs) for the 10 Part D drug selected for Medicare drug price negotiation in August of 2024. These prices will go into effect on January 1, 2026. CMS’s detailed rationale for each negotiated MFP is not expected until closer to the March 1, 2025 deadline. However, key learnings can be considered based on a number of factors. This issue panel will explore the initial outcomes and insights from the first year of Medicare drug price negotiations. OVERVIEW: Taylor Schwartz will provide an overview of the results of the first year of Medicare price negotiation and summarize the value evidence manufacturers can submit for Year 2 negotiation. Michael Ciarametaro will provide an analysis of Year 1 MFPs, including the likely drivers of MFPs for each product, nuances due to key product characteristics, and what impact this could have on the market. Peter Neumann will discuss the importance of therapeutic alternative selection and analyze the potential weighting of negotiation factors, including the value evidence submitted by manufacturers. Russ Montgomery will highlight key considerations for manufacturers moving into future years of negotiation and describe best practices and timing for price negotiation preparation.
Moderator
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Taylor T Schwartz
Avalere, Valencia, CA, United States
Speakers
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Peter Neumann, ScD
Tufts Medical Center, Boston, MA, United States
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Michael Ciarametaro, BS, MA, MBA
Avalere Health, Washington, DC, United States
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Russ Montgomery, PhD
GSK US, Nashville, TN, United States
10:30 AM - 1:30 PM
Poster Session 1
Session Type: Research Posters
11:15 AM - 1:00 PM
Lunch Service (Exhibit Hall)
Session Type: General Meeting
As you enjoy your lunch in the Poster and Exhibit Hall, seize the opportunity to engage in meaningful conversations with fellow attendees. Take this time to exchange ideas, forge new partnerships, or simply enjoy casual conversations. Provided by ISPOR.
11:30 AM - 12:15 PM
Oncology Poster Tour
Session Type: Research Posters
This tour will take place during Poster Session 1, Poster will be hung from 10:30 AM - 1:30 PM.
Posters featured in this tour:
PT1: Developing a Budget Impact Shinney Application to Assess the Financial Implications of Implementing Organized Cancer Screening Programs in Countries With Limited Resources: Breast Cancer as an Example
PT2: Survival Analysis in Breast Cancer Patients Treated With Targeted Therapies and Conventional Therapies in the US: A Comparative Real World Study
PT3: An Artificial Intelligence (AI)-Assisted Systematic Literature Review (SLR) of the Economic Burden in Metastatic Pancreatic Adenocarcinoma: A Proof-of-Concept Study
PT4: A Systematic Review on Economic Evaluations of Comparisons Between CAR-T Therapies in Relapsed or Refractory Diffuse Large B-Cell Lymphoma
PT5: Disparities in Access to CAR-T Treatments: Evidence From 100% Medicare Fee-For-Service and Medicare Advance Claims Data
PT6: Comparison of Meaningful Score Difference Estimates From Longitudinal Item Response Theory and Anchor-Based Methods
HEOR Impact Cases Poster Tour
Session Type: HEOR Impact Cases
This tour will take place during Poster Session 1, Poster will be hung from 10:30 AM - 1:30 PM.
How to Use Real-world Data Across Regions to Gain Regulatory Approval: A Case Study
Problem Statement: A new Marketing Authorization Application (MAA) received a negative opinion from the Committee for Medicinal Products for Human Use (CHMP). Two study sites were considered to have serious issues with conformance standards to Good Clinical Practice Guidelines. Excluding data from the sites rendered the primary endpoint non-significant. The manufacturer could not conduct another trial.
Description: This is a case study featuring the use of US RWD to secure the approval of a new drug in Europe (EU). The revised MAA incorporated data from one pivotal clinical trial, data from the FDA FARES database, and a US effectiveness and cardiovascular safety study. The execution of a robust real-world study in this instance addressed a critical data gap, ultimately leading to the EU approval.
Lessons Learned: The case study is one of the first examples of the use of RWE to support approval of a new medical intervention in Europe for a disease that is not considered to have high unmet need. Lessons learned include: (1) adhere to regulatory guidance for the given country/region in planning RWE study; (2) Engage your target audience early for input; (3) Prepare a pre-specified protocol and analysis plan, including power estimation, validated endpoints and analyses plan to minimize biases due to confounding; (4) Register in CT.gov for transparency, (5) Consider variations and generalizability in disease epidemiology and clinical practice guidelines for cross-regional comparisons.
Stakeholder Perspective: RCTs are the gold standard for assessment of clinical efficacy and safety but have limited generalizability and cannot fully characterize safety of new medications. Formal guidance on use of RWE in regulatory applications and broader availability of RWD provide the opportunity for accelerated drug approvals. This example demonstrates how data from a real-world study together with other evidence can be used cross-regionally in lieu of an additional RCT when conducting a study is not logistically or ethically feasible.
Accelerated Access Pathways at Canada’s Drug Agency: Evaluating Progress and Future Directions in HTA
Problem Statement: Canada’s Drug Agency’s accelerated access pathways, including Rolling Reviews, Time-Limited Recommendations (TLR), and the PACES (Pharmaceuticals with Anticipated Comparable Efficacy and/or Safety) pathway, are designed to streamline drug evaluations and ensure timely access to essential therapies. As pilot initiatives, these pathways aim to address systemic challenges in the market access landscape, maintain rigorous standards, and align with global efforts to modernize health technology assessments (HTA). Their long-term viability, fairness, and potential for broader application remain key questions.
Description: These accelerated pathways enable earlier evidence submission and simplify the review process, emphasizing efficiency and collaboration across the reimbursement continuum. Rolling Reviews and TLR are aligned with the "Target Zero" campaign to eliminate delays between regulatory approval and reimbursement recommendations. PACES focuses on accelerating reviews for simple, low-risk pharmaceuticals, reallocating resources to complex files while maintaining efficiency. This session highlights insights from Canada's Drug Agency on the pathways’ design and impact, pCPA on pricing and negotiation strategies, and a patient advocate on equity considerations and timely access from a patient advocate’s perspective. Key topics include their influence on collaboration among stakeholders, metrics for success such as time-to-listing and cost-effectiveness, and necessary structural or policy changes to support scalability and permanence.
Lessons Learned: While the pathways have demonstrated potential for improving timeliness and resource allocation, challenges remain in scaling these initiatives, ensuring fairness, and building trust. Metrics for evaluating success require refinement, emphasizing the balance of patient outcomes, cost-effectiveness, and equity.
Stakeholder Perspective: This is presented from multiple perspectives, including policymakers analyzing scalability, payers assessing pricing efficiency, and patient advocates addressing equity and access to therapies. These insights seek to guide the development of sustainable pathways that meet the needs of all stakeholders.
Payment Models for Sickle-Cell Disease Gene Therapies in Colorado Medicaid: Real-World Data Analysis
Problem Statement: Colorado Medicaid faced the challenge of covering high-cost gene therapies for sickle-cell disease (SCD) while ensuring sustainable, value-based spending. The introduction of exagamglogene autotemcel (exa-cel) and lovotibeglogene autotemcel (lovo-cel) required a comprehensive evaluation of potential payment strategies.
Description: To inform this decision, Colorado Medicaid analyzed real-world data from the Health Care Policy & Financing database, focusing on the costs associated with severe SCD patients from 2018 to 2023. This analysis evaluated several payment models proposed by the Center for Medicare and Medicaid Innovation under the Gene Therapy Access Model. These models included outcome-based agreements (OBAs), volume-based rebates, and guaranteed rebates over a six-year contract period, with scenarios accounting for different criteria related to vaso-occlusive events and treatment durability. Three-state Markov models were employed to compare the costs of standard-of-care (SoC) treatments with those of gene therapies, both with and without the proposed payment models. The findings indicated that gene therapies resulted in a negative cumulative balance, averaging -$2.11M for exa-cel and -$3.00M for lovo-cel per patient over six years compared to SoC. However, OBAs could potentially save Medicaid approximately $260K (UI $88K-$772K) per patient on average for exa-cel, and $367K (UI $122K-$1,111K) for lovo-cel. Volume-based and guaranteed rebates also showed potential savings, but the impact varied based on contract duration and the effectiveness of gene therapy.
Lessons Learned: The study found that achieving budget neutrality over six years is unlikely because the costs associated with the SoC are relatively low. However, innovative payment models could improve value-based spending by linking high therapy costs with potential health outcomes. The significance of real-world data was emphasized in identifying eligible patient populations and determining the actual costs of SoC. Furthermore, the analysis pointed out that the duration of contracts has a significant impact on financial outcomes.
Stakeholder Perspective: Colorado Medicaid.
The clinical and financial benefit of adopting negative pressure would therapy to reduce surgical site complications after cesarean section
Problem Statement: We evaluated the clinical and financial value of using negative pressure wound therapy (NPWT) in patients with a BMI greater 30 kg/m2 who undergo cesarean section at our quaternary care hospital.
Description: Questions remain about the clinical effectiveness of NPWT versus standard care in women with high BMI post-cesarean section. We conducted a meta-analysis of 10 randomized controlled trials to evaluate (i) the impact of NPWT vs standard care on clinical outcomes in patients with a BMI greater than 30 kg/m2 who undergo cesarean section (ii) whether the level of negative pressure (-80 mmHg vs -125 mmHg) impacts outcomes. We also conducted a budget impact analysis. We found moderate quality evidence indicating that NPWT reduces surgical site infections (SSI) in patients with BMI greater than 30 kg/m2 undergoing cesarean section; however, there was no evidence of benefit for other outcomes such as hospital readmissions and reoperation. Low quality evidence indicated no difference in level of pressure on SSI. In terms of budget impact, the use of the NPWT device at $200/patient would result in an additional $40,000 per year to treat 200 patients. The ICER indicates that it would cost $11,173 to prevent one additional case of an SSI by using this device in this population. Given the very low rate of surgical site infection (1.47% to 2.8%) post-caesarean section at the MUHC, and that there is no evidence of effectiveness of the device on more serious complications and readmissions, we issued a recommendation that the opportunity for impact on clinical benefit and cost savings is minimal.
Lessons Learned: Although moderate-quality evidence indicates that NPWT could reduce surgical site infections in this population, it is important to look at local burden of illness, which demonstrated that the low rate at our hospital did not justify investing in this technology.
Stakeholder Perspective: Government-affiliated hospital
Navigating Uncertainty Within a Re-evaluation Process: Epidemiological Approach vs Real-World Data in a Budget Impact Analysis for CAR T-cell Therapies in Quebec
Problem Statement: In an ever-changing environment, health technology assessment (HTA) agencies must adapt their methods to inform decision-makers regarding fair and rapid access to innovative therapies, even in the face of low levels of evidence. In this regard, the Institut national d’excellence en santé et services sociaux (INESSS) introduced a new type of reimbursement recommendation in 2018. This mechanism allows exceptional access to innovative therapies in contexts where clinical data are limited or immature, with a requirement for re-evaluation when deemed appropriate by INESSS. This case study examines the methodology used by INESSS for two CAR T-cell therapies (Kymriah and Yescarta) and the challenges faced when re-evaluating their budget impact analysis (BIA).
Description: A reanalysis of the initial BIA, conducted in 2019 using an epidemiological approach, was performed. The listing of these therapies, in addition to the follow-up requirements inherent to this new reimbursement mechanism, enabled certified centers to collect real-world data (RWD) over the years. This facilitated the conduct of a retrospective BIA with up-to-date data, which was also corroborated by sales data from the IQVIA Canadian Drugstore and Hospital Purchase Audit database. Overall, the initial estimations for Yescarta were accurate, but the market uptake was slower than anticipated. In contrast, the initial estimations for Kymriah were significantly overestimated. Indeed, various discrepancies emerged when comparing the two analyses, each based on a different approach, allowing INESSS to assess the differences and collaborate with Quebec clinicians to elucidate the underlying reasons.
Lessons Learned: In the absence of more robust data, the epidemiological approach is often considered the method of choice to conduct BIAs and inform decision-makers. However, this approach is subject to uncertainty and partly based on assumptions derived from clinicians’ input. A retrospective analysis using RWD provides more accurate estimates and should be favored in a re-evaluation context whenever possible.
Stakeholder Perspective: Government
Using AI to reduce carbon footprint in the hospitals
Problem Statement: Globally Healthcare sector produces 2 gigatons of CO2 globally making it 5th largest emitter of greenhouse gases. There is an urgent need for healthcare establishments in UAE to innovate to reach net zero emissions by 2050, or before EHS’s sustainability efforts led us to build an AI solution to measure and reduce our carbon footprint.
Description: The AI solution proactively identifies such appointments that can be converted to e-clinic benefitting both the patient & environmentThis novel AI solution was developed in alignment with the UAE Net Zero 2050 strategy to help EHS & other healthcare establishments in UAE become the greenest healthcare providers globally. It is the first innovation in the region to use technology to reduce carbon footprint while continuing to increase health services quality and improve patient outcomes. The first objective was to design an Artificial Intelligence algorithm to proactively review and then suggest the in-clinic visits to be converted to telemedicine visits based on multiple factors - patient history, past appointments, clinical condition, type of service etc.Secondly, the EHS Intelligence platform analyzes large data related to patient visits and uses the algorithm to calculate the related carbon footprint of each patient travelling to the EHS facility and benchmark it to global standards. EHS plans to scale up the AI solution to concentrate on surgical areas' C footprint, which accounts for 24% of all emissions in healthcare. The model was used to determine strategies to reduce total emission in surgical areas and assess the carbon footprint of each individual surgery, which is currently estimated to be 6 to 814 kg CO2.
Lessons Learned: 1. Having a Clear Vision 2. Importance of Education and Training 3. Building Strong Partnerships 4. Measure and Communicate Impact Regularly
Stakeholder Perspective: It was well received by internal and external stakeholders
11:45 AM - 12:15 PM
RWE Generation: Blueprint for Drug Development and Commercialization
Topics: Real World Data & Information Systems
Level: Introductory
11:45 AM - 12:45 PM
ISPOR Good Practices Task Force on Patient Reported Outcomes (PROs) in Prospective Real-World Studies: Preliminary Recommendations
Session Type: Forums
Topics: Patient-Centered Research, Real World Data & Information Systems, Clinical Outcomes
Level: Intermediate
Global regulators, health technology assessors, and policy makers have indicated that patient reported outcome (PRO) data can provide valuable information on the effectiveness, safety and tolerability of new health technologies from the patient perspective. Existing PRO guidance focuses on the use of PRO measures in a controlled trial setting. However, little guidance exists regarding the use of PROs in real world (RW) studies. An ISPOR task force is in the process of developing a good practices report for use of these measures in RW Studies.
This session will present the task force’s findings thus far focused on realising the value of PROs in RW studies and the preliminary recommendations regarding study population, data quality, RW-PRO implementation, treating patients as partners, data analysis, technology and validity of PRO measure in RW context. Speakers will present case examples and consider the methodological and logistical requirements of data to be acceptable to different stakeholder groups - discussed from research, regulatory, and industry standpoints, respectively.
ISPOR community feedback is an essential step in the optimisation of an ISPOR expert consensus-developed good practices reports. Feedback will be sought on the preliminary recommendations. Audience examples and comments on the use of real-world patient reported outcomes (RW-PROs) data in regulatory and payer submissions are encouraged. This session is designed for researchers, payers, regulators, technology assessors, and industry professionals, offering a unique opportunity to explore the intersection of PROs, real-world evidence, and patient-centered research.
Moderator
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Konrad Maruszczyk, MSc
Centre for Patient-Reported Outcome Research (CPROR), University of Birmingham, Birmingham, United Kingdom
Speakers
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Onyeka Illoh
US Food and Drug Administration, Silver Spring, MD, United States
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Jessica Roydhouse, PhD
Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia
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Tom Keeley, PhD
GSK, London, United Kingdom
Driving Evidence-Based Medicine Forward with Generative AI (GenAI)
Topics: Methodological & Statistical Research, Study Approaches
Level: Intermediate
Enhancing HTA: Surrogate Endpoints, Statistical Standards, and Their Impact on Patients
Session Type: Forums
Topics: Clinical Outcomes, Health Technology Assessment, Methodological & Statistical Research
Level: Intermediate
This session presents the rationale, objectives, and preliminary recommendations from the ISPOR Statistical Evaluation of Surrogate Endpoints for Health Technology Assessment (HTA) Decision-Making Task Force. Attendees will gain insights into existing and novel statistical methods for demonstrating clinical and economic value when surrogate endpoints are used for drug licensing, and how surrogate endpoints affect clinical decisions, patient access and outcomes, and strategies to mitigate uncertainty.
Surrogate endpoints can be measured more quickly than target outcomes, reducing trial duration and facilitating earlier regulatory and HTA approvals. This, in turn, may accelerate patient access to potentially life-changing therapies. However, despite the availability of guidelines on use of surrogate endpoints from numerous HTA agencies, few HTA submissions explicitly provide evidence linking the treatment effect on surrogate endpoints to target outcomes. Lack of robust evaluation of surrogate endpoints can lead to increased uncertainties in HTA decision-making and delays to patient access.
In this dynamic session, Dr. Heeg (6 min) will introduce the session and its objectives. Dr. Thorlund will discuss statistical approaches for evaluating surrogate endpoints, addressing prediction challenges, uncertainty, and emerging tools for less-than-ideal data scenarios. Professor. Lee will explore how surrogate endpoints are integrated into health economic modeling, detailing how they support predictions of treatment effects and their corresponding uncertainties. Dr. Stefani will discuss the broader implications for clinicians and patients when drugs are approved based on surrogate endpoints, weighing the decision to prescribe these novel therapies, despite uncertainty about their impact on target outcomes.
The session will conclude with Dr. Heeg moderating a Q&A segment focused on the task force’s recommendations. This session is designed for researchers, payers, regulators. assessors, and industry professionals, offering a unique opportunity to explore the intersection of surrogate endpoints, statistical innovation, and patient-centered decision-making.
Moderator
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Bart Heeg, PhD
Cytel, Rotterdam, Netherlands
Speakers
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Dawn Lee, MSc
University of Exeter Medical School, Exeter, United Kingdom
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Kristian Thorlund, MSc, PhD
McMaster University, Hamilton, ON, Canada
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Stephen D Stefani, MBA, MD
UNIMED/RS, Porto Alegre, Brazil
Navigating the Path to COA Label Claims: Overcoming Challenges and Seizing Opportunities: A Success Story in Tenosynovial Giant Cell Tumor
Topics: Patient-Centered Research, Methodological & Statistical Research, Study Approaches
Level: Intermediate
Integrating the Value of Diagnostic and Prognostic Information With Efficiency Enhancements in Healthcare Systems
Session Type: Forums
Topics: Health Service Delivery & Process of Care, Medical Technologies, Health Technology Assessment
Level: Intermediate
The objective of this forum is to explore the intersection of diagnostic and prognostic information with capacity-enhancing innovations in healthcare systems. By combining these two critical areas, we aim to create awareness and facilitate discussions on how effective capacity-enhancing innovations including diagnostics can improve patient pathways, influence treatment outcomes, and ultimately enhance system efficiency. Our approach will particularly focus on the impact of early diagnosis on patient care and healthcare efficiency metrics.
The significance of integrating and valuating diagnostic and prognostic information into healthcare delivery is paramount in contemporary practice. Efficient inclusion of diagnostic and prognostic tools and innovative medical technologies can streamline patient care—from diagnosis through treatment, prognosis and monitoring—significantly impacting efficiency-related key performance indicators. However, the transportability, measurement, and recognition of these efficiency gains by Health Technology Assessment (HTA) bodies, providers, and procurers is often hindered by organizational readiness and sustainability measures in the existing healthcare environment. By examining case studies and expert insights, we will highlight best practices and challenges associated with realizing, assessing, and valuating these benefits.
Our panel will feature the perspectives of stakeholders spanning various sectors of the healthcare ecosystem, including healthcare providers, industry representatives, and HTA bodies. Discussions will address the specific roles of medical devices and diagnostics in optimizing patient pathways, addressing the challenges associated with identifying and measuring relevant efficiency dimensions, and the potential for integrated care approaches. A particular emphasis will be placed on how efficient practices can be achieved through early diagnoses and the restructuring of healthcare professional deployment and how those should be measured and considered in technology assessment to ensure timely adoption and valuation.
Moderator
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Belinda Mohr, PhD
Medtronic, Phoenix, AZ, United States
Speakers
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Sudha Kutty, BSc, MBA
Canada's Drug Agency, Toronto, ON, Canada
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Artem T Boltyenkov, MBA, PhD
Siemens Healthcare Diagnostics Inc., Lexington, SC, United States
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Vincent De Guire, PhD, DEPD, CSPQ
Maisonneuve Rosemont Hospital, Montreal, QC, Canada
1:30 PM - 2:30 PM
Student Network Session: Bridging Evidence and Action - Multistakeholder Collaborations for Value-Based Healthcare Decision-Making
Session Type: Forums
Topics: Health Technology Assessment
Level: Introductory
This ISPOR 2025 Student Network Event will explore and discuss how collaboration among diverse stakeholders can drive the adoption of value-based healthcare models and improve healthcare decision-making. As healthcare systems evolve, there is a growing need for innovative approaches that prioritize patient outcomes, cost-effectiveness, and sustainability. This session will delve into how Health Economics and Outcomes Research (HEOR) serves as a critical bridge between evidence generation and actionable decision-making. The expert panelist from academia, industry, and healthcare policy will discuss the challenges and opportunities in aligning the interests of payers, providers, regulators, and patients to create more value-driven healthcare solutions. Attendees will gain insights into how these collaborations can shape policy, drive healthcare reforms, and support the implementation of value-based care models. This interactive discussion will be designed to foster a dialogue among students, early-career professionals, and experienced ISPOR members eager to learn how multistakeholder collaborations can advance healthcare decision-making and outcomes.
Moderator
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Safalta Khadka, MS
West Virginia University, Morgantown, WV, United States
Speakers
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Kate W Williams, BSc, MSc, PhD
Acaster Lloyd Consulting, London, United Kingdom
Kate is a director of patient-centred outcomes research at Acaster Lloyd Consulting Ltd. She has over 15 years’ experience in patient-centred research in academia, consulting and the pharmaceutical industry. Her main research interests are in the design and conduct of qualitative and mixed methods research studies to capture the patient voice. She also has expertise in the development of clinical outcome assessment (COA) strategies for clinical studies. She has experience across a range of therapeutic areas, with a particular interest and expertise in rare diseases and neurological conditions. Kate holds a PhD in Psychology from University College London. She has more than 30 peer-reviewed publications and has presented at multiple conferences. Kate is currently Associate Editor at the Journal of Patient-Reported Outcomes and is Chair-Elect of the ISPOR Clinical Outcome Assessment Special Interest Group.
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Robert B McQueen, BA, MA, 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. He is active in ISPOR through contributions to short courses, workshops, issue panels, and research presentations.
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Shawn Du, PhD
Janssen Scientific Affairs, LLC, Horsham, PA, United States
1:45 PM - 2:45 PM
The Power and Pitfalls of AI in Health Data Analysis
Session Type: Research Podiums
The session highlights the strengths and challenges of using artificial intelligence (AI) in the analysis of health data. Topics presented will cover the predictive power of AI in risk identification and outcome estimation and the impact of AI hallucinations on prognostic model performance.
Boosting Predictive Power: Thoughtfully Unleashing the Potential of Machine Learning In Real-World Healthcare Outcome Estimation
OBJECTIVES: Machine learning (ML) has been proposed as a more accurate approach to predictive modeling in health economics and outcomes research (HEOR) compared to traditional methods (TM). However, supporting evidence comparing the two approaches is limited by inconsistent reporting of results, biased comparisons, and incorrect validation procedures. A rigorous comparison of ML vs TM is needed to better understand the added value of ML in real-world data (RWD) studies.
METHODS: We evaluated the performance of ML vs TM for predicting annual healthcare costs (typically challenging to predict using TM) across multiple dimensions, including sample size and the number of baseline independent variables, in cohorts of multiple sclerosis (MS) and breast cancer (BC) patients identified in the IQVIA Pharmetrics® Plus closed-claims database. For ML, we applied XGBoost and deep neural nets with hyperparameter tuning, and for TM we employed linear regression with restricted cubic splines for continuous independent variables. Performance was assessed using 10-fold cross-validation, quantified by R2 and the slope of the calibration curve.
RESULTS: ML outperformed TM at large sample sizes using conventional HEOR variables for prediction, while performance of the models was comparable at smaller sample sizes. Adding variables based on clinical classification of claim codes improved ML predictive performance. Using splines improved performance for the MS cohort but less so for the BC cohort in the TM analysis. XGBoost offered the best predictive performance among ML methods.
CONCLUSIONS: ML approaches performed equally well as TM in smaller sample sizes and improved cost prediction in larger samples. Potential efficiencies in study conduct were observed with ML. Researchers should balance the potential gains in predictive performance against the interpretability of results when considering ML for a given study. This work allows us to make recommendations for optimal ML use in HEOR.
Evaluating Fairness Across Machine Learning Algorithms in Health Models Incorporating Race/Ethnicity as Predictors
OBJECTIVES: Incorporating socioeconomic factors, such as race and ethnicity, in health prediction models remains a topic of debate. While previous studies have assessed the fairness of including social factors, the role of different machine learning algorithms and hyperparameter optimization has been underexplored. This study examines the tradeoffs between model performance and fairness across various algorithms and scenarios in health predictive modeling.
METHODS: We examined two cases: (1) predicting cardiovascular diseases using the National Health and Nutrition Examination Survey data from 2007 to 2018 and (2) predicting adverse pregnancy outcomes through U.S. live birth certificate from 2016 to 2023. For each case, we compared general and race-specific models across three scenarios: (1) race-neutral (RN), which excludes race/ethnicity as a predictor; (2) race-sensitive (RS), which includes race/ethnicity; and (3) RN with race-stratified during cross-validation. We evaluated the performance of eight algorithms, each with Bayesian hyperparameter optimized and nested resampling to ensure generalizability. The model performance was assessed using the areas under the curve (AUC). The 95% confidence intervals (95% CI) were constructed with bootstrap.
RESULTS: In the first case, 4,942 individuals (41.4% non-Hispanic White, 27.0% Hispanic, 22.3% non-Hispanic Black, 9.3% Other) were included; the second case comprised 24,765,394 single live births (53.2% non-Hispanic White, 25.5% Hispanic, 13.9% non-Hispanic Black, 7.5% Other). Regarding models built for the whole sample, among two cases and all scenarios, XGBoost consistently demonstrated the highest AUC (0.82, 95% CI 0.80, 0.85), while K-nearest neighbors (KNN) showed the lowest AUC (0.64, 95% CI 0.62, 0.67). However, XGBoost exhibited significant variability, with the poorest performance among Black individuals, while KNN showed minimal variation across racial groups.
CONCLUSIONS: Fairness evaluations in predictive modeling require consideration beyond simple algorithm choice and tuning. To improve decision-making, researchers should optimize hyperparameters and assess fairness-performance trade-offs across diverse algorithms and racial/ethnicity subgroups, ensuring robustness and generalizability in predictive models.
The Impact of Hallucinations in Synthetic Health Data on Prognostic Machine Learning Models
OBJECTIVES: The application of synthetic data generation (SDG) as a privacy-preserving mechanism for sharing health data is increasing. Hallucinations are commonly observed in text-generating models but may also occur in tabular SDG. Hallucinations can erode trust in the utility of the generated data. This study investigates (1) the hallucination rate (HR) during tabular SDG, and (2) whether hallucinations deteriorate the performance of downstream prognostic models.
METHODS: We used 6,354 dataset variants derived from 12 large real world health datasets by increasing their complexity. From these variants, training datasets were sampled for SDG using 7 different generative models. The hallucination rate (HR) was defined as the proportion of non-existent synthetic records in the population. Downstream utility was assessed by training a gradient boosted decision tree (GBDT) classifier on the synthetic data and testing it on a real holdout dataset.
RESULTS: The median HR was 89.6% (IQR 66.0-99.3%). The odds for hallucinations increased significantly with higher complexity (fixed effect) across all datasets (random effects). At minimum complexity, sequential decision trees had the smallest odds (1.49, 95%CI [0.39, 5.70]) and the variational autoencoder the highest odds (14.24, 95%CI [2.12, 95.54]); and complexity was positively associated with HR, from 1.03 in Bayesian Networks, 95%CI [1.01, 1.05], to 1.16 in Normalizing Flows, 95%CI [1.11, 1.22]. The effect of hallucinations on downstream utility was inconsistent across the generators with no effect in 6/7 generators and a negative effect in the Generative Adversarial Network (-0.02, 95%CI [-0.03, -0.02]).
CONCLUSIONS: Our findings suggest that hallucinated records can form a major portion of synthetic data with higher HR as complexity increased. The rate of increase in HR varied among generators with Normalizing Flows at the upper end. Hallucinations by Sequential Trees, Adversarial Random Forests, Variational Autoencoders, Normalizing Flows and Bayesian Networks did not impact the performance of GBDT.
Leveraging Real-World Data and NLP to Identify At Risk Metabolic Dysfunction Associated Steatohepatitis in the General Population
OBJECTIVES: Metabolic Dysfunction Associated Steatotic Liver Disease (MASLD) affects approximately 25% of the global population, with the highest prevalence reported in the Middle East (32%). A subset of these patients develop Metabolic Dysfunction-Associated Steatohepatitis (MASH), and those with a Metavir Fibrosis-score>= F2 are at increased risk of adverse liver-related health outcomes, including cirrhosis and hepatocellular carcinoma (HCC). Despite its clinical and public health significance, MASLD screening remains inconsistent, and diagnosed cases are frequently under-documented in electronic health records (EHRs). With emerging therapeutic options, identifying undiagnosed or undocumented MASH cases has become a critical priority in real-world clinical settings. This study aimed to leverage real-world data (RWD) and develop an advanced natural language processing (NLP) model to identify patients with at-risk MASH through radiology reports and laboratory test results.
METHODS: Abdominal radiology reports and Fibrosis-4 (FIB-4) index scores (Age, ALT, AST, Platelet count) from 2020-2024 were analyzed, sourced from a leading state-mandated health provider in Israel. Reports were labeled using multiple validation sources, including expert radiologist reviews, coded diagnoses, age, and laboratory values. A machine learning-based NLP classification model was developed using the Briya© computational platform (Briya NLP). Model performance was evaluated using area under the curve (AUC), sensitivity, specificity, and accuracy metrics.
RESULTS: The study analyzed 132,124 radiology reports from 78,741 unique patients. External validation demonstrated high model performance, with sensitivity and specificity exceeding traditional diagnostic methods (specific metrics pending). Implementation of the Briya NLP model significantly increased at-risk MASH case identification compared to traditional diagnostic codes alone.
CONCLUSIONS: This RWD-driven NLP based approach offers an efficient, scalable solution to identifying under-documented at-risk MASH cases in routine clinical practice. This automated system could enhance earlier intervention through lifestyle modifications and targeted therapies, ultimately improving patient outcomes in real-world healthcare settings.
Medicare Price Negotiation of Part B Drugs: Implications for Provider Reimbursement and Commercial Spillover
Session Type: Spotlight
Topics: Health Policy & Regulatory, Health Technology Assessment
Level: Intermediate
ISSUE: How will the negotiation of high-cost biologics and other physician-administered drugs (Part B) prices by Medicare starting in 2026 impact practice and clinic economics and private sector prices?
OVERVIEW: Starting in early 2026, physician-administered (Part B) drugs will be selected for Medicare price negotiation, with implementation in 2028. This will generate major changes in provider reimbursement of drugs, both in Medicare and the commercial sector. Before negotiation, Medicare reimbursed providers for physician-administered drugs 106% of Average Sales Price (ASP). For negotiated drugs, ASP will be replaced by the negotiated price. Because the negotiated price is expected to be lower than ASP, provider mark-ups will decrease. Provider mark ups are also likely to decrease in the commercial sector. This is because: 1) ASP is widely used for private sector provider reimbursement; and 2) it is expected that Medicare sales (at the negotiated price) will be factored in the estimation of ASP for negotiated drugs. The result will be spillover into the commercial health insurance markets.
Moderator
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Sean D Sullivan, PhD
University of Washington, Seattle, WA, United States
Speakers
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Inma Hernandez, PhD
UCSD, La Jolla, CA, United States
Inmaculada (Inma) Hernandez is a pharmaceutical health services researcher and a Professor with tenure at the University of California, San Diego. She has authored more than 140 scientific articles. Her research has focused on the study of medications for stroke prevention and the examination of drivers of drug prices. She has made major contributions to improving transparency in the drug pricing and reimbursement system. She currently serves as the National Academy of Medicine Fellow in Pharmacy.
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Kristi Martin
Camber Collective, Washington, DC, United States
Kristi Martin provides policy expertise and strategic counsel to advance meaningful health policy that focuses on improving the health and wellbeing of people while delivering practical policy solutions. She draws on more than 20 years of experience working in the public sector, with private sector clients, and in philanthropy. Most recently, Kristi served as the chief of staff and senior advisor to the deputy administrator in the Center for Medicare at the Centers for Medicare & Medicaid Services (CMS). While serving at CMS, she played a significant role advancing regulatory policy in Medicare and implementing the Inflation Reduction Act -- the most significant changes to Medicare Part D since its inception. Kristi facilitated and coordinated the implementation of the Medicare Drug Price Negotiation Program, which successfully negotiated the first set of drug prices under the Medicare Drug Price Negotiation Program that will save people with Medicare and the program billions of dollars on prescription drug costs as well as contributed to a wide range of other policy and operational initiatives that have made Medicare better than ever. Kristi previously was the Vice President for Health Care at Arnold Ventures where she led the philanthropy's prescription drug pricing portfolio and was the Managing Director of Waxman Strategies' health practice where she worked alongside Congressman Henry Waxman to drive outcomes in health policy. She has previously served several years in the U.S. Department of Health and Human Services, Office of Personnel Management, and Government Accountability Office. As a senior advisor in the Obama administration's Office of Health Reform, she had primary oversight responsibility for the coordinated and timely implementation of cross-cutting departmental public health and prevention initiatives under the Affordable Care Act, including addressing the rising cost of drugs and setting up the women's preventive services initiative. She received her bachelor's and master's degrees in health communication from the University of Kentucky and a Master of Public Administration from George Washington University.
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Ramesh Srinivasan, PhD
McKesson Corporation, Coppell, TX, United States
Patient-Centricity in Oncology: From PROs to Endpoints
Session Type: Research Podiums
Decisions about oncology treatments require balancing possible clinical benefit against potentially severe side effects. Patient-reported outcomes (PROs) provide important information on the patient experience during treatment, but approvals are often based on other endpoints. This session will cover studies in oncology with PROs as well as assessments of other endpoints to improve patient-centricity in oncology.
The Landscape of Current Policy and Health Authority Positions on Intermediate Endpoints (IEs) for Clinical Outcomes in Oncology
OBJECTIVES: While rates of new drug approvals based on IEs have increased recently, approaches for IE validation are inconsistent. This study reviewed the current landscape of guidance from regulatory bodies, health technology assessment (HTA) agencies, payers, and other policy-makers on IEs in oncology.
METHODS: We conducted a literature search using Embase (1974 to 10-29-2024), supplemented by manual searches of prespecified organizations in the Americas, Europe, and Asia-Pacific regions, for guidance or policy on IEs.
RESULTS: We identified guidance from >40 organizations on IE use and/or surrogacy validation. Other relevant documents pertained to approval trends. Regulatory bodies lacked detailed guidance on IE validation methods. Most HTA agencies only minimally referenced the need for significant/established relationships between IEs and target clinical outcomes, while a few agencies provided more detailed guidance. The National Institute for Health and Care Excellence (NICE; UK) recommended a Bayesian meta-analytic approach with take-one-out cross-validation. The Institute for Quality and Efficiency in Health Care (IQWiG; Germany) provided guidance for IE validation, which was adapted for a validation framework by the National Authority of Medicines and Health Products (INFARMED; Portugal). Some HTA agencies only cited other organizations, such as the European Network for Health Technology Assessment (EUnetHTA), which reported a 3-level hierarchy of evidence. Specific correlation thresholds for IE validation were noted by IQWiG, EUnetHTA, European Commission, and INFARMED.
CONCLUSIONS: Detailed guidance on IE validation is insufficient and inconsistent across most organizations. A minority of HTA agencies, including IQWiG and NICE, provide more comprehensive frameworks. Nevertheless, the majority of guidance is limited and not disease-specific. Recommendations on validation criteria remain limited, and thresholds for correlations between IEs and specific clinical outcomes are often stringent or undefined. To enhance decision-making, it is crucial to align on robust validation approaches and use correlation thresholds that consider tumor type, disease context, and clinical consequences for patients.
Patient Reported Adverse Psychosocial Outcomes and Identification of Predictive Factors in Those with Lymphoma or Chronic Lymphocytic Leukemia - An analysis of the Lymphoma Coalition's 2024 Global Patient Survey
OBJECTIVES: Adverse psychosocial outcomes (APSO’s) are an under-reported phenomenon amongst patients during the cancer journey. The diversity of APSO’s extends well beyond anxiety and depression which are commonly captured in many patient reported outcome measures (PROM’s). In this study, we examined the prevalence of 19 different APSO’s experienced by patients with lymphoma or chronic lymphocytic leukemia (CLL) and explored associations with demographics and various experiential aspects of the cancer journey to provide evidence for the refinement of future PROM instruments.
METHODS: A cross-sectional survey was employed to gather patient reported-outcomes (PRO) from a global sample of patients with lymphoma or CLL in early 2024. Age, biological sex, relapse status, time since last treatment, and time since diagnosis were used as predictors to model the prevalence of 19 APSO’s utilizing nominal logistic regression.
RESULTS: The sample contained 6073 patient responses from 67 countries with a median age of 64 [18-92] and 60% were female. The most prevalent APSO’s amongst the respondents were fear of progression or relapse (47%), fear of being immunocompromised (38%) and anxiety (34%). We assessed depression as a separate PRO from anxiety and found only 52% of those reporting anxiety also reported depression. Of all predictors examined, increasing age was significantly associated (p<0.0001) with a reduction in all but one APSO, fear of being immunocompromised (p=0.4).
CONCLUSIONS: These results suggest that the mosaic of APSO’s experienced by patients with lymphoma and CLL are diverse and extend solely beyond depression and anxiety. Our results also support the hypothesis that the prevalence of APSO’s are amplified younger patients. In the development and refinement of novel PROM’s, it will be imperative to incorporate a more diverse representation of APSO’s to truly reflect the experiences of this vulnerable population. Finally, the results suggest younger patients be assessed for APSO's to enable timely implementation of intervention measures.
Changes in Patient Reported Outcomes Relative to the Time of Disease Progression in Non-Small Cell Lung Cancer
OBJECTIVES: Although progression free survival is a common primary endpoint in cancer clinical trials, it is not universally accepted as being patient relevant. This study is the first to use pre- and post-progression patient-reported outcome (PRO) data to assess how symptoms and functioning change in relation to the time of radiographic disease progression in non-small cell lung cancer (NSCLC).
METHODS: Data were derived from the Phase 3 MARIPOSA (NCT04487080) and MARIPOSA 2 (NCT04988295) trials evaluating amivantamab-based treatment regimens in adult patients with EGFR-mutant advanced NSCLC. The study included patient-reported lung cancer symptoms (measured by NSCLC-SAQ) and global health, physical function, and role function (measured by EORTC QLQ-C30). Analyses included 590 participants in the MARIPOSA study that experienced disease progression and 240 participants across the MARIPOSA and MARIPOSA 2 studies that experienced intracranial disease progression. Longitudinal change in PRO scores was evaluated with piecewise mixed effects modeling using the time of progression as the transition point.
RESULTS: Across all four PRO measures and all treatment groups, PRO score trajectories showed increased worsening in the months leading up to progression, worsening at the time of progression, and trends in a worsening direction after progression. In the MARIPOSA study, all fixed effect time estimates were significant (p<.01), and the extent of worsening was particularly pronounced for the subgroup of patients who experienced intracranial progression. Results from MARIPOSA 2 were consistent with the findings from MARIPOSA showing associations between intracranial progression and worsening in PROs.
CONCLUSIONS: This study provides evidence that radiographic disease progression, including intracranial progression, is associated with worsening of patients’ NSCLC symptoms and health-related quality of life. The findings support prolonging time to disease progression and development or progression of brain metastases as patient relevant endpoints in NSCLC.
Development and Prospective Evaluation of the Bladder Utility Symptom Scale (Utility): A Novel Tool to Measure Utilities and Quality of LIfe in Bladder Cancer Patients
OBJECTIVES: Bladder cancer (BCa) and its treatments significantly impact quality-of-life (QOL). To facilitate comparative-effectiveness research, a tool to measure QOL and utilities in these patients is required. The Bladder Utility Symptom Scale-Psychometric (BUSS-P) is a preference-based psychometric instrument that has undergone rigorous internal and external validation, and can be used across all phases of BCa. We created an algorithm to calculate utilities from the BUSS-P instrument and evaluated these in a prospective study.
METHODS: In time-tradeoff(TTO) interviews, 200 BCa patients and 200 community members provided utilities for scenarios derived from the BUSS-P. Patients were proportionally recruited from non-muscle-invasive(NMIBC), muscle-invasive(MIBC) and metastatic participants to represent all disease phases. Bayesian generalized linear multilevel models were used to estimate the impacts of the ten BUSS-P attributes. An algorithm was developed to calculate utilities from the BUSS-P responses (BUSS-Utility). We then prospectively evaluated the BUSS-U, and compared it against the EQ-5D-5L and EORTC-QLU-C10D.
RESULTS: Of 400 participants, 167 community members and 155 patients (70-NMIBC,53-MIBC,32-metastatic) completed the TTO exercises with adequate comprehension, providing 3,288 unique BUSS-P scenario valuations. The final BUSS-U derivation model had weighted correlation coefficients between predicted and observed utilities of 0.733 and 0.734 in community and patient groups, respectively. The BUSS-U was then completed by 406 BCa patients at three Canadian academic centres (Toronto, Vancouver, McGill), representing 17 unique health states. BUSS-U utilities discriminated health states, and followed EQ-5D-5L and EORTC-QLU-C10D scores.
CONCLUSIONS: The new BUSS-U is a BCa-specific utility instrument grounded in TTO methodology and applicable across the BCa care spectrum. Our study has created a standard reference set of BCa utilities for economic evaluations, decision-modeling, and policy work. Given the improved discrimination for health-related QOL when transitioning across clinically-significant health states, and the inclusion of BCa-specific health domains, we suggest using the BUSS to measure QOL and utilities in BCa patients for future research.
Bridging the Evidence Gap: Integrating Real-World Data With Randomized Controlled Trials
Session Type: Workshop
Topics: Real World Data & Information Systems, Study Approaches, Health Policy & Regulatory
Level: Intermediate
PURPOSE: This workshop will explore how integrating Real-World Data (RWD)—such as registry data and other observational sources—with data from Randomized Controlled Trials (RCTs) can address critical research and regulatory questions that RCTs alone cannot answer. Combining these complementary data sources enables researchers to generate deeper insights into treatment effectiveness, expand findings to broader patient populations, and improve decision-making across diverse settings. DESCRIPTION: This workshop will feature dynamic, short-format illustrations of how merging RWD with RCT data can overcome traditional trial limitations and enhance evidence generation. Presentations will highlight diverse RWD from the USA and the Nordics, demonstrating how global data sources can enrich insights and applicability across populations. Ms. Grip will present on creating external control arms to generate critical additional evidence for RCTs, focusing on a cytarabine trial in acute myeloid leukemia linked with high-quality RWD (10 min). Dr. Young will discuss methods for integrating RWD with RCTs to extend trial results to real-world populations, illustrated by a case study on anticoagulation during percutaneous coronary intervention (10 min). Dr. Dixon will share practical considerations for planning, designing, and executing external control arms, drawing on industry experience across multiple therapeutic areas. (10 min).Dr. Ritchey will conclude the session with a 30-minute interactive discussion and Q&A. To foster engagement, interactive polling will capture audience perspectives, guide the conversation, and prioritize topics in real time. This approach will provide participants the opportunity to contribute their insights and directly shape the discussion. This symposium will be valuable to researchers, regulators, and industry professionals seeking to leverage integrated data to address complex research questions and improve regulatory decision-making.
Moderator
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Mary Beth Ritchey, MSPH, PhD
CERobs Consulting, LLC, Philadelphia, PA, United States
Speakers
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Emilie Toresson Grip, MSc
Quantify Research, Stockholm, Sweden
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Matthew Dixon, PharmD, PhD
Bristol Myers Squibb, New Hope, PA, United States
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Kirk Geale, MSc, PhD
Quantify Research, Stockholm, Sweden
Kirk Geale is the CEO of Quantify Research (www.QuantifyResearch.com), the Nordic’s leading provider of real-world evidence (RWE), health economics and outcomes research (HEOR) to the pharma industry. His unique combination of Nordic research expertise, global HEOR consulting practice, and business acumen gives him a unique perspective on the transformative role of Nordic RWE in the global healthcare landscape.
Kirk received his PhD from the Department of Public Health and Clinical Medicine at Umeå University (Sweden). He is an affiliated researcher at Bispebjerg Hospital (Denmark), a graduate of Stanford University's Graduate School of Business (USA) and the Swedish Interdisciplinary Graduate School in Register-Based Research (Sweden). He holds an MSc in Economics from Lund University (Sweden) and a B.Comm in Management Economics in Industry and Finance from the Gordon S. Lang School of Business and Economics at Guelph University (Canada).
Accelerating the Adoption of Generative AI in HEOR: Lessons From Early Adopters
Session Type: Issue Panel
Topics: Health Technology Assessment, Methodological & Statistical Research
Level: Introductory
ISSUE: Generative Artificial Intelligence (AI) has the potential to revolutionize HEOR by enhancing efficiency, driving innovation, and informing data-driven decisions. However, many HEOR professionals are uncertain about how to effectively leverage this emerging technology. Common challenges include limited awareness of generative AI’s capabilities, organizational barriers to adoption, and navigating complex ethical and regulatory landscapes. Early adopters of generative AI have begun to overcome these hurdles, demonstrating that effective strategies exist to integrate these tools into routine practice. OVERVIEW: This panel, convened by the ISPOR Generative AI Working Group, will highlight successful approaches for deploying generative AI in HEOR. Moderated by Dr. Jag Chhatwal, the discussion will begin by examining the current opportunities and limitations of generative AI within HEOR. Dr. Turgay Ayer will discuss recent advancements in technology, and showcase practical applications and lessons learned in applying generative AI to HEOR. Ms. Ipek Stillman will discuss concrete steps to accelerate adoption, including addressing organizational hesitancy, building interdisciplinary teams, and promoting self-education to develop internal AI expertise. Dr. Rachael Fleurence will then outline the regulatory environment and discuss how health technology assessment (HTA) bodies view the use of AI in HEOR, providing guidance on aligning with decision-maker expectations and maintaining transparency and trust.By exploring case studies, practical roadmaps, and actionable guidance, attendees will learn how to overcome common implementation barriers, gain leadership support, and successfully integrate generative AI into HEOR workflows.
Moderator
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Jag Chhatwal, PhD
Harvard Medical School / Massachusetts General Hospital, Wilmington, MA, United States
Dr. Chhatwal is an associate professor at Harvard Medical School and Director of the Institute for Technology Assessment at Massachusetts General Hospital. Dr. Chhatwal has co-authored over 120 original research articles and editorials in peer-reviewed journals. His work has been cited in leading media outlets, including CNN, Forbes, National Public Radio, New York Times, and Wall Street Journal.
Since 2011, Dr. Chhatwal has taught several workshops and short courses on decision modeling and AI at the ISPOR. He is a member of ISPOR AI Working Group. He also serves as an associate editor of Value in Health and is serving as the guest editor for special issues on AI in Value in Health.
Speakers
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Turgay Ayer, PhD
Value Analytics Labs, Boston, MA, United States
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Rachael Fleurence, MSc, PhD
National Institutes of Health, Bethesda, MD, United States
Dr Fleurence is a Senior Advisor at the National Institutes of Health where she is working on launching a national initiative to eliminate Hepatitis C in the United-States. Dr Fleurence is also affiliated with the National Institute of Biomedical Imaging and Bioengineering where she works on advances in Artificial Intelligence and Machine Learning. Dr Fleurence currently co-leads the ISPOR Task Force on the suitability of EHR data for Health Technology Assessments. Previously, Dr Fleurence served as a senior health advisor in the Biden-Harris White House, Dr. Fleurence received a BA from Cambridge University (United Kingdom), an MA in business management from ESSEC-Paris (France), and an MSc and PhD in health economics from the University of York (UK).
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Ipek Ozer Stillman, MBA, MSc
Takeda, Cambridge, MA, United States
Integrating the Patient Voice: Successful Models of Continuous Engagement Science That Advance Data Science and Drug Development
Session Type: Workshop
Topics: Patient-Centered Research, Health Policy & Regulatory, Study Approaches
Level: Introductory
PURPOSE: The PATIENTS Program defines continuous engagement science (CES) as a systematic approach focused on fostering trust and authentic collaboration while ensuring patients’ voices are heard and valued. It emphasizes a measurable approach to sustain ongoing engagement between researchers and patient communities, co-creating innovative solutions. This workshop will describe CES strategies to enhance trustworthiness in health economic and outcomes research (HEOR) studies among patients, the public and other decision-maker communities. It will highlight practical methods for integrating patient and community perspectives to develop new solutions. Participants will identify challenges and potential solutions for sustainable, enterprise-wide CES. DESCRPTION: DeJuan Patterson, a PATIENTS Professor and credible messenger, will open the session by introducing the Credible Messenger Approach, a framework for leveraging trusted patient advocates and community leaders to enhance participation, build trustworthiness, and foster authentic engagement in HEOR (10 mins). • Dr. O’Sullivan will describe a series of FDA-funded cancer studies where a community advisory board (CAB) of patients, care providers, and researchers co-developed study protocols and guided prioritization of topics and approaches to inform future regulatory studies (10 mins). • Dr. Yanni will discuss how CES and active integration of the patient perspective in decisions during drug development and delivery can be transformative and improve value in health care across diverse settings and populations (10 mins). • The audience will participate in two hands-on exercises (20 mins). The first exercise guides identifying patients, credible messengers, and community influencers to serve as CAB members, with a focus on how their unique perspectives enhance participation and engagement. The second exercise demonstrates how patient engagement can help to avoid medicine development failures and improve uptake of novel therapies, with examples.
Moderator
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C. Daniel Mullins, PhD
University of Maryland Baltimore, Baltimore, MD, United States
C. Daniel Mullins is a Professor at the University of Maryland School of Pharmacy. He is Founder and Executive Director of the University of Maryland PATient-centered Involvement in Evaluating effectiveNess of TreatmentS (PATIENTS) Program, a community-academic partnership for patient-driven research. Dr. Mullins has received approximately $25 million in funding as a Principal Investigator from AHRQ, FDA, NCI, NHLBI, NIA, NIMHD, the Patient-Centered Outcomes Research Institute (PCORI) and various patient advocacy organizations and pharmaceutical companies. At the University of Maryland Baltimore (UMB), he received the Dr. Patricia Sokolove Outstanding Mentor Award and the Dr. Martin Luther King Jr. Faculty Diversity Award. He was named Researcher of the Year at UMB and was awarded a University System of Maryland Wilson H. Elkins Professorship. At ISPOR, he has served as Editor-in-Chief of Value in Health since 2010 and received the Marilyn Dix Smith Leadership Award in 2017.
Speakers
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DeJuan Patterson
Bridge Advisory Group LLC, Baltimore, MD, United States
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Meaghan Krohe, PhD
Astellas Pharma US, Northbrook, IL, United States
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Amy K O'Sullivan, PhD
Ontada, Boston, MA, United States
Collecting Actionable Evidence on the Full Range of Economic Impacts From Patients and Caregivers: Advancing “Whole Person” HTA
Session Type: Workshop
Topics: Patient-Centered Research, Economic Evaluation, Health Policy & Regulatory
Level: Intermediate
PURPOSE: To educate health economics and outcomes research (HEOR) professionals on applying the principles of the Patient-Centered Economic Impacts Research Framework using methods such as patient experience mapping to collect and incorporate the full range of economic impacts patients and caregivers face into holistic health technology assessment (HTA).
DESCRIPTION: HTA traditionally focuses on clinical outcomes and direct costs, but the full range of financial impacts on patients and caregivers are often overlooked. This interactive session aims to demonstrate to the HEOR community ways to include patient-centered costs beyond direct costs and inform prioritization of the most critical economic impacts for future research. We will invite the HEOR community, patients, and caregivers to discuss these impacts and how to measure them in both qualitative and quantitative research approaches.
Ms. Ushma Patel will provide an overview of the Patient-Centered Economic Impacts Research Framework, work to date implementing the framework through virtual workshops with stakeholders, as well as her own patient and caregiver perspective of economic impacts.
Dr. Elisabeth Oehrlein will provide an overview of qualitative patient experience mapping, including how it can be used in conjunction with quantitative methods to uncover the hidden burdens of patients and families when facing a serious healthcare condition or treatment.
Next, Elisabeth will model the patient experience mapping methodology with Ms. Tina Aswani-Omprakash to explore her lifelong struggles navigating Crohn’s disease and other chronic conditions.
Finally, Ms. Stacey Kowal will illustrate how patient productivity impacts and spillover effects to informal caregivers are currently being measured in Alzheimer’s disease research.
The audience will be invited to participate via polls and group discussion questions about strategies for collecting actionable evidence and prioritizing the most important patient-centered economic impacts.
Moderator
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Ushma Patel, MSPH
Center for Innovation & Value Research, Apex, NC, United States
Ushma Patel, MSPH, PMP is a public health professional, patient advocate, and strategic leader with almost 20 years of health policy, patient engagement, and qualitative research experience. Ushma is passionate about authentic patient collaboration and empowering women to trust their own instincts. As a preeclampsia and stroke survivor, and mother of a child with a rare disease, she shares her story on a state and national level with patients, caregivers, and providers to spread awareness and hope for moms and children with genetic conditions. She is currently the Director of Patient Engagement at the Center for Innovation & Value Research where she oversees the Patient Advisory Council, leads the Patient-Centered Economic Impacts project, and ensures the patient voice is captured in all Center research initiatives.
Speakers
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Elisabeth Oehrlein, MS, PhD
Applied Patient Experience, LLC, Washington, DC, United States
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Tina Aswani Omprakash, MPH
South Asian IBD Alliance, New York, NY, United States
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Stacey Kowal, BS, MSc
Genentech, Alameda, CA, United States
Preventive Genomic Services: Trial- and Model-Based Approaches to Estimating Health and Economic Outcomes
Session Type: Other Breakout Session
Topics: Methodological & Statistical Research, Clinical Outcomes, Economic Evaluation
Level: Intermediate
Purpose: To introduce preventive genomic testing and the evidentiary needs of policymakers; and to address methodological challenges to generating this evidence via clinical studies and health economic models.
Description: Genomic testing is increasingly available to inform disease prevention despite limited understandings about patient preferences about it and uncertainties about its benefits, harms, and cost-effectiveness. Addressing evidence gaps will require methodological innovations given the rarity of genetic disorders and the unique complexities of genomic information.
The Global Economics and Evaluation of Clinical Sequencing Working Group (GEECS) was founded to improve methods for assessing the value of genomic medicine. GEECS members will introduce preventive genomic testing and the evidentiary needs of policymakers (10 minutes, Jansen). They will then discuss Prevent Gene, a project that provides genetic risk information about cardiovascular disease and breast cancer, to summarize challenges and solutions to collecting data about patient preferences (13 minutes, Marshall). A pilot randomized trial of preventive genomic testing of adults, the MedSeq Project, will be discussed to address how outcomes for the initial 6-month period were selected and to address how they corresponded with patient outcomes 10 years later (13 minutes, Christensen). Afterwards, GEECS members will discuss the PreEMPT Model, a simulation model developed to estimate the lifetime outcomes and cost-effectiveness of newborn genomic sequencing to address selection of primary and secondary endpoints and methodological challenges and solutions (13 minutes, Smith). The session will conclude with a discussion between audience and panel members, with an emphasis on comparing alternative approaches to economic evaluations of preventive genomic testing (10 minutes). This session will benefit health economic and outcomes researchers, policymakers, and payers who make decisions about supporting genomic testing.
Moderator
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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
Speakers
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Deborah Marshall, PhD
University of Calgary, Calgary, AB, Canada
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Kurt Christensen, PhD
Harvard Pilgrim Health Care Institute, Boston, MA, United States
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Hadley S Smith, PhD
Harvard Pilgrim Health Care Institute, Brookline, MA, United States
HEOR Meets Investing - Why Are Banks and VCs Collaborating With Health Economists?
Session Type: Workshop
Topics: Health Policy & Regulatory, Economic Evaluation, Patient-Centered Research
Level: Intermediate
PURPOSE: While HEOR has broad applications across the healthcare industry, its role in life science investing has historically been limited. In recent years, there has been a growing trend of HEOR professionals collaborating with investment banks and venture capitalists (VC). Why are banks and VCs thinking about health economics? Can health economics inform investment decisions? Can HEOR methods and thinking improve return on investment for life science investors? This panel convenes a group of health economists collaborating with various financial institutions to explore these questions. Each panelist will discuss the potential applications of HEOR in life science investing and outline opportunities and challenges for collaborations among the different sectors. DESCRIPTION: Meng Li will introduce the panelists, and highlight the growing synergy between HEOR and finance. She will briefly discuss how different types of HEOR research can be used to inform investment decisions. The discussion will then feature insights from three panelists:Will Canestaro will offer a perspective of a seed-stage healthcare and biotech investor, sharing how HEOR methods are being used to inform investment decisions and how he has built programs to incorporate HEOR methods in decision-making. Richard Xie will focus on the applications of HEOR methods to inform investment in later-stage companies (e.g., phase 2 or 3), and support policy and communication initiatives of investors. Melanie Whittington will discuss the differences in the modeling approach, timing, and frequency of updates between the financial sector and the value assessment sector. Each panelist will share how HEOR is being applied in their current positions and discuss opportunities for additional synergies between the health economic and financial sectors. The workshop will end with an interactive Q&A, allowing the audience to directly engage with panelists to discuss the emerging intersection between HEOR and investing.
Moderator
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Meng Li, MS, PhD
Tufts Medical Center, The Center for the Evaluation of Value and Risk in Health, Boston, MA, United States
Speakers
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William Canestaro, PhD
Washington Research Foundation, Seattle, WA, United States
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Richard Xie, PhD
RA Capital Management, Newton, MA, United States
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Melanie D Whittington, MS, PhD
Leerink Center for Pharmacoeconomics, Boston, MA, United States
Melanie Whittington is the Managing Director and Head of the Leerink Center for Pharmacoeconomics where she leads pharmacoeconomic evaluations of in-development and recently approved pharmaceuticals and studies incentives for innovation. She is also a Senior Fellow at the Center for the Evaluation of Value and Risk in Health (CEVR) where she advises on CEVR projects related to value assessment, economic modeling, and CEVR databases.
Measuring and Evaluating Important Health Concepts: Are Patient-Reported or Device Acquired Data Better?
Session Type: Issue Panel
Topics: Medical Technologies, Clinical Outcomes, Methodological & Statistical Research
Level: Intermediate
ISSUE: Rapid technological advancements in digital health technologies are revolutionizing the way health is measured. The increased use of sensor-based measures in drug development may enhance endpoint precision and provide an objective measurement source with minimal patient burden. Sensors are particularly suited to measuring data that may be difficult for patients to articulate, such as sleep patterns, mobility, or heart rate. Digital measures can provide high-resolution, continuous data, enabling new insight of disease or treatment response. In contrast, patient-reported outcomes (PROs) are necessary for assessing subjective experiences, such as pain and fatigue; concepts that rely on individual perception and are critical to understanding the impact of disease and treatment on quality of life. The panel will explore the critical question of if and when sensor-based data offer advantages over PROs in clinical research and drug development. OVERVIEW: Dr. Floden will provide a 10-minute overview of the uptake of sensor technologies and the current landscape of incorporating the patient-voice in clinical trials, outlining key opportunities, challenges, and importance of aligning measures with meaningful health outcomes, regulatory expectations, and patient-centered priorities. Dr. Roydhouse will present on PRO collection in clinical research outside of clinical trials, and the feasibility of digital measurement. Dr. Potter will present on digital measures in clinical trials and the incorporation of patient voice. Panelists will be asked to respond to a series of thought-provoking questions :• Can sensor-based data replace PROs in certain contexts, or will PROs remain the gold standard for capturing the patient experience?• Are we at risk of over-relying on objectivity of sensors while undervaluing the nuanced subjectivity captured by PROs?• How do we ensure that sensor-based measures are valid and reliable in capturing meaningful aspects of health, and how does this compare to the rigor of PRO validation?
Moderator
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Libby Floden, MPH, PhD
Evinova, Waltham, MA, United States
Speakers
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Jessica Roydhouse, PhD
Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia
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Andrew Potter, BA, PhD
US Food and Drug Administration, Bethesda, MD, United States
2:45 PM - 3:15 PM
Wednesday Afternoon Coffee and Connect (Exhibit Hall)
Session Type: General Meeting
Head to the exhibit hall to refuel, recharge and connect with fellow attendees and exhibitors over a steaming cup of coffee. Provided by ISPOR.
3:15 PM - 4:15 PM
Climbing the HEOR Career Ladder: Strategies for Success in an Era of Change
Session Type: Forums
Topics: Organizational Practices
Level: Introductory
Since its inception nearly three decades ago, ISPOR has been instrumental in furthering its members’ training and development in the tools and techniques of health economics & outcomes research (HEOR). ISPOR short courses, educational webinars, and online resources predominantly focus on HEOR methodology, with content ranging from beginner-level fundamentals to advanced topics on the frontiers of innovation. ISPOR’s Health Economics and Outcomes Research Competencies Framework—developed to structure professional development needs and identify gaps in current training opportunities—also has a strong methodologic focus.
Yet, as the field of HEOR has matured and become more established as a profession, the prerequisites for career advancement have evolved beyond just demonstrating increasing levels of methodologic expertise. In biopharma, HEOR teams are now less siloed and more integrated with other functions, such as market access and medical affairs, as value evidence has become table stakes to a product’s commercial success. Similarly, in the larger consultancies and CROs, HEOR is less often positioned as a ‘boutique’ stand-alone and more frequently integrated into bundled service offerings that include clinical & real-world evidence generation and/or commercialization support.
The implications of these changes are significant for formulation of career advancement strategies. HEOR professionals are now expected to move beyond the science, demonstrating a broader mindset, ability to communicate effectively with non-HEOR colleagues, and greater strategic understanding of how HEOR impacts commercial objectives. This forum will review these trends, solicit guidance from industry veterans on implications for career advancement strategies, and demonstrate how the ISPOR HEOR Competency Framework and ISPOR learning programs can be leveraged for professional growth.
Moderator
Speakers
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Stephanie Earnshaw, PhD
RTI Health Solutions, Pittsboro, NC, United States
Stephanie Earnshaw is a Senior Fellow at RTI International within RTI Health Solutions (RTI HS) and currently Chair of ISPORs Educational Council. Dr. Earnshaw’s area of specialization is in performing decision-analysis modeling in support of health care decision making. With expertise in mathematical programming (constrained optimization) and Markov, simulation, and other state transition modeling, she has developed mathematical models to determine cost effectiveness, create pricing strategy, predict clinical outcomes, allocate resources, and understand cost care pathways particularly in support of medical diagnostics. She also has extensive experience in performing budget impact analyses. She has published extensively in several peer-reviewed journals in addition to having written several book chapters and authored the book, Budget-Impact Analysis of Health Care Interventions: A Practical Guide.
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Christopher M. Blanchette, MA, MBA, MSc, PhD
Novo Nordisk, Doylestown, PA, United States
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David Thompson, PhD
Rubidoux Research LLC, Manchester, MA, United States
Navigating the Evolving Landscape of US Healthcare Policy Reforms: Implications for Drug Pricing and Access, Health Equity, and Healthcare Research
Topics: Health Policy & Regulatory
Level: Intermediate
How to Address Health Equity Gaps With HEOR and Policy Development in Asia Pacific
Session Type: Forums
Topics: Epidemiology & Public Health, Economic Evaluation, Health Policy & Regulatory
Level: Intermediate
Most countries in the Asia Pacific region have made significant progress in providing universal healthcare to the general population. However, universal healthcare has an intrinsic bias of allocating government funding towards sickness, and often cannot effectively manage preventive health nor rare diseases. This inevitably creates inequities between health versus care, those with access versus without access. For example, Japan’s national insurance is nearly entirely dedicated for hospital care, while preventative care such as health screening is managed at prefecture level with large variations across the prefectures. For nationally reimbursed services, several countries have patient co-payment policies usually adjusted for patients’ income level and age. However, it is not clear whether there are un-intended consequences on patients’ financial burden, or variations in health resource utilization across different diseases.
This forum is designed to bring experts in both HEOR and policy development together aiming to first understand latest developments of methodologies that incorporate health equity in cost-effectiveness analysis; and then learn from case studies where HEOR have promoted health equity through evidence-informed policy development. Nathorn Chaiyakunapruk will provide an overview of top health equity issues around the Asia Pacific region, and opportunities to improve these issues in reference to other regions/countries that may have made progress. Stacey Kowal will present health equity indicators and discuss data and methods needed for incorporating health equity into cost-effectiveness analysis from the US and UK perspectives. Jing Wu will share case studies where health equity gaps are minimized through HEOR informed national policy development. Finally, the moderator will bring speakers together to discuss the challenges and promoters for varies stakeholders to consider when they start evidence-informed health equity initiatives in their country.
Moderator
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Viva Ma, MBA, MPH, PhD
Becton Dickinson, Singapore, Singapore
Speakers
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Nathorn Chaiyakunapruk, PharmD, PhD
University of Utah, Salt Lake City, UT, United States
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Stacey Kowal, BS, MSc
Genentech, Alameda, CA, United States
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Xiaoning He, PhD
Tianjin University, Tianjin, China
Bringing Us Together or Pushing Us Apart: Will JCA, HEMA, and Other Cross-Border Collaboration Initiatives Improve Patient Access?
Topics: Health Technology Assessment, Economic Evaluation, Health Policy & Regulatory
Level: Introductory
Moderator
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Erika Wissinger, PhD
Cencora, Conshohocken, PA, United States
Speakers
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Erika Wissinger, PhD
Cencora, Conshohocken, PA, United States
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Michael Drummond, MCom, DPhil
University of York, Lichfield, United Kingdom
Michael Drummond is Professor Emeritus and former Director of the Centre for Health Economics at the University of York in the United Kingdom. His main field of interest is in the economic evaluation of health care treatments and programmes. He has undertaken evaluations in a wide range of medical fields including care of the elderly, neonatal intensive care, immunization programmes, services for people with AIDS, eye health care and pharmaceuticals. He is the author of two major textbooks and more than 750 scientific papers. He has been President of the International Society of Technology Assessment in Health Care, and the International Society for Pharmacoeconomics and Outcomes Research. In October 2010 he was made a member of the National Academy of Medicine in the USA. He has advised several governments on the assessment of health technologies and chaired one of the Guideline Review Panels for the National Institute for Health and Care Excellence (NICE) in the UK. He served for 14 years as Co-Editor-in-Chief of Value in Health and was made Editor Emeritus in May 2024. He has been awarded 3 honorary doctorates, from City University (London), Erasmus University (Rotterdam) and the University of Lisbon.
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Jon Campbell, PhD
National Pharmaceutical Council, Washington, DC, United States
Women in HEOR: Navigating HEOR Career Transitions-Insights, Experiences, and Growth Strategies
Session Type: Forums
Topics: Organizational Practices
Level: Introductory
The purpose of the ISPOR 2025 Women in HEOR Forum is to facilitate a discussion among panelists about navigating change in HEOR careers, highlighting experiences of ISPOR members from different sectors, along their career trajectory.
The vision of the Women in HEOR initiative is to support the contribution of women in our field by serving as a catalyst for leadership and a platform for mentorship, collaboration, and networking. This Women in HEOR Forum will highlight a topic of recent interest in recent Virtual Networking sessions: navigating career change. Career change may occur as careers advance or trajectories shift owing to market and personal changes. This forum will highlight experiences of ISPOR members who have navigated career transitions among industry, consulting, academia or other sectors at different points in their careers.
Julia Slejko will introduce the session, including the objectives of the Women in HEOR initiative (10 minutes). Three panelists, including ISPOR members, will present on their own career transitions (25 minutes). A moderated discussion among the panelists cover topics such as: exploring career changes (voluntary or necessary), planning change strategically, navigating planned and unplanned change, and strategies for success (10 minutes). The final 15 minutes will engage the audience in Q&A, and live polling will be used throughout to elicit perspectives on the forum topics.
Moderator
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Julia F. Slejko, PhD
University of Maryland School of Pharmacy, Baltimore, MD, United States
Speakers
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Deborah Marshall, PhD
University of Calgary, Calgary, AB, Canada
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Elisabeth Oehrlein, MS, PhD
Applied Patient Experience, LLC, Washington, DC, United States
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Amie R Tan, PhD
Genentech, South San Francisco, CA, United States
4:00 PM - 4:30 PM
What’s Really Happening with GLP-1s? Insights from AI-Enabled RWD
Session Type: Exhibit Hall Theaters
Topics: Real World Data & Information Systems
Level: Intermediate
4:00 PM - 4:45 PM
Methodology in HEOR Poster Tour
Session Type: Research Posters
This tour will take place during Poster Session 2, Poster will be hung from 4:00 - 7:00 PM.
Posters featured in this tour:
PT7: Selection and Stability of Parametric Bivariate Copula Models for Joint Modelling of Overall and Progression-Free Survival
PT8: Time-Driven Activity-Based Costing in Healthcare: Should We Adjust for Inflation or Reapply the Method?
PT9: Application of ML-NMR to Time-to-Event Outcomes Using Parametric Models and Flexible Parametric (Spline) Models: A Case Study Using A Simulated Dataset
PT10: Patient-Reported Outcome Endpoint Emulation in Heart Failure External Control Arm Study (EMULATE-HF PRO-ECA Study)
PT11: Leveraging Knowledge Graphs for Health Equity Analysis With Real-World Data
PT12: Large-Language Models to Complement and Augment Literature Review: Hi! How Can I Help You?
Rare Disease Poster Tour
Session Type: Research Posters
This tour will take place during Poster Session 2, Poster will be hung from 4:00 - 7:00 PM.
Posters featured in this tour:
PT13: Clinician-Reported Outcomes — A Rare Opportunity for Orphan Labels?
PT14: Do Breakthrough Therapies Demonstrate Breakthrough Value to Payers? An Evaluation of US Hemophilia B Gene Therapy Access Policies
PT15: Assessing Minimal Clinically Important Difference Estimates for the Rett Syndrome Behavior Questionnaire (RSBQ) Using Data From the Trofinetide Clinical Program
PT16: Assessing the Impact of Disparity on Hospital Outcomes: Review of 5 Diseases and Their Unique Challenges
PT17: Challenges for PAIC in Rare Diseases: Results of a Systematic Literature Review
PT18: Prescribing Trends of Disease-Modifying Medications in Texas Medicaid Enrollees With Sickle Cell Disease
4:00 PM - 7:00 PM
Poster Session 2
Session Type: Research Posters
5:00 PM - 6:00 PM
Exploring the Influence of Patient Preference Information in Health Technology Assessment: Insights From Mock Deliberations With Agencies
Session Type: Issue Panel
Topics: Health Technology Assessment, Health Policy & Regulatory, Patient-Centered Research
Level: Intermediate
ISSUE: Internationally, there is a growing drive to integrate patient preference information (PPI) into Health Technology Assessment (HTA) decision-making, reflecting a shift towards more diverse and inclusive forms of evidence. However, it is unclear how PPI is used in real-world contexts and the extent to which it can reshape and influence HTA decisions. Understanding how PPI can be meaningfully used in HTA is fundamental for supporting its practical application and increasing trust in the use of PPI. This panel session aims to enhance understanding of how HTA committees interpret and incorporate PPI into decision-making. OVERVIEW: The panel will present key findings from mock deliberation workshops conducted by members of the HTAi Patient Preference Project Subcommittee with experts from four HTA agencies. For the workshops, a mock evidence package was developed including PPI together with clinical and economic evidence to simulate decision-making processes in a mock deliberation to understand how decision-makers might use PPI. The findings highlight the importance of standardizing the path to integration as well as the content and format of PPI to support consistent interpretation and application in HTA. The panel will include a PPI researcher and representatives from patient advocacy (patient with lived experience) and HTA. An overview of results from the mock deliberations will be provided by the PPI researcher and the moderator (approximately 15 minutes). The moderator will summarize the mock scenario from the workshops (i.e., key clinical, economic, and PPI evidence), enabling the audience to participate in a mini-voting session. By examining how PPI is weighed alongside clinical and economic evidence, the issue panel session will discuss and provide valuable insights for stakeholders aiming to generate more pertinent PPI to be incorporated into the decision-making process and will provide key takeaways for HTA agencies interested in balancing this evidence in their assessments.
Moderator
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Catherine Koola, MPH
Institute for Clinical and Economic Review (ICER), Cambridge, MA, United States
Speakers
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Farah Husein, BSc, MSc, PharmD
CDA-AMC, Toronto, ON, Canada
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Barry Stein
Colorectal Cancer Canada, Montreal, QC, Canada
Real-World Life-Cycle Evaluation for Precision Medicine: From Conceptualization to Successful Implementation
Session Type: Other Breakout Session
Topics: Health Policy & Regulatory, Clinical Outcomes, Economic Evaluation
Level: Intermediate
PURPOSE: This session seeks to critically engage an international audience for operationalizing life-cycle health technology assessment (LC-HTA) and real-world evidence (RWE) to manage precision medicine uncertainties during the regulatory approval process. Our panel will: introduce a novel framework for life cycle assessment for highly uncertain precision medicine technologies; present learnings from the implementation of this framework within a Canadian cancer care system; and discuss international relevance and transportability of RWE generated through LC-HTA. DESCRIPTION: Advances in precision medicine challenge conventional regulatory and reimbursement processes. These advances are rapid, involve small patient groups, and are frequently evaluated without a randomized comparison group. Life-cycle assessment alongside patient engagement and continuous RWE generation can resolve evidentiary uncertainty on comparative effectiveness and value. This session will begin by introducing an LC-HTA framework operationalized within British Columbia, Canada’s cancer control system through the PRecision oncology Evidence Development in Cancer Treatment (PREDiCT) program (10’ Regier). Centred on a case study of entrectinib, a conditionally authorized treatment targeting advanced NTRK-gene fusion-positive cancers, presenters will then: establish comparative effectiveness by concatenating single-arm Phase I/II entrectinib trial data with RWD from British Columbia and the United States (13’ Weymann); determine real-world cost-effectiveness of entrectinib versus standard care, demonstrating how value for money evolves with new evidence in relation to a national index economic evaluation (13’ Krebs); and discuss RWE transportability for informing international regulatory and reimbursement decisions (13’ Adamson). The session will conclude with a facilitated discussion on key challenges for embedding LC-HTA within learning healthcare systems, engaging with the audience through a real-time prioritization polling exercise (10’).
Moderator
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Dean Regier, BA, MA, PhD
BC Cancer - ARCC - UBC, Burnaby, BC, Canada
Speakers
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Deirdre Weymann
BC Cancer, Burnaby, BC, Canada
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Emanuel Krebs, MA
Cancer Control Research, BC Cancer, Vancouver, BC, Canada
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Blythe Adamson, MPH, PhD
Flatiron Health, New York, NY, United States
Balancing Innovation and Affordability: A Roadmap for Navigating State Drug Pricing Boards
Session Type: Other Breakout Session
Topics: Health Policy & Regulatory, Economic Evaluation
Level: Introductory
PURPOSE: As states begin to regulate drug pricing and affordability through Prescription Drug Affordability Boards (PDABs), stakeholders face new challenges in navigating state-level pricing limits, affordability reviews, and evidence generation. This session will provide an in-depth PDAB overview covering the core functions of PDABs, how they assess drug affordability, and what impactful evidence can be prepared to engage with PDABs effectively. We will discuss the evolving landscape of PDABs, how they assess factors like cost, utilization, and out-of-pocket costs, and how pharmaceutical companies can adapt and evolve the evidence strategy to meet these state-specific regulatory requirements. The session will provide product case examples from Colorado and Maryland PDAB reviews and discuss learnings on recent affordability reviews, reimbursement methodologies evaluated, implications on patient access, and strategies for evidence generation. DESCRIPTION: Dr. Ramsey will moderate and spend 10 minutes defining PDABs, states that utilize them, and their roles. Dr. Padula will spend 15 minutes focusing on Upper Payment Limit (UPL) setting processes along state legislative considerations on drug pricing thresholds and value demonstration. Dr. Patel will spend 20 minutes reviewing the specific drug affordability review process across states, including key trends in how state PDABS are evaluating affordability (costs to system, utilization, out-of-pocket expenses). Dr. Patel will provide practical recommendations for key stakeholders to optimize engagement in PDABs to balance affordability and access to innovative treatments. 15 minutes will include real-time polling for the product case examples to gather audience perspectives with interactive discussion and question and answers from obtain practical insights and solutions. Attendees from life sciences industry professionals, payers, patient organizations, policymakers, and researchers will benefit from this session.
Moderator
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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.
Speakers
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William V Padula, PhD
University of Southern California, Los Angeles, CA, United States
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Chad Patel, PharmD
AESARA, Chapel Hill, NC, United States
AI-Assisted Literature Reviews: Requirements and Advances
Session Type: Research Podiums
The session discusses recent advancements in using artificial intelligence (AI) tools for literature reviews. Topics included will highlight potential advantages and limitations of AI tools for screening, extraction, and synthesis of published literature, with an emphasis on practical considerations and appropriate use scenarios.
Assessment of Reasoning Agents for building Literature Search Strategies
OBJECTIVES: The application of Large language models (LLMs) to screening and extraction in Systematic Literature Reviews (SLRs) is well studied. However, current LLM search tools represent ‘black boxes’, lacking transparency or human feedback, and can hallucinate (including hallucinating MeSH terms). Embedding-based search methods may address hallucination, but at the cost of human understanding. We propose a novel approach that utilizes human-in-the-loop reasoning agents in building Boolean Search strings for SLRs and targeted literature reviews.
METHODS: We launched ‘Smart Search,’ a reasoning agent that employs LLM-based chain-of-thought reasoning and a generator-critic loop, into the Nested Knowledge SLR software. Smart Search iteratively generates and assesses Boolean strings based on users’ textual Research Questions and iterative chat-based user clarifications. To validate this, we provided the Objective/Aims statement from ten Cochrane SLRs to Smart Search and assessed Recall, using PubMed-indexed records that were included in the Cochrane SLRs as the gold standard. We repeated this test on twenty SLRs performed in the Nested Knowledge system, and also assessed black-box LLMs (specifically GPT) in the same tasks.
RESULTS: Cochrane reviews covered the following topics: Multiple Sclerosis, Non-small Cell Lung Cancer, Renal Cell Carcinoma, Subfertility, Non-alcoholic Fatty Liver Disease, Epilepsy, Human Immunodeficiency Virus, Statins, Ischemic Conditioning, and Prostate cancer. Smart Search had 76.8% Recall against Cochrane reviews and 79.6% Recall against reviews performed in Nested Knowledge, compared to 13.0% Recall with black-box LLM search construction.
CONCLUSIONS: Our results demonstrate the potential of human-in-the-loop reasoning agents to generate search strategies for SLRs and targeted reviews. Specifically, Smart Search outperformed LLMs and achieved acceptable Recall in validation against SLRs of diverse clinical topics. Further research, particularly comparison of searches built by reasoning agents against expert-drafted search strategies, are required to assess appropriateness of LLMs for SLR search strategies.
AI Tools for Literature Reviews: Are Current Guidelines Meeting the Needs of Researchers?
OBJECTIVES: Artificial intelligence (AI) offers the opportunity to make literature reviews—historically human-driven and resource-intensive processes—more efficient. Unlike systematic literature reviews (SLRs), which are known for their rigor, pragmatic literature reviews have greater methodological flexibility. As such, reviewing and implementing guidelines and recommendations is crucial to ensure that AI is effectively and ethically employed across different types of literature reviews. This study aimed to explore guidelines and recommendations for utilizing AI in literature reviews, including SLRs and pragmatic literature reviews.
METHODS: A scoping review was conducted in January 2025 to identify guidelines and recommendations for using AI in literature reviews. Sources included PubMed; organizations and societies, such as Cochrane and the Centre for Reviews and Dissemination; and working groups, such as Responsible AI in Evidence Synthesis (RAISE). The focus was to identify recommended workflows (e.g., AI-driven, human-in-the-loop) and phases where AI is recommended. Additionally, the extent to which guidelines addressed the use of AI for SLRs compared with pragmatic literature reviews was assessed.
RESULTS: AI is recognized by key stakeholders as a valuable tool for literature reviews, and guidelines and recommendations generally suggest that AI should augment—but not replace—human efforts. The information was predominantly focused on SLRs, where most recommendations were provided for title/abstract screening and data extraction. However, there was less information related to other SLR phases, such as reporting. Gaps were identified in addressing how to adapt AI to the less structured nature of pragmatic literature reviews, where reference sets are generally smaller than for SLRs.
CONCLUSIONS: This scoping review highlights the evolving role of AI in evidence synthesis at a time when many existing guidelines are being updated and new ones are under development. It also highlighted the need for best practices for AI use in pragmatic literature reviews to expand AI’s utility across diverse literature review methodologies.
Evaluating the Performance of Claude 3.5 Sonnet in Data Extraction Automation for Systematic Literature Reviews (SLRs)
OBJECTIVES: To evaluate the performance of Claude 3.5 Sonnet in automating data extraction for SLRs.
METHODS: A custom model was developed using the large language model, Claude 3.5 Sonnet, for data extraction, employing a multi-stage processing approach. The model’s performance was tested for its ability to extract data from 14 studies across two SLRs in dermatology and oncology; we intend to test the model on 50 studies across various disease areas. Performance was benchmarked against extractions conducted and reconciled between two senior independent human reviewers. False positives were defined as incorrect data points; false negatives represented missed data points. Performance metrics included accuracy (total correct predictions across all classes), precision (proportion of true positive predictions), sensitivity, and F1 score (harmonic mean between precision and sensitivity).
RESULTS: The model demonstrated average accuracy of 76.2%, average precision of 89.2%, and average sensitivity of 85.1%, with an F1 score of 86.5%, reflecting strong alignment with human extraction. Compared with human reviewers, 76.2% of extracted data points were true positives, 9.9% were false positives, and 14.0% were false negatives. The model performed best in extracting study design characteristics (accuracy: 92.2%; precision: 98.1%; sensitivity: 93.9%; F1: 96.0%) and baseline participant characteristics (accuracy: 90.7%; precision: 96.9%; sensitivity: 93.3%; F1: 95.0%). Performance for intervention characteristics was strong but was impacted by a higher proportion of missed data points (accuracy: 83.7%; precision: 94.3%; sensitivity: 88.2%; F1: 91.2%). Outcomes exhibited the lowest performance, driven by a higher rate of false negatives (accuracy: 71.6%; precision: 85.0%; sensitivity: 83.7%; F1: 85.6%).
CONCLUSIONS: The proposed workflow for automated data extraction shows promising performance, particularly in extracting study design and baseline participant characteristics, indicating its potential to complement human reviewers. Lower performance in extracting outcomes, driven by false negatives, underscores the need for targeted improvements through modified prompts and output schema.
Machine Learning-Assisted Screening for Evidence Synthesis: When Can We Stop?
OBJECTIVES: Machine learning (ML)-assisted screening is increasingly used in evidence synthesis for its potential efficiency compared to dual-human screening. However, it is unclear when, or if, humans can stop screening abstracts. The purpose of this study was to inform decisions about thresholds for stopping human abstract screening.
METHODS: We retrospectively analyzed the screening results from seven systematic reviews (SR) conducted between August 2022 and October 2024. Each SR included randomized controlled trials of treatment options for people with chronic kidney disease. For each SR, we used ML-assisted screening in PICO Portal. After initial training with dual-human independent reviewers, citations were re-ranked daily based on the ML predictions for full-text eligibility. Reviewers stopped screening when the prediction of eligible for full-text reached at least 95% recall. We analyzed the percentage of citations ultimately included in the SRs identified after screening 10%, 25%, and 40% of the abstracts. We calculated a weighted average by project size of the percentage of abstracts needed to be screened manually to identify all eligible citations and estimated potential time saved.
RESULTS: We uploaded 32,102 records into PICO Portal (range, 2629 to 8730). After screening 10%, 25%, and 40% of the abstracts, we identified >40% (range, 43.1% to 100%), >90% (range, 94.7% to 100%), and 100% of the eligible citations. On average, 19.0% (range, 2.6% to 33.6%) of the abstracts needed to be screened by dual-human screening to identify all eligible citations. If we had used a 35% threshold for stopping screening instead of 95% recall, our team could have saved an additional 11 hours (range, -1 to 38.1) per project.
CONCLUSIONS: When using ML-assisted screening, humans may need to screen fewer than 35% of the abstracts to identify all relevant citations. Prospective studies are needed to guide researchers on determining appropriate stopping thresholds when using ML-assisted screening systems.
Challenges in the Implementation of Generalized Cost Effectiveness Analysis (GCEA): Debating a Path Forward
Session Type: Issue Panel
Topics: Health Technology Assessment, Health Policy & Regulatory, Economic Evaluation
Level: Advanced
ISSUE: Incorporating broader societal value elements into health technology assessment (HTA) remains a challenge. While a recently published Generalized Cost-Effectiveness Analysis (GCEA) user guide outlines methods to empirically quantify these values, questions linger about their feasibility, fairness, and impact on pricing and coverage decisions considering the ongoing uncertainties related to double counting, threshold modifications, and surplus appropriation. This panel will debate whether and how societal value elements should shape value assessment and payer decision making in the US. OVERVIEW: Dr. Li will introduce the panel, summarize conventional approaches, and provide an overview of the current evidence and evidence gaps for GCEA. Dr. Whittington will argue for the inclusion of GCEA into value assessment and payer decision making and will provide recommendations for implementing GCEA even considering double counting, lack of a threshold, and uncertainties about manufacturer surplus. Dr. Shafrin will that additional research is needed to translate GCEA value estimates into pricing and coverage decisions. In particular, he will emphasize the intersection between fairness and efficacy as it relates to value elements. Finally, Dr. Lakdawalla will argue for the incorporation of disease severity into value assessment using a GRACE-based approach rather than ad hoc adjustments. Additionally, he will discuss whether GRACE can be integrated with other value elements (e.g., equity, option value). The panel will conclude with a debate on the overall merits of using GCEA for drug pricing and coverage. Panelists will weigh the trade-offs between the complexity of implementation and the accuracy of societal value measurement. Key questions include: Is the additional precision worth the effort? How do we prevent double counting? Do willingness-to-pay thresholds need adjustment? How does the answer to these questions vary across single payer compared to more market-based geographies?
Moderator
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Meng Li, MS, PhD
Tufts Medical Center, The Center for the Evaluation of Value and Risk in Health, Boston, MA, United States
Speakers
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Jason Shafrin, PhD
FTI Consulting, Los Angeles, CA, United States
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Darius Lakdawalla, PhD
University of Southern California, Los Angeles, CA, United States
Darius Lakdawalla is a widely published, award-winning researcher and a leading authority on health economics and health policy. He holds the Quintiles Chair in Pharmaceutical Development and Regulatory Innovation at the University of Southern California, where he sits on the faculties of the School of Pharmacy, the Sol Price School of Public Policy, and the Leonard D. Schaeffer Center for Health Policy and Economics, one of the nation’s premier health policy research centers.
His academic research has focused primarily on the economics of risks to health, the value and determinants of medical innovation, the economics of health insurance markets, and the industrial organization of healthcare markets. Dr. Lakdawalla serves as associate editor at the Journal of Health Economics and has previously served in this role at the American Journal of Health Economics and the Review of Economics and Statistics. His academic work has appeared in leading peer-reviewed journals of economics, health policy, and medicine, including the American Economic Review, Quarterly Journal of Economics, Health Affairs, the Journal of Health Economics, and the New England Journal of Medicine. In addition, his work has been featured by prominent popular press outlets, such as the Wall Street Journal, National Public Radio, Forbes, and the New York Times. Dr. Lakdawalla has also received the PhRMA Foundation Value Assessment Challenge Award, designed to encourage innovative approaches to defining and measuring value in health care, in 2019 (third place) and 2020 (first place), along with the ISPOR Excellence in Research Methodology Award, the Garfield Prize, and the Milken Institute Award for Distinguished Economic Research.
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Melanie D Whittington, MS, PhD
Leerink Center for Pharmacoeconomics, Boston, MA, United States
Melanie Whittington is the Managing Director and Head of the Leerink Center for Pharmacoeconomics where she leads pharmacoeconomic evaluations of in-development and recently approved pharmaceuticals and studies incentives for innovation. She is also a Senior Fellow at the Center for the Evaluation of Value and Risk in Health (CEVR) where she advises on CEVR projects related to value assessment, economic modeling, and CEVR databases.
Designing Equitable Measurement Frameworks That Are Community Centered: Why, What, and How?
Session Type: Issue Panel
Topics: Patient-Centered Research, Organizational Practices
Level: Intermediate
Health economics and outcomes research (HEOR) is an important tool for policymakers and healthcare providers regarding resource allocation, reimbursement, and clinical guidelines. However, engaging underrepresented populations is essential in addressing structural and systemic barriers in healthcare access, treatment outcomes, and patient burden. By including underserved communities and their diverse patient perspectives equity in healthcare can truly be achieved rather than perpetuating systemic biases.
Despite the desire for equity in healthcare, challenges such as allocating resources for patient/community engagement and lack of standardized methods for sustainable engagement persist. Addressing these challenges raises critical questions: How can authentic patient and community engagement be fostered when researchers lack prior experience working with diverse populations? What soft skills are essential for building trust and meaningful partnerships?
Our advocacy organization addresses these gaps by educating and training patients, caregivers, community health workers, and clinical researchers on cancer care delivery and the science behind cancer treatment. Through this work, we aim to equip stakeholders with the tools needed to advance equity and trust in healthcare research and delivery. Researchers will little to no experience working collaboratively with patients will benefit greatly from attending this session.
Our panel will discuss important steps used in our work with cancer patients and researchers, focusing on actionable strategies for long term engagement in underserved communities:
1. Establishing in creating a Shared Agenda:
2. Adopting Collaborative Patient to Community
Communication:
3. Agreeing to Partner on Sustainable Engagement
Moderator
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Kimberly Richardson, MA
Black Cancer Collaborative, Chicago, IL, United States
Speakers
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Hala Durrah, MA
The Humanization Matters Collaborative, San Diego, CA, United States
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Ysabel Duron, BA
The Latino Cancer Institute, San Jose, CA, United States
Advancing Inclusive Healthcare Benefit Design: Engaging Employees Through Participatory Decision-Making
Session Type: Workshop
Topics: Patient-Centered Research
Level: Introductory
PURPOSE: Employers are a primary purchaser of healthcare in the US, responsible for making complex, value-laden coverage decisions that shape healthcare access, costs, and coverage options for millions of employees. These decisions require tradeoffs and may not reflect the diverse needs and preferences of the workforce. This workshop will explore methods to meaningfully engage employees directly in the decision-making process, promoting shared responsibility. Participants will learn how an employer successfully used a participatory decision-making process to co-create a benefit reflecting collective needs and employee preferences.
DESCRIPTION: Workshop attendees will obtain knowledge of a) the role of employers as healthcare stakeholders, b) tradeoffs involved in healthcare benefit design, and c) opportunities for employers to engage employees in benefit development to improve trust, transparency, and acceptance. Ms. Westrich will introduce the role of employers in healthcare decision-making and the tradeoffs they consider when making healthcare coverage decisions. Ms. McNichol will describe how her organization developed and utilized a participatory decision-making framework to engage employees in deliberative workshops to develop a health plan. She will identify the data sources and practices that informed the development of the framework, and share key results and lessons learned from this initiative. Dr. Vandigo will link the framework with patient-centered research and patient experience data, how we define and assess value in public policy, and highlight the relevance of the framework for patient organizations, manufacturers, and investors. Audience participation will include brainstorming examples of value-laden healthcare decisions, exploring tradeoffs, reflecting on the challenges of balancing individual and collective needs, and examining how structured dialogue can improve benefit design. This workshop will be valuable to those interested in advancing more consumer/patient-focused benefit designs.
Moderator
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Kimberly Westrich, MA
National Pharmaceutical Council, Herndon, VA, United States
Kimberly Westrich, MA, is the Chief Strategy Officer of the National Pharmaceutical Council (NPC), which sponsors and conducts research on health policy issues related to the development and use of innovative biopharmaceuticals to improve the health of patients. NPC’s research contributes to the body of evidence that supports discussions and decisions about patient access to treatments, appropriate use, and the value innovative treatments provide to both patients and the healthcare system.
Ms. Westrich provides strategic guidance to NPC’s policy research and communications activities. She leads several research initiatives across NPC’s portfolio, including employer-sponsored insurance. She has published extensively on issues related to value assessment frameworks, patient-centered formulary and benefit design, value-based contracts, quality performance measurement, and accountable care organizations. Additionally, Ms. Westrich leads NPC’s workplace culture initiative — most notably demonstrated by our company's recognition as a Certified Great Place To Work®.
Ms. Westrich began her NPC career in 2000. She has also served as Director of Research at the Pharmaceutical Research and Manufacturers of America (PhRMA), worked as a healthcare consultant at The Lewin Group and Xcenda, and as a health economics and outcomes researcher at Johnson & Johnson.
Ms. Westrich is a certified yoga teacher and life coach with a passion for helping others learn and thrive. She received her master’s degree in economics from Northwestern University and her undergraduate degree in economics and mathematics from the College of William and Mary.
Speakers
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Janet G McNichol
Inside Workplace Wellness, Reston, VA, United States
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Joe Vandigo, MBA, PhD
Applied Patient Experience, Greensburg, PA, United States
Unlocking Ethics in Health Technology Assessment: Exploring Practice and Impact
Session Type: Workshop
Topics: Health Technology Assessment, Health Policy & Regulatory, Organizational Practices
Level: Introductory
PURPOSE: Explicit attention to ethical considerations is increasingly being recognized as integral to Health Technology Assessment (HTA) and health care decision-making. The increasing complexity of the health care landscape is making the importance of ethical considerations even more apparent, as HTA organizations and decision-makers are faced with the need to identify innovative opportunities to assess, appraise, and harness the total value of health technologies across the life cycle. Despite this growing recognition of the importance of ethics in HTA, capacity remains limited in how to apply, understand, and leverage key ethical considerations within the practices and methodologies of HTA. This workshop will introduce participants to the role of ethics in HTA, and outline approaches to meaningfully consider ethics to best support HTA practice and health systems decision-making. DESCRIPTION: Workshop participants will learn the history, scope, rationale, purpose and methods for the inclusion of ethical considerations in HTA, as well as considerations related to ethics in the conduct of HTA itself (15 min.). Participants will be introduced to a framework for ethics analysis developed by Canada’s Drug Agency, and participate in brief break-out group discussions to apply their learnings to ethics analyses in select case examples, including a CAR-T therapy, drug for a rare disease, and oncology medical device (25 min.). Participants will have a chance to discuss their findings, applicability of ethics analysis to their own work, and an opportunity to engage with experts in the field (20 min.). Participants will leave this workshop with a toolkit of methods, strategies, practices and resources to better understand, leverage, and learn from ethical considerations in their own practice, and in the broader, changing health care landscape.
Moderator
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Ana Komparic, PhD
University of British Columbia, Vancouver, BC, Canada
Speakers
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Renata Axler, PhD
Canada's Drug Agency, Ottawa, ON, Canada
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Michael DiStefano, PhD
University of Colorado, Aurora, CO, United States
Health Disparities: Trends in Patient Access and Policy Insights Across the Globe
Session Type: Research Podiums
This podium session delves into global trends in health disparities, patient access, and policy insights. Four abstracts will be presented, offering diverse perspectives on: Equity in innovative therapies, public attitudes towards health inequality, demand for specialized treatments among different populations, and prescription disparities in public health programs. By examining these topics across various countries and healthcare systems, the session aims to illuminate the complex landscape of health disparities.
The Past, Present, and Future of Demand for Bariatric Surgery in Chile: A Subgroup Analysis for no-income (Group A) FONASA Beneficiaries
OBJECTIVES: In 2022, the public insurer FONASA introduced a Bundled Payment program to co-finance bariatric surgeries performed by private providers. Eligible patients must meet specific clinical and income criteria, excluding a subgroup of lower-income individuals from access despite their clinical eligibility. This study aims to characterize the past, present, and future demand within this no-income patient segment (Group A).
METHODS: A descriptive, retrospective, longitudinal study was conducted using open, anonymized secondary data on hospital discharges from 2022 to 2023 to analyze past and present demand. For projections of future demand, a funnel-down technique was employed, integrating sociodemographic (gender, age range, insurance, income group, region) and clinical data (BMI, major and mild comorbidities) with biostatistical expansion of national health registries at regional and national levels.
RESULTS: Historically, before PAD implementation, 620 bariatric surgeries were conducted in Chile, with 274 (21.3%) involving Group A patients. During PAD implementation, PAD surgeries increased to 13,120 in the first year and 21,140 in the second year, while non-PAD bariatric surgeries decreased to 375, with only 75 cases (20.0%) involving Group A cases nationwide. Despite this, the projected effective demand for bariatric surgery in Group A by 2025 is 133,553 women and 46,330 men, totaling 179,884 clinically eligible patients who are not PAD-eligible due to no co-payment capacity and no-income. These cases lack prioritization in any coverage scheme.
CONCLUSIONS: The no-income Group A remains a non-prioritized segment under PAD implementation, highlighting the need for targeted strategies to address this gap. Having no special programs to address 179K patients could exacerbate obesity-associated inequities.
Health Inequality Aversion in the United States and Americans' Views on Health Inequality
OBJECTIVES: Americans’ views on health inequalities have largely been ignored when evaluating the distribution of healthcare resources. Considering the importance of this topic in United States’ (US) politics, our study examined political party affiliation and views on health equity in the US.
METHODS: We adapted an established benefit trade-off (BTO) instrument to elicit health inequality aversion among the US adult general public from June - December 2023. We administered the BTO and survey questions on demographics, political affiliation, and health inequalities using an online platform. Questions were framed around US population groups described as ‘Better Off’, ‘Worse Off’, or ‘Middle’, in terms of length/quality of life and geographic social vulnerability. BTO responses were analyzed to calculate Atkinson parameters. Parameters >0 reflect ‘health inequality aversion’, or the willingness to sacrifice efficiency to improve equality. Survey responses were summarized using descriptive statistics. We compared views and proportion inequality averse across the US population groups using Chi-squared tests.
RESULTS: Among 1,290 respondents, political affiliation was: Republican 26% (n=339), Democrat 37% (n=471), Independent/Unaffiliated 35% (n=452), Unreported 2% (n=28). Most respondents agreed/strongly-agreed with reducing health inequality between Americans and with having an equal opportunity to be healthy, although there were higher proportions agreeing/strongly-agreeing among Democrats/Independents. The percent of the population inequality averse significantly differed (p<0.01) by political affiliation: Republican (78%), Democrat (94%), Independent/Unaffiliated (90%). Although 94% of respondents agreed that improving the health of the American people should be a priority for the federal government (87% of Republicans, 99% of Democrats, 93% of Independent/Unaffiliated), only 45% would pay more taxes to address health inequalities (27% of Republicans, 61% of Democrats, 42% of Independent/Unaffiliated).
CONCLUSIONS: While the general US population is largely inequality averse, the greatest difference in views on health equity between political parties pertained to government’s role in funding efforts to reduce health inequalities.
Advancing Equity in CAR T-Cell Therapy: An Analysis of Health Technology Assessments by Canada's Drug Agency and the National Institute for Health and Care Excellence
OBJECTIVES: Chimeric antigen receptor T-cell (CAR T-cell) therapies have revolutionized treatment for hematological malignancies. Access disparities related to cost, delivery complexity, and manufacturing challenges limit equitable benefits, especially among minority and vulnerable populations impacted by social determinants tied to diversity, equity, and inclusion (DEI). This review examines if and how health technology assessments (HTAs) by Canada’s Drug Agency (CDA) and the National Institute for Health and Care Excellence (NICE) consider equity in evaluating CAR T-cell therapies.
METHODS: HTA reports from CDA and NICE for six CAR T-cell therapies (Abecma, Breyanzi, Carvykti, Kymriah, Tecartus, Yescarta) were reviewed by two researchers for equity considerations related to access disparities, capacity, socioeconomic determinants, and related clinical and economic evidence. A pre-specified template guided data extraction. Results were summarized thematically.
RESULTS: Eighteen CDA and NICE submissions published between 2021 and 2024 were reviewed. Excluding five terminated submissions, 13 HTAs (CDA=7; NICE=6) across five indications were included. All CDA submissions highlighted disparities in disease incidence, treatment, and outcomes by race, socioeconomic status, diagnosis and referral patterns, and age, noting financial and geographical barriers disproportionately affecting marginalized groups. Six CDA submissions criticized economic evaluations for underestimating indirect travel and caregiver costs, with three highlighting unrepresentative trial populations. The CDA appraisal of Abecma included a scenario analysis with indirect costs (parking, caregiving, and productivity loss). In five submissions, NICE critiqued the additional indirect costs submitted by companies. NICE Committees in two appraisals raised concerns about the lack of evidence for older and transplant-ineligible patients.
CONCLUSIONS: This review identified that DEI considerations related to CAR T-cell therapy access like patient costs and geographical barriers were not routinely supported by evidence in CDA and NICE submissions. Evidence generation challenges in CAR-T therapy may inadvertently deprioritize equity concerns. Recent commitments to equity from HTA bodies offer opportunities to ensure fair access to novel, high-cost therapies.
Disparities in Antipsychotic Prescribing Among the US Medicare Population
OBJECTIVES: Antipsychotics remain a primary treatment option for many psychiatric conditions; however, prolonged exposure, especially to first-generation antipsychotics, is associated with increased risk of drug-induced movement disorders, including tardive dyskinesia. This study builds upon previous analyses suggesting racial and ethnic disparities in antipsychotic prescribing by examining whether these disparities persist across broader health equity measures in the Medicare population.
METHODS: We conducted a retrospective cohort study using 100% Medicare claims data to identify beneficiaries with any antipsychotic prescription drug claim from 2017-2022. We identified demographic and clinical factors associated with incident first- versus second-generation antipsychotic selection using separately specified logistic regression models. Fitted logistic regression models were used to estimate predicted probabilities and average marginal effects via recycled predictions. Standard errors and 95% confidence intervals (CIs) were generated using bootstrap resampling.
RESULTS: Of 2,677,242 incident antipsychotic users, 6% (n=161,485) were prescribed first-generation antipsychotics and 94% (n=2,515,757) were prescribed second-generation antipsychotics. Approximately 26% (n=687,139) were under 65 years of age at incident antipsychotic prescription, with 41% dually eligible for Medicare and Medicaid. The risk of incident first-generation antipsychotic treatment was estimated to be 39% higher (95% CI: 37%-41%) among Black versus White patients, 116% higher (95% CI: 100%-137%) among patients treated in long-term care (LTC) versus community mental health center settings, and 36% higher (95% CI: 34%-38%) among dual-eligible versus Medicare-only patients. Conversely, Latino patients were 17% less likely (95% CI: 15%-18%) to initiate first-generation antipsychotics versus White patients.
CONCLUSIONS: In this study, while less commonly prescribed, incident first-generation antipsychotic use was significantly more likely among Black, LTC, and dual-eligible patients, and less likely among Latino patients. Results highlight the increased likelihood of higher-risk antipsychotic selection across multiple vulnerable populations. Future studies are needed to understand the implications, such as risk of drug-induced movement disorders like tardive dyskinesia, among these groups.
From Prompting to Policy: The Advances of Generative AI in the Last Year
Session Type: Other Breakout Session
Topics: Methodological & Statistical Research
Level: Introductory
PURPOSE: In the past year, the field of Generative AI (GenAI) has seen remarkable advancements, significantly impacting its applications in HEOR. These advancements offer exciting new opportunities but also demand a rigorous and scientific approach to maintain the integrity and reliability of generated evidence. This session aims to provide attendees with a thorough overview of these recent developments. By addressing both the potential benefits and the challenges, we will delve into the implications for the reliability, transparency, and validity of GenAI in HEOR. Attendees will gain the latest knowledge and insights, ensuring they are well-informed about the current state and future potential of GenAI in HEOR. DESCRIPTION: The session, moderated by Siguroli Teitsson, will begin with a concise summary (7’) of developments in Generative AI (GenAI) over the past year, including the availability of more powerful large language models (LLMs), increased prominence of advanced prompt engineering and publication of guidance and regulation regarding the use of GenAI in HEOR. Sven Klijn from BMS will discuss the advances in prompting techniques and the implications for reliability, transparency and validity of GenAI applications (10’). Tim Reason from Estima Scientific will present on novel use cases for GenAI in HEOR, that were hitherto not possible or lacked scientific robustness (10’). Dr. Rachael Fleurence from NIH will reflect on the rapid progress in the field of GenAI from a policy perspective, with a focus on Health Technology Assessment and the Joint Clinical Assessment (10’).Throughout the presentations, the audience will be interactively polled to gather community perspectives regarding recent GenAI developments. A significant part of the session will be reserved for open discussion, encouraging active audience participation. By facilitating a multi-perspective dialogue, the session seeks to address existing concerns regarding GenAI and identify robust methods of working in this rapidly developing field.
Moderator
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Siguroli Teitsson, BSc, MSc
Bristol Myers Squibb, Denham, United Kingdom
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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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.
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Rachael Fleurence, MSc, PhD
National Institutes of Health, Bethesda, MD, United States
Dr Fleurence is a Senior Advisor at the National Institutes of Health where she is working on launching a national initiative to eliminate Hepatitis C in the United-States. Dr Fleurence is also affiliated with the National Institute of Biomedical Imaging and Bioengineering where she works on advances in Artificial Intelligence and Machine Learning. Dr Fleurence currently co-leads the ISPOR Task Force on the suitability of EHR data for Health Technology Assessments. Previously, Dr Fleurence served as a senior health advisor in the Biden-Harris White House, Dr. Fleurence received a BA from Cambridge University (United Kingdom), an MA in business management from ESSEC-Paris (France), and an MSc and PhD in health economics from the University of York (UK).
6:00 PM - 7:00 PM
Welcome Reception (Exhibit Hall)
Session Type: General Meeting
Join us for the Welcome Reception, supported by Corporate Partners. A perfect kick-off to connect, unwind, and gear up for what's ahead.
Thu May 15
7:00 AM - 8:30 AM
Morning Coffee Service
Session Type: General Meeting
Don't miss the start of day two with the Plenary Session. Enjoy your morning coffee as you listen to dynamic presentations intended to inspire and empower. Provided by ISPOR.
7:00 AM - 5:00 PM
Registration Hours
Session Type: General Meeting
8:30 AM - 9:45 AM
Second Plenary Session
Session Type: Plenary
9:30 AM - 7:00 PM
Exhibit Hall Hours
Session Type: General Meeting
9:45 AM - 10:15 AM
Thursday Morning Coffee and Connect (Exhibit Hall)
Session Type: General Meeting
Head to the exhibit hall to connect with felow attendees and exhibitors over a steaming cup of coffee. Provided by ISPOR.
10:15 AM - 10:45 AM
Cloud-First Insights Generation: How Research Teams and RWD Sources Are Collaborating for Faster, More Secure Data Discovery and Assessment
Session Type: Exhibit Hall Theaters
Topics: Real World Data & Information Systems, Study Approaches, Organizational Practices
Level: Intermediate
10:15 AM - 11:15 AM
Rethinking Value and Access Strategy Through the Lens of Value Evidence Archetypes in a Dynamic Healthcare Landscape
Session Type: Issue Panel
Topics: Organizational Practices, Health Technology Assessment
Level: Intermediate
Payer archetyping has long been a valuable tool to better understand the specific needs and behaviors of different payer types. Archetyping helps identify similarities and differences across markets to inform strategy development and strategic resource allocation in the pharmaceutical industry. Historically, payer archetypes have been classified into categories such as cost-effectiveness driven, budget impact driven, competitive tendering driven, and clinical benefit driven markets. However, these usually do not consider the value evidence requirements that underpin health-care decision-making in these markets. While final payer decisions may often hinge on budget impact or price ceiling/cost-effectiveness thresholds, the first step is demonstrating added benefit on patient relevant outcomes like mortality, morbidity and quality of life through well designed head-to-head clinical trials. Benefit must then be supported by a robust cost-effectiveness model informed by RWE, as well as robust assessments of cost of illness. This “cost of play” reflects the growing demand for comprehensive evaluations that meet the evidentiary and contextual requirements of diverse healthcare systems. This workshop will propose to complement payer archetypes with “value evidence archetypes” to better inform the Value and Access strategy for companies across the product lifecycle.
Moderator
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Martin Rost, PhD
AESARA, Boca Raton, FL, United States
Speakers
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Denise Globe, PhD
Gilead Sciences, Foster City, CA, United States
Denise Globe PhD is currently the Head of the GHEOR and the Global Value and Access Center of Excellence at Gilead. She has 30 years of experience in health care with a focus on quantitative policy research and direct research experiences in health economics research including the outcomes, process, financing and delivery of care. She leads a team at Gilead that is accountable for global observational research, evidence for access strategy and execution for the oncology, virology, liver and inflammation portfolios to maximize reimbursement and access across the life cycle.
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Indranil Bagchi, MS, PhD
GSK US, Collegeville, PA, United States
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Jens Grueger, PhD
Boston Consulting Group, Baden-Württemberg, Germany
Real-World Evidence to Inform Decisions: Focus in Oncology
Session Type: Research Podiums
This session focuses on real world evidence in the Oncology treatment pattern and patient outcomes landscape. Using case studies and advanced analytics, it uncovers insights on patients journey, heterogeneity and impact of novel therapies. Attendees will gain insights on use of advanced methodologies in enhancing patient care while understanding key trends in some oncology treatment patterns and role of RWD in mapping patient journey.
Moderator
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Maja Kuharic
Northwestern University, Chicago, IL, United States
Using Z Codes to Characterize Health and Social Histories in Commercially Insured Non-Hodgkin Lymphoma Patients: Insights from Real-World Data
OBJECTIVES: Social and health-related factors, such as socioeconomic status and smoking history, influence cancer outcomes, including survival and mortality. Z codes, introduced in 2015 within the ICD-10-CM system, document patient histories and exposures. These codes offer insights into determinants of health that impact care and outcomes. However, the extent of Z code documentation in oncology remains unclear. Using Non-Hodgkin Lymphoma (NHL) patients as a case study, this study aimed to examine Z code documentation and patient characteristics among NHL patients.
METHODS: We conducted a retrospective analysis of Merative MarketScan® claims database to identify patients with ≥1 inpatient diagnosis or ≥2 outpatient diagnoses of NHL and any Z code claim between January 1, 2016, and December 31, 2021. We determined the distribution of documented Z codes by category (e.g., economic, housing, lifestyle behaviors) and by the NHL subtype. Patient demographics, including age, sex, and insurance type, were summarized using descriptive statistics.
RESULTS: Among NHL patients (N=129,090), only 4.16% (N=5,366) had documented Z code. The most prevalent NHL subtypes within this cohort were diffuse large B-cell lymphoma (DLBCL-34.74%), chronic lymphocytic leukemia of the B-cell type (CLLBCT-27.67%), and follicular lymphoma (FL-26.63%). Lifestyle-related factors, such as alcohol and tobacco use, physical inactivity, and receipt of health services due to lifestyle, represented 94.93% of documented Z codes. Patients were predominantly male (58.4%) with a mean age of 59.6 years, and 51.6% were covered by a preferred provider organization insurance plan.
CONCLUSIONS: Z code documentation in NHL patients was limited but provided valuable insights into social and behavioral health factors influencing care. The dominance of lifestyle-related codes underscores the need for targeted strategies to address behavioral health concerns and reduce disparities in NHL outcomes. Expanding Z code usage may enhance comprehensive care delivery in oncology settings, particularly among NHL patients.
Real-World Treatment Patterns of Advanced Melanoma in the United States
OBJECTIVES: Melanoma has a good prognosis if diagnosed at a localized stage. However, despite significant recent advances in therapy, treatments for patients with unresectable or metastatic melanoma are most often not curative. The objective of this study was to characterize real-world treatment patterns of advanced, unresectable melanoma patients who progress to second-line (2L) systemic treatment.
METHODS: Adults in a large administrative claims database between 1/2018-6/2024 were included in the analysis if they had: ≥2 claims for melanoma at least 7 days apart, melanoma as the primary tumor, ≥1 code for a systemic melanoma treatment, ≥1 code for metastatic disease, and had progressed to 2L treatment. Included pts had ≥3 months of continuous enrollment before the index date (first melanoma claim). Claims-based algorithms were used to identify monotherapy/combination regimens, by line of treatment (LOT). A Sankey diagram was constructed to illustrate the exact treatment pattern flows between LOT1 and LOT2.
RESULTS: 4,677 patients met study criteria and had progressed to a 2L regimen. 58% were male and the median age was 63.5 years. Among these patients, the most common 1L regimens were immune checkpoint inhibitors (ICI) (n=3,459, 74.0%): pembrolizumab (n=1,196, 25.6%), nivolumab (n=1,124, 24.0%), nivolumab+ipilimumab (n=1,020, 21.8%), nivolumab+relatlimab (n=101, 2.2%) or other anti-PD-1 therapy (n=18, 0.3%). Other frontline treatments received were targeted therapy for BRAF-V600 mutation (n=881, 18.8%), chemotherapy (n=187, 4.0%) or other regimens (n=168, 3.6%). After progression to 2L, the treatments became more heterogeneous with decreased utilization of ICI therapy (n=2,402, 50.3%). The most common 2L therapies were targeted therapy for a BRAF-V600 mutation (n=1,335, 28.5%), nivolumab (n=786, 16.8%), pembrolizumab (n=742, 15.9%), nivolumab+ipilimumab (n=741, 15.8%), chemotherapy (n=304, 6.5%) or other (n=685, 14.6%).
CONCLUSIONS: Real-world treatment patterns suggest that patients with advanced melanoma who fail 1L therapy have no clear standard of care as the 2L treatment landscape is heterogenous.
Navigating Real-World Data (RWD) Complexities: Operational Assessment Strategy to Identify Fit-For-Purpose Data Sources for Real-World Evidence (RWE) Studies With Regulatory Purpose (OASIS)
OBJECTIVES: Operationalizing RWD feasibility evaluation methods and the reporting structure for the subdimensions of relevance (data availability, adequacy of sample size, representativeness, timeliness, and coverage) and reliability (provenance, completeness, conformance, plausibility, and validity) prior to protocol finalization and data access, presents challenges. The first objective of this research was to compare these terms across recently published RWE guidance. The second objective was to develop aligned descriptions and create a global glossary. The third objective was to design evaluation methods and a reporting structure for each subdimension in the global glossary.
METHODS: Relevance and reliability evaluation methods and subdimension definitions were compared in 13 RWE guidance documents published between 2021 and 2024 by the International Council of Harmonization, European Network of Centres for Pharmacoepidemiology and Pharmacovigilance, and regulators across Asian Pacific, Europe, North America, South America, and the United Kingdom. Next, a global glossary and feasibility evaluation methods for each subdimension were developed. Finally, the glossary and assessment strategies were incorporated into feasibility reporting templates and piloted.
RESULTS: Of the 13 guidelines reviewed, most were missing definitions for each of the 10 subdimensions (with the exception of completeness which was defined in just over half): coverage and representativeness (84.6% [11/13]), adequacy of sample size, conformance, and plausibility (76.9% [10/13]), timeliness (69.2% [9/13]), availability, provenance, and validity (53.8% [7/13]), and completeness (46.2% [6/13]). Feasibility evaluation methods for relevance were found in 15.4% (2/13) of guidance documents, however, 0 guidelines included feasibility evaluation methods for reliability. Creating a global glossary and corresponding feasibility evaluation methods bridged a current gap found across published RWE guidelines.
CONCLUSIONS: The global glossary and feasibility evaluation methods developed from this research facilitated consistent assessment of relevance and reliability and their subdimensions. OASIS provided tools to improve RWD source selection which contributed to high-quality RWE that met regulatory standards.
Oncology Trial Emulation Using Real-World Electronic Health Record Data: Results of the Coalition to Advance Real-World Evidence Through Randomized Controlled Trial Emulation (CARE) Initiative
OBJECTIVES: The CARE Initiative seeks to advance understanding of when real-world data (RWD) can generate valid treatment effectiveness estimates by emulating randomized controlled trials (RCTs). We present findings from three oncology RCT emulations.
METHODS: Following feasibility assessments of candidate RCTs in available U.S. data sources, we emulated the KEYNOTE-189 (metastatic NSCLC) trial of first-line pembrolizumab+chemotherapy vs. chemotherapy in two electronic health record datasets (DS1 and DS2) and the PALOMA-2 (advanced breast cancer) trial of first-line palbociclib+letrozole vs. letrozole in DS1. Trial entry criteria were applied, as feasible. Treatment status was based on first-line regimens (using data partner-defined line of therapy algorithms) initiated during a fixed ascertainment period. Inverse probability of treatment weighting was used to control baseline confounding. Cox proportional hazards models were used to estimate the primary outcome(s). RWD-based estimates were assessed for qualitative agreement (same direction/magnitude) with RCT results.
RESULTS: The KEYNOTE-189 emulation real-world progression-free survival (rwPFS) hazard ratio (HR) in DS2 was of similar magnitude to the RCT finding, whereas the DS1 result did not demonstrate qualitative agreement [RCT: HR=0.52 (0.43, 0.64); DS2: HR=0.64 (0.47, 0.84); DS1: HR=0.81 (0.65, 1.00)]. KEYNOTE-189 emulation real-world overall survival estimates differed from the RCT results [RCT: 0.49 (0.38, 0.64), DS2: 0.89 (0.63, 1.29), DS1: 1.18 (0.95, 1.44)]. The PALOMA-2 emulation rwPFS HR also differed from RCT findings [RCT: HR=0.58 (0.46, 0.72); DS1: HR=0.84 (0.61, 1.23)].
CONCLUSIONS: Our results highlight that RWD oncology emulation conclusions depend on dataset features (e.g., care setting, therapy uptake, data completeness), treatment modality, and real-world clinical care. Future work should emphasize fit-for-purpose RWD selection and consideration of real-world care patterns to generate robust, interpretable real-world evidence.
New Tools Facilitating Health Economics and Outcome Research
Session Type: Research Podiums
This session highlights the utility of generative artificial intelligence, metamodeling, and an automated Markov cohort model generator in facilitating data extraction, evidence synthesis, information labelling, model conceptualization, and model programming. Collectively they reflect efforts in developing new methods and tools to enhance model programming and automation in health economics and outcomes research.
HELMET: A Benchmark Dataset for Evaluating Generative AI in Health Economics and Outcomes Research
OBJECTIVES: Generative artificial intelligence (GenAI), particularly large language models (LLMs), has shown potential automating tasks such as data extraction, evidence synthesis, and document labelling in health economics. However, there is no standardized benchmark to evaluate LLM performance in these tasks, particularly within the domains of cost-effectiveness models (CEM) and budget impact models (BIM). This study introduces the Health Economics Language Model Evaluative and Testing dataset (HELMET), designed to address this gap and advance AI applications for Health Economics and Outcomes Research (HEOR).
METHODS: HELMET comprises document-query-output triplets for data extraction, evidence synthesis, and information labelling. A total of 728 CEM, 256 BIM and 183 systematic literature reviews (SLRs) across indications in oncology, immunology, rare diseases, and chronic conditions were identified and retrieved from PubMed. Full-texts were used to construct the dataset, with queries generated by a prompt-based LLM (gpt-3.5-turbo and llama-index libraries). Data-extraction queries were generated for individual sentences in abstracts and stored with abstract-masked documents. For evidence synthesis, schemas summarizing evidence scopes were created from SLR result tables, guiding query development. Information labelling queries categorized document sections by domain and subheadings. Baseline performance was assessed using state-of-the-art LLMs with metrics like query-text alignment and token-level analysis.
RESULTS: HELMET contains 17,179 triplets for data-extraction, 1,647 for evidence synthesis and 18,980 for information labelling. Validation revealed a 0.92 Pearson correlation between query length and abstract sections in data-extraction, confirming queries were proportionally aligned with section content and length. Token analysis showed fewer missing tokens in queries compared to outputs across all datasets (89%,82%,78%), confirming comprehensive capture of contexts and alignment with LLM benchmarking standards.
CONCLUSIONS: HELMET provides a robust framework to evaluate and refine LLMs for HEOR applications, including evidence synthesis and economic modelling. By streamlining these processes, HELMET can support efficient decision-making in health economics, enhancing tools for researchers and developers.
Use of Metamodels in Health Economics to Bypass Complexity and Democratize Modeling
OBJECTIVES: All models, of necessity, simplify. However, the ability to incorporate and retain complexity is a requirement to ensure face validity and increase the accuracy of modelled outcomes. Model complexity impacts on the transparency of the underlying coding and increases run-times and hardware requirements. We demonstrate the utility of metamodeling to reduce computational burden and facilitate increased accessibility to complex models.
METHODS: A dynamic prevalence model of CKD was developed in R based on a system of ordinary differential equations (ODEs). A training and test sets of 20,000 and 10,000 model runs, respectively, were generated using Latin hypercube sampling, based on the variance of three model parameters, and used to fit a neural network based on mean absolute percentage errors (MAPE) between model and metamodel results. The resulting metamodel reduced the underlying ODEs to a series of linear algebraic expressions. Results, run-times and hardware requirements for the two models were compared.
RESULTS: The metamodel was able to accurately recreate the results of the underlying model (overall MAPE in training: 0.178%, overall MAPE in testing: 0.139%, worst scenario fit in testing: 0.427%). In testing, the metamodel was significantly faster than the original model (31 times faster for a single run).
CONCLUSIONS: Metamodels can reduce the computational burden of models on the end-user enabling, for example, the development of real-time dashboards for complex simulation models or broader value messaging. Similarly, the use of neural networks for metamodeling reduces complex models to a series of linear algebraic equations facilitating their usage in software such as Excel and enabling direct mathematical optimisation. This approach also enables the use of interpretable machine learning techniques, such as SHAP analysis, to increase transparency of the metamodel results. Each of these contributes to the democratization of knowledge and value messaging.
VBA and R to Automate Health Economic Model Programming
OBJECTIVES: Developing health economic models can be a time- and resource-consuming process. In an era of increasing automation, the question of whether this process can be accelerated arises. This study aimed to explore the potential of a Microsoft (MS) Excel-based tool for automation of cost-effectiveness models programming.
METHODS: An automated Markov cohort model generator was developed, utilizing a combination of Visual Basic for Applications (VBA) and R programming languages to prepare health economic models. Users provide input parameters into a pre-specified MS Excel workbook and then run an R script to generate a model in MS Excel. The tool is based on a fully deterministic algorithm, meaning it always produces the same results for a fixed input. This generator was employed to replicate two Markov models. The first one assessed the cost-effectiveness of two innovative prostheses for total hip replacement compared to a standard prosthesis. The second model compared the cost-effectiveness of combination therapy (lamivudine and zidovudine) with zidovudine alone in a four-state HIV/AIDS model.
RESULTS: The model generator successfully replicated both models on the first attempt. The replicated models were error-free, and their results matched those of the manually programmed models. The automated programming process for these models took 90 minutes in the first example and 28 in the second example. Both replicated models were capable of performing probabilistic sensitivity analysis and deterministic sensitivity analysis.
CONCLUSIONS: Utilizing the generator was relatively fast, straightforward, and intuitive. This way of programming decreases risk of a human error while being fully deterministic, increasing confidence in the produced results without the need for repeated testing. While AI may surpass this approach in the coming years, for now the generator can serve as a viable compromise between manual model programming and its automation.
The Use of Artificial Intelligence in the Development of Economic Models
OBJECTIVES: The use of artificial intelligence (AI) tools in health economics outcomes research is rapidly growing. Through a systematic literature review assisted with AI for screening, this study aimed to identify evidence where AI is used to aid in the conceptualization and/or programming of economic models.
METHODS: Ovid MEDLINE®, Embase, and Cochrane Library were searched for studies of AI-developed economic models published between January 2010 to December 2024, along with conference abstracts retained in Embase and CENTRAL from January 2022 to December 2024. Records were screened by one human reviewer and one AI reviewer using the Nested Knowledge® platform.
RESULTS: Of 1,872 unique records identified, 1,866 were excluded with 32 disagreements between human and AI reviewers after AI training (a 98.2% agreement rate). Five unique studies were included, the majority of which (4/5) reported on the use of Generative Pre-Trained Transformer 4 (GPT-4). Two AI-developed models were coded in Excel and one used R. Overall, the accuracy of AI models was variable with generation of an error-free model ranging from 60% to 97%. One study reported incremental cost-effectiveness ratios of error-free AI-generated models were within 1% of published models. Four studies reported AI modelling was a success compared to published models or experienced developer code. Success of the AI model was largely described as requiring specific prompt development, whereas general prompts failed to generate working code. Only one study reported hallucination of data by AI, which generated a clinically implausible transition in health states.
CONCLUSIONS: AI improved efficiency while maintaining accuracy for article screening for this systematic review. Early research suggests AI can help to conceptualize and program economic models, while also identifying evidence gaps. Use of AI could increase efficiency and decrease model development cost, with potential future growth in adoption of this approach.
Rethinking Clinical Meaningfulness and Value Assessment in the Context of Chronic Progressive Diseases
Session Type: Workshop
Topics: Clinical Outcomes, Health Policy & Regulatory, Health Technology Assessment
Level: Intermediate
PURPOSE: This workshop brings together experts on clinical outcome assessment and economic evaluation for a multiperspective dialogue on assessing the clinical meaningfulness and economic value of treatment benefits for chronic progressive diseases. DESCRIPTION: Therapies for chronic progressive diseases can potentially delay or prevent the cumulative societal burden associated with these conditions. Regulatory approval for these therapies requires evidence on the meaningfulness of treatment benefits observed in clinical trials, whereas access and reimbursement decisions require evidence of long-term value driven by cumulative treatment benefits. Efforts to assemble this evidence for treatments for chronic progressive diseases have motivated advances in the estimation and application of clinical meaningfulness thresholds, statistical methods for analyzing trial data, and approaches for extrapolating trial endpoints to long-term outcomes.Dr. Herring will orient the audience to the unique challenges presented by treatments for chronic progressive diseases (12 min). Dr. Coon will highlight distinctions between within-person changes and between-group differences and advocate for identifying context-specific meaningfulness thresholds by combining quantitative methods with qualitative stakeholder input (12 min). Dr. Lenderking will contrast the endpoint requirements for regulatory applications with those of clinical settings and health technology assessment (12 min). Dr. Whittington will discuss approaches for extrapolating treatment benefits over longer time horizons while emphasizing unique considerations for value assessment of disease-modifying therapies, such as valuing outcomes during life extension and real option value (12 min). We will conclude with a roundtable discussion (12 min). Audience polling will be used to gauge understanding and assess viewpoints. This workshop will be relevant for those involved in regulatory, access, and reimbursement decisions for treatments for chronic progressive diseases.
Moderator
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William L Herring, PhD
RTI Health Solutions, Research Triangle Park, NC, United States
Speakers
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Cheryl Coon, PhD
Critical Path Institute, Tucson, AZ, United States
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William Lenderking, PhD
William R Lenderking, LLC, Harvard, MA, United States
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Melanie D Whittington, MS, PhD
Leerink Center for Pharmacoeconomics, Boston, MA, United States
Melanie Whittington is the Managing Director and Head of the Leerink Center for Pharmacoeconomics where she leads pharmacoeconomic evaluations of in-development and recently approved pharmaceuticals and studies incentives for innovation. She is also a Senior Fellow at the Center for the Evaluation of Value and Risk in Health (CEVR) where she advises on CEVR projects related to value assessment, economic modeling, and CEVR databases.
Bridging the Credibility Gap: Establishing Competent and Reliable Scientific Evidence (CARSE) to Support Productive Healthcare Economic Information (HCEI) Discussions With US Payer Audiences
Session Type: Workshop
Topics: Economic Evaluation, Health Policy & Regulatory, Health Technology Assessment
Level: Introductory
PURPOSE: Although the FDA published guidance on communicating HCEI in 2018, HCEI discussions between manufacturers and health care decision-makers (HCDMs) remain challenging. Validating that economic evidence is based on CARSE is critical to bridging any real or perceived evidence credibility gaps. But what options do we have in determining CARSE, and what best practices exist in communicating rigorous HCEI in a relevant and useful way? This workshop will outline approaches to establishing CARSE and propose best practices for engaging HCDMs in productive conversations regarding HCEI from manufacturer, HCDM, and academic perspectives. DESCRIPTION: Dr. Lee will chair and introduce the topic, framing the HCEI opportunity and highlighting common stumbling blocks (10 minutes). Dr. Brixner will compare approaches to CARSE designation and discuss challenges and solutions to meet diverse stakeholder needs (10 minutes). Drs. Gillard and Daw will provide salient manufacturer and HCDM perspectives on the opportunities and challenges in advancing effective HCEI dialogue (20 minutes). Attendees will identify solutions to improve HCDM/manufacturer discussions in a simulated case study (20 minutes). This workshop will be of value to anyone involved in generating and communicating value evidence in US payer contexts.
Moderator
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Jeff Lee, PharmD
Lumanity, Franklin, TN, United States
Speakers
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Diana Brixner, RPh, PhD
University of Utah, Salt Lake City, UT, United States
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Kristin K Gillard, PharmD, PhD
BMS, Boulder, CO, United States
Dr. Kristin Gillard is a skilled health outcomes researcher with over 15 years of experience in pharmacoeconomics and real-world evidence generation. She received her PharmD from the University of Southern California and her PhD from the University of Arizona. Kristin is currently Executive Director at BMS, leading US HEOR strategy and execution to support the Neuroscience franchise. Prior to BMS, she held HEOR leadership roles at Esperion Therapeutics, Dermira, Allergan, and Xcenda/Cencora.
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Jessica Daw, MBA, PharmD
Sentara Health Plans, Virginia Beach, VA, United States
Value Flower: How Can We Make It Blossom in Value Assessments?
Session Type: Issue Panel
Topics: Health Technology Assessment, Health Policy & Regulatory
Level: Introductory
ISSUE: Medicines can bring value to patients, caregivers and society by, for example, keeping people in the workforce and advancing medical research and development. However, adopting broader value elements requires willingness and ability by all stakeholders and raises methods, evidence, and incentive challenges. Patients and society can benefit from innovations that improve health and produce spillover non-health effects. Researchers are developing new methods for measuring these elements, but technical and ethical challenges remain. Payers and health technology assessment (HTA) agencies consider criteria beyond cost-effectiveness in their deliberations, but guidance is limited and adoption is inconsistent, as HTA is typically tasked with informing reimbursement by the health system, leaving no clear answer to who should pay for non-health benefits. At the same time, the omission of broader value elements may miss opportunities to reward innovations that produce significant societal benefits. OVERVIEW: The session will address challenges in incorporating novel value elements into routine assessments and payer decisions. It will emphasise the need for stakeholder alignment on methodology, timing, evidence types, and incentives. The moderator will introduce the topic. Panellist 1 will present the patient perspective and discuss the areas of value that matter most to patients and how they can inform evidence generation at an early stage. Panellist 2 will discuss methodological challenges and research progress. Panellist 3 will cover payer challenges, including budgets restricted to the healthcare sector and uncertainty around broader value elements, as well as potential solutions. The discussion leader will engage the audience with polls and conclude with a panel discussion on developing systems to support the evidence generation, assessment, and utilisation of broader value elements.
Moderator
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Martina Garau, BA, MSc
Office of Health Economics, London, United Kingdom
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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Dan Ollendorf, MPH, PhD
Institute for Clinical & Economic Review, Boston, MA, United States
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Durhane Wong-Rieger, PhD
Canadian Organization for Rare Disorders, Toronto, ON, Canada
Flip (to) the Script: Is It Time to Rethink Health Economic Modeling for HTAs?
Session Type: Issue Panel
Topics: Economic Evaluation, Health Technology Assessment, Methodological & Statistical Research
Level: Intermediate
ISSUE: There are abundant cases of critical errors in decision-making and reporting resulting from organizations’ dependencies on spreadsheet workbooks for complex data-driven analytics. Spreadsheets easily become bloated and slow, and results often not reproducible. Nevertheless, spreadsheet modeling is highly prevalent in health economic modeling conducted for and evaluated by Pharma and HTA bodies, with accompanying risks to decision-making. Script-based languages such as R provide potential solutions, but have never had strong endorsement from HTAs, and may not yet fully address others’ needs. For some, HTA decisions based on spreadsheet modeling is just fine; others believe in significant benefits that could be derived from script-based approaches. OVERVIEW: This panel will discuss: What issues or concerns have speakers observed in the health economic models developed or reviewed? How do we best mitigate risks in results or decision-making from spreadsheet-induced errors? Does the future lie in script-based modeling (using R or other languages)? What would it take for both HTAs and Pharma to ‘flip to script’?
Moderator
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Dominic Muston, BSc, MSc
Merck & Co. Inc, Summit, NJ, United States
Speakers
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Nicole Mittmann, MSc, PhD
Canada's Drug Agency, Toronto, ON, Canada
In her Chief Scientist role, Dr. Mittmann is responsible for ensuring that CDA (a.ka. CADTH) actively learns, ensures rigour and quality, mobilizes evidence, and links science to strategy. In her Scientific Evidence, Methodologies and Resources role, Nicole leads CDA’s shared science groups, including the Science and Methods, Health Economics, Research Information Services, Publishing, Early Scientific Advice and Real-World Evidence teams.
In her academic capacity, Dr. Mittmann holds an MSc and PhD in pharmacology from the University of Toronto. She holds a faculty position as an assistant professor at the University of Toronto in the Department of Pharmacology & Toxicology; and is cross-appointed to the Institute for Health Policy, Management and Evaluation. She is also an associate scientist at Sunnybrook Health Sciences Centre in Toronto, Canada. Dr. Mittmann has conducted and collaborated on notable research in the areas of economic evaluations, outcomes research, and drug/patient safety. Research methodologies include the examination of large databases, economic methodologies, and decision analysis.
She likes to link, leverage and liberate data and evidence.
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Robert Smith
SCHARR, University of Sheffield, Sheffield, United Kingdom
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Rebekah Heinzen Borse, PhD
Merck & Co. Inc, Washington, DC, United States
IRA Under Trump: What Is Next?
Session Type: Issue Panel
Topics: Health Policy & Regulatory
Level: Introductory
ISSUE: The Inflation Reduction Act (IRA) has changed the US policy and drug pricing landscape. However, there is potential for significant shifts as the Trump administration implements its policy agenda with a unified Republican Congress. What changes will the new administration make to the IRA MFP determination and Part D redesign? Will MFP-related changes be accompanied by legislative changes to the orphan exclusions and qualified single-source drug (QSSD) definitions? Or will potential policy changes be driven by cost savings and reintroducing policies incorporating international reference pricing? Will changes extend beyond IRA impacts as we know them today? Will market stabilization policies like the Part D demonstration be rescinded? And what would these changes mean for evidence generation and value assessment? This panel will explore (1) Potential changes to IRA price determination and Part D Redesign under the Trump administration; (2) Implications of these changes for demonstrating and evaluating value; and (3) Consequences of these policy developments for biopharmaceutical access and innovation. OVERVIEW: Potential changes under the Trump administration are uncertain, but some could broadly impact the US healthcare value and innovation ecosystem. This panel will critically evaluate some of the most impactful potential policy changes. Lisa Joldersma will begin the conversation by describing the nature of these potential changes, including the scope of potential changes, and highlighting the events that need to occur for these policies to be implemented. Mike Ciarametaro will discuss the value demonstration and evaluation implications, including potential negotiation impacts and value demonstration ramifications for the Part D market. Ulrich Neumann will review scientific evidence on the potential consequences for future innovation, including implications for the overall level of innovation, incentives for certain types of innovation (disease area, small vs. large molecule, etc.), and impact on patient access.
Moderator
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Michael Ciarametaro, BS, MA, MBA
Avalere Health, Washington, DC, United States
Speakers
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Lisa Joldersma, JD
Birch Point Strategies, LLC, Washington, DC, United States
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Ulrich Neumann, BA, BSc, MA, MBA, MSc
Johnson & Johnson, Titusville, NJ, United States
AI Agents and Guardrails in HEOR: The Ultimate Solution to GenAI Shortcomings or Just Another Overhyped Tool?
Session Type: Issue Panel
Topics: Methodological & Statistical Research, Health Technology Assessment, Study Approaches
Level: Introductory
ISSUE: As AI agents (autonomous systems leveraging large language models (LLMs) and related algorithms) become more prevalent in HEOR, a critical debate emerges: Should these agents be widely integrated into decision-making processes, given ongoing concerns related to transparency, ethical implications, and accountability? Are robust guardrails (structured policies, mechanisms, and technical controls that ensure outputs are safe, accurate, and ethical) sufficient to mitigate these risks? This session will debate whether AI agents’ promise outweighs the potential hazards. OVERVIEW: Dr. Foluso Agboola will begin the session by providing a short history of the evolution of AI implementation in HEOR (5 minutes).This issue panel will feature three distinct perspectives: Mr. Sven Klijn (12 minutes): Will define AI agents and highlight their capabilities, illustrating how automation supports scalability, consistency, and performance uplift. This perspective will argue that integrating AI agents can advance HEOR, optimize resources, and enable informed decisions. Dr. Tim Disher (12 minutes): Will focus on the risks and negative externalities, including lack of transparency, accountabilities, ethical concerns, and unintended consequences. This perspective will challenge assumptions about unfettered AI adoption, urging caution and oversight. Dr. Ghayath Janoudi (12 minutes): Will discuss the concept of guardrails—defining them as structured safeguards to ensure responsible deployment. By exploring HTA guidance, best practices, and accountability measures, this perspective will assert that AI agents can be harnessed responsibly without stifling innovation. Following these presentations, there will be a 15-minute audience Q&A and debate period, offering the audience actionable insights to navigate the balance between AI-driven potential and the imperative for integrity, transparency, and trust.
Moderator
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Foluso Agboola, MPH, MD
Institute for Clinical and Economic Review (ICER), Springfield, MA, United States
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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Tim Disher, RN, PhD
Loon, West Porters Lake, NS, Canada
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Ghayath Janoudi, MSc, PhD
Loon, Cantley, QC, Canada
Enhancing Regulatory Engagement to Streamline and Advance Patient-Focused Drug Development
Session Type: Issue Panel
Topics: Patient-Centered Research, Methodological & Statistical Research
Level: Intermediate
ISSUE: Sponsors routinely collect patient experience data (PED) to inform their understanding of a disease area and ensure that they are meeting the needs of patients. To advance patient-focused drug development, alignment between industry, patient advocacy groups, and regulators needs to start early in the development process to support identification of what is clinically meaningful to patients, ensure that the sponsor’s program deliver fit-for-purpose data, inform regulatory decisions, and inclusion of PED into labelling and patient-facing resources. Although the regulators encourage Industry to engage early and often regarding the collection and use of PED in development programs, Industry is often unclear regarding when to engage and what information is needed to support PED discussions to elicit actionable feedback. To facilitate strategic and timely discussions on the use of PED in product development and regulatory decision-making, resources including frameworks, best practices documents are being developed by stakeholders, and there continues to be a need for regulatory feedback and guidance. In this session, panelists will discuss the realities of early regulatory engagement on topics related to patient experience data and present frameworks that can help sponsors as they develop their regulatory engagement strategy. OVERVIEW: In this session, the moderator will provide background on current practices and recommendations. FDA representative will discuss regulatory considerations for engagement with regulators related to PED (e.g., qualitative PED, COAs, patient preference information). Industry panelists will present case examples and discuss frameworks (E.g., BIO’s FDA-Sponsor Engagement Framework for Patient Preference Information) that are being developed to support regulators call for “early engagement” and help support regulatory discussions.
Moderator
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Pujita Vaidya
Sanofi, Alexandria, VA, United States
Speakers
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Michelle Campbell, PhD
US Food and Drug Administration, Silver Spring, MD, United States
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Samantha Roberts
Astra Zeneca, Gaithersburg, MD, United States
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Rebecca Noel, DrPH
AMGEN, Thousand Oaks, CA, United States
10:30 AM - 1:30 PM
Poster Session 3
Session Type: Research Posters
11:15 AM - 1:00 PM
Lunch Service (Exhibit Hall)
Session Type: General Meeting
As you enjoy your lunch in the Poster and Exhibit Hall, seize the opportunity to engage in meaningful conversations with fellow attendees. Take this time to exchange ideas, forge new partnerships, or simply enjoy casual conversation. Provided by ISPOR
11:30 AM - 12:15 PM
Student Research Poster Tour
Session Type: Research Posters
This tour will take place during Poster Session 3, Poster will be hung from 10:30 AM - 1:30 PM.
Posters featured in this tour:
PT25: The Impact of Financial Assistance Programs on Medication Adherence: A Systematic Review With AI-Driven Prediction
PT26: Cost-effectiveness Analysis of Sunvozertinib as a Second-line Treatment for Advanced Non-Small Cell Lung Cancer With EGFR exon20ins Mutation: An Economic Evaluation Based on MAIC
PT27: Cost-Effectiveness of Delaying Progression of Alzheimer's Disease With Novel Monoclonal Antibodies: A Societal Perspective
PT28: Evaluation of Measurement Properties of Health Assessment Questionnaire Disability Index (HAQ-DI) Among Gout Populations in China
PT29: Increased Incidence of Parkinson Disease Associated With Antiseizure Medication Use
PT30: Evolving Trends in Racial and Ethnic Disparities in Syphilis Prevalence Among People Who Are Pregnant in the United States From 2016 to 2023
Access and Policy Poster Tour
Session Type: Research Posters
This tour will take place during Poster Session 3, Poster will be hung from 10:30 AM - 1:30 PM.
Posters featured in this tour:
PT19: Timing of Health Technology Assessment in the United States: An Evaluation of ICER Reviews Over Seven Years
PT20: Estimating the Cost at Which GLP-1 RAs Would Become Cost-effective for Multimorbid Type 2 Diabetes Patients in Canada
PT21: US Commercial Health Plan Coverage of Oncology Therapies: 2017 - 2024
PT22: Payer Archetypes and Decision-Making in the United States (US): A Framework for Generalized Cost-Effectiveness Analysis (GCEA) Value Elements to Optimize Patient Access and Equity
PT23: Availability, Pricing, and Affordability of Antithrombotic Medicines in Addis Ababa, Ethiopia: Implications for Health Policy
PT24: A Quantitative Exploration of Challenges to the Sustainability of the United States Biosimilar Market
11:45 AM - 12:15 PM
Is IRA Becoming America’s HTA?
Session Type: Exhibit Hall Theaters
Topics: Health Technology Assessment, Clinical Outcomes, Economic Evaluation
Level: Intermediate
11:45 AM - 12:45 PM
Definition and Consistent Approaches to Integrating Evidence-Based, Multi-Stakeholder, and Perspectives-Based Advocacy in Rare Disease Health Technology Assessment (HTA)
Session Type: Forums
Topics: Health Technology Assessment, Health Policy & Regulatory, Medical Technologies
Level: Intermediate
Involvement of stakeholders in Rare Disease technology appraisal process may be fragmented from the development of a technology and leading to engagement in its recommendation into clinical practice.
More concerted efforts in securing multi-stakeholder engagement and integrating their perspectives can enhance the value, health equity, and impact of HTA. This is especially true in Rare Disease technologies, where greater uncertainty in value exists due to the small and heterogeneous populations and more limited disease knowledge. ?
This session discusses potential systematic and practical approaches or frameworks for integrating stakeholders (including patients, patient organisations, caregivers, clinicians and general public) perspectives in the HTA process.
Involvement of people in Health Technology Assessment is recognized as an important contribution to determining the need and articulating the value of new technologies. Whilst this position is broadly accepted, what is less clear is ‘how’ to involve people. By this we mean a range of stakeholders patients, public, healthcare professionals.
Our session will briefly report the findings of a systematic review which has evaluated the evidence for the involvement of people in Rare Disease HTA. We will summarize the evidence on how people are involved in rare disease HTA, and the contributions this appears to have made. This systematic review mapped the key stages of people's involvement in the HTA process (e.g., determination of unmet needs; trial design; HTA submission; decision-making committee meeting; and post-submission communication and dissemination.
Aim: The aim of the session is to share findings from the review and discuss how these findings could be used to develop a toolkit for stakeholders to use evidence based advocacy in HTA.
Moderator
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Sheela Upadhyaya, Dip
Independent Consultant, London, United Kingdom
Speakers
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Keith Howard Tolley, BA, MPhil, MPP
Tolley Limited, Buxton, United Kingdom
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Rodolfo Castro
Oswaldo Cruz Foundation, Rio de Janeiro, Brazil
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Mohit Jain, MBA, PhD
IntraBio, London, United Kingdom
Health Preference Research Today: How Patient-Centered Is It and How Can It Be More Patient-Centric?
Session Type: Forums
Topics: Patient-Centered Research, Health Technology Assessment, Methodological & Statistical Research
Level: Intermediate
How patient-centered is health preference research (HPR) and how can we make it more patient-centric? The ISPOR Patient-Centered SIG invites all stakeholders (i.e., patient-centered, health preference, HEOR) to this session to understand recent trends in patient-centricity in HPR and learn about strategies to improve patient-centricity in HPR.
Patient-centricity and engagement are key to ensuring that health outcomes research adequately reflects patient perspectives and priorities. Patient Preference Information (PPI) can complement other aspects of patient experience data (PED) such as patient-reported outcomes by measuring patient willingness to trade different aspects of an intervention. Patient engagement involves patients as research partners to ensure patient-centricity of the research itself. Patient-centricity and patient engagement are important for all aspects of PED, including PPI. This workshop will cover the current state of the field for patient centricity in PPI and demonstrate how to engage patients at all stages of HPR research.
Jessica Roydhouse will present findings from an HPR review study and share key conclusions on patient-centricity of HPR studies, including patient engagement in study design and HPR attribute development. Siu Hing Lo will share insights from a recent review on the current status of reporting of PED to inform patient preference study attribute selection and other study design aspects, and patient engagement in patient health preference studies. Angie Botto-van Bemden will share her experience as a patient partner helping communities capture patient preference information most useful for decision-making. Ryan Fischer will share his experiences and lessons learnt as a patient advocacy representative researching patient and caregiver preferences for gene therapy in Duchenne muscular dystrophy.
Interactive examples and audience engagement through real-time polling and discussion will enable participants to critically assess and evaluate ways to incorporate the Patient Voice and engage patients in HPR that is meaningful to patients.
Moderator
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Jessica Roydhouse, PhD
Menzies Institute for Medical Research, University of Tasmania, Hobart, Australia
Speakers
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Siu Hing Lo, MA, MSc, PhD
Acaster Lloyd, London, United Kingdom
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Angie Botto-van Bemden, PhD
Musculoskeletal Research International, Holiday, FL, United States
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Ryan Fischer, BA
Foundation for Angelman Syndrome Therapeutics, Marble Falls, TX, United States
Leveraging Automated Tools for Literature Reviews in Health Economics and Outcomes Research: Opportunities, Challenges, and Best Practices
Session Type: Forums
Topics: Health Technology Assessment, Methodological & Statistical Research, Study Approaches
Level: Intermediate
The increasing complexity and volume of literature reviews (LR) necessitate efficient and scalable approaches to evidence synthesis. Automated tools, such as artificial intelligence-assisted screening and data extraction platforms, have the potential to streamline LRs by reducing time and labor, improving bias and reproducibility. However, it is crucial that appropriate human oversight, transparency and integration of existing research practices are incorporated when implementing such tools.
This forum will explore the role of automation in LR with a concrete case study of a scoping review reporting the experience of using a commercially available evidence synthesis platform for an ongoing Health Equity Special Interest Group (HER SIG) project.
The discussion will address the following key focus areas:
• The role of automation in LR workflows, including study selection, data extraction, and synthesis.
• Key challenges and limitations in adopting novel tools, such as transparency, validation, and integration with traditional methodologies and current LR practices.
• Lessons learned from implementing automated tools in the scoping review for the "State of Play" project sponsored by ISPOR HER SIG.
• Strategies to ensure best scientific practices while driving efficiency with human-in-the-loop approaches to automation, as well as appropriate oversight, controls, and implementation of AI tools into LR workflows.
• Opportunities for broader adoption of LR automation tools in academic, regulatory and scientific organizations settings.
The forum will adhere strictly to ISPOR’s Code of Conduct and Antitrust Guidelines. It will be an educational discussion without any promotional intent, ensuring an open and unbiased exchange of ideas.
As part of the forum, we welcome perspectives from researchers, HTA assessors, data analysts, and industry stakeholders to collectively explore how automation can enhance the rigor and efficiency of literature reviews in HEOR.
Moderator
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Ramiro E Gilardino, MHA, MSc, MD
Independent, Zurich, Switzerland
Impact-driven healthcare executive with 15+ years of leadership in Global Market Access, Health Policy, and HEOR. Successfully led strategies that improved patient access, drove reimbursement success, and shaped health policy in pharma, biotech, and global organizations. Expert in advancing HTA frameworks and forging stakeholder partnerships to promote health equity and deliver value-based healthcare solutions globally.
Speakers
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Ranita M Tarchand, BA, MS
Nested Knowledge, Farmington, MN, United States
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Rajshree Pandey, MPH, PhD
Independent, Boston, MA, United States
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Mitch Higashi, PhD
ISPOR, Villanova, PA, United States
The Unexpected Liver Disease MASH: The Clinical Burden and Cost of Inaction of an Underdiagnosed Metabolic Disease
Topics: Epidemiology & Public Health
Level: Introductory
1:00 PM - 1:30 PM
Unlocking the Potential of Routine Patient Health Records for RWE
Session Type: Exhibit Hall Theaters
Topics: Real World Data & Information Systems, Study Approaches, Clinical Outcomes
Level: Intermediate
1:30 PM - 2:30 PM
New Professional Session: Leading With Curiosity—How Lifelong Learning Drives Success
Session Type: Forums
Topics: Organizational Practices
Join us for an engaging panel discussion with esteemed health economists from diverse industries to explore the pivotal role of curiosity along their career journeys. This session will delve into how curiosity drives innovation, enhances decision-making, and fosters adaptive strategies within the realm of health economics. Panelists will share personal experiences on cultivating a culture of curiosity, addressing challenges with curiosity, and leveraging curiosity in their leadership. Join us to discover how cultivating curiosity can be a competitive advantage in navigating complex career paths for health economists.
Moderator
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Irwin Tran, PharmD, MS, ACC
NextLeader Coaching, Alameda, CA, United States
Speakers
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Florence Haruna, MPhil
Zipline, Accra, Ghana
Florence Haruna is a public health researcher and impact strategist with expertise in health systems, implementation science, and global health equity. As an Impact Research Officer, she leads initiatives focused on maternal health, immunization, and healthcare accessibility. With 5+ years of experience mentoring young professionals, Florence is passionate about capacity-building and curiosity-driven learning. Florence is committed to advancing equitable healthcare solutions through innovation, data-driven decision-making, policy advocacy, and mentorship.
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Monica Yu, MSc, PhD
Imperial College London, London, United Kingdom
Monica Yu is an experienced professional in health economics, health services research and health information management, with over 10 years of experience spanning government, private sector, and academic roles. She recently completed her PhD at Imperial College London, where her work focused on comparative effectiveness research leveraging RWE in hematology. Monica is passionate about leveraging data-driven insights to enhance healthcare policy and patient outcomes.
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Aryana Sepassi, PharmD
University of California, Irvine, School of Pharmacy & Pharmaceutical Sciences, Carlsbad, CA, United States
1:45 PM - 2:45 PM
Prompt Engineering: Harnessing Generative AI for HEOR
Session Type: Spotlight
Topics: Methodological & Statistical Research, Study Approaches, Real World Data & Information Systems
Level: Intermediate
PURPOSE: Generative AI, particularly large language models (LLMs), can transform evidence synthesis, health economic modeling, and real-world evidence (RWE) generation. To realize this potential HEOR professionals need to master prompt engineering—the art and science of crafting instructions that guide LLMs to produce precise, contextually relevant outputs. Offered by members of the ISPOR Generative AI Working Group, this session will teach participants how to optimize their prompts to tasks such as data extraction, health economic modeling, and generating insights from real-world datasets.
DESCRIPTION: This session begins with a primer on LLMs, focusing on their underlying mechanics and how thoughtful prompt design improves output quality. We will highlight the wide range of HEOR applications for LLMs.Participants will explore key prompt engineering techniques, including Zero-shot, Few-shot, Chain of Thought, Tree of Thoughts, and persona prompting, with examples tailored to evidence synthesis, HEOR, and RWE tasks. Practical applications, such as extracting data, synthesizing insights from real-world datasets, and health economic modeling, will be demonstrated.To ensure engagement, the session features open discussions where participants collaboratively explore prompt engineering challenges and solutions. Attendees will also discuss LLM capabilities and limitations, such as contextual retention and accuracy issues, and learn how effective prompting mitigates these challenges.This interactive format allows participants to share experiences, ask questions, and develop practical strategies for integrating LLMs into HEOR and RWE tasks. While optional, participants are encouraged to experiment with these techniques using tablets or mobile devices.
Moderator
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Jag Chhatwal, PhD
Harvard Medical School / Massachusetts General Hospital, Wilmington, MA, United States
Dr. Chhatwal is an associate professor at Harvard Medical School and Director of the Institute for Technology Assessment at Massachusetts General Hospital. Dr. Chhatwal has co-authored over 120 original research articles and editorials in peer-reviewed journals. His work has been cited in leading media outlets, including CNN, Forbes, National Public Radio, New York Times, and Wall Street Journal.
Since 2011, Dr. Chhatwal has taught several workshops and short courses on decision modeling and AI at the ISPOR. He is a member of ISPOR AI Working Group. He also serves as an associate editor of Value in Health and is serving as the guest editor for special issues on AI in Value in Health.
Speakers
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Rachael Fleurence, MSc, PhD
National Institutes of Health, Bethesda, MD, United States
Dr Fleurence is a Senior Advisor at the National Institutes of Health where she is working on launching a national initiative to eliminate Hepatitis C in the United-States. Dr Fleurence is also affiliated with the National Institute of Biomedical Imaging and Bioengineering where she works on advances in Artificial Intelligence and Machine Learning. Dr Fleurence currently co-leads the ISPOR Task Force on the suitability of EHR data for Health Technology Assessments. Previously, Dr Fleurence served as a senior health advisor in the Biden-Harris White House, Dr. Fleurence received a BA from Cambridge University (United Kingdom), an MA in business management from ESSEC-Paris (France), and an MSc and PhD in health economics from the University of York (UK).
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Turgay Ayer, PhD
Value Analytics Labs, Boston, MA, United States
Accelerating Health Economics Research Through Privacy-Enhancing Technologies (PETs)
Session Type: Other Breakout Session
Topics: Health Technology Assessment, Health Policy & Regulatory, Real World Data & Information Systems
Level: Advanced
PURPOSE: This panel brings together leaders in health economics, privacy technology, and outcomes research to address how Privacy-Enhancing Technologies (PETs) are transforming the speed and scale of HEOR studies. The objective of this session is to explore practical implementation strategies that automate regulatory compliance for real-world evidence (RWE) while maintaining research integrity. DESCRIPTION: Health economics researchers face growing challenges in accessing and analyzing real-world data while meeting privacy requirements. This panel addresses five critical angles that directly impact HEOR studies including Data Access, Research Efficiency, Quality Assurance, Cost Analysis, and Innovation. This session will start with an introduction of HEOR data bottlenecks—the impact of privacy regulations on research timelines, hidden costs of manual compliance processes, data access bottlenecks in multi-site studies, and case studies of delayed or limited studies due to privacy constraints. PETs can be leveraged as a strategic solution—the panel will share their perspectives on ROI analysis of PET implementation, success stories in automated compliance and how to maintain research quality while enhancing privacy. The session will continue by exploring practical implementation strategies for PET adoption including integration with existing workflows, staff training and resource allocation, quality assurance in privacy-preserved analysis, and best practices for multi-site implementation. The session will conclude with an interactive problem-solving workshop between audience and panel members covering real-world implementation scenarios, overcoming common challenges, regulatory compliance strategies, and resource optimization techniques. This session would benefit compliance executives and teams who utilize large scale data for HEOR.
Moderator
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Timothy Nobles
Integral Privacy Technologies, New York City, NY, United States
Timothy Nobles, Chief Commercial Officer at Integral, is passionate about empowering organizations to explore the full potential of their data while maintaining the highest standards of privacy and compliance. With over 20 years of experience in data and analytics, he has held leadership roles at innovative companies across multiple industries. Prior to Integral, Timothy served as Chief Product Officer at Trilliant Health and Head of Product at Embold Health, where he developed advanced analytics solutions for healthcare providers and payers.
Speakers
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Christine Lee
AnalyticsIQ, Atlanta, GA, United States
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Kenzie Alexander, BA
Datavant, Denver, CO, United States
Mackenzie (Kenzie) Alexander leads Datavant’s Privacy Product Success (solutions) group. Prior to this role, Kenzie spent time building Datavant’s cloud partnerships strategy including Privacy Enhancing Technology integrations.
Kenzie has worked at the intersection of strategy, sales, and innovation for the past 10 years. Prior to joining Datavant, Kenzie worked across industries and clients in McKinsey’s Marketing & Sales practice. Before McKinsey she served in various sales management roles at Anheuser-Busch InBev, focused primarily with acquired craft brewery partners.
Kenzie spent her undergraduate studying Energy, Environmental, and Chemical Engineering at Washington University in St. Louis.
Bridging the Gap in Early-Stage Clinical Research: Lessons for EU Stakeholders From the US FDA Early Feasibility Studies Program
Session Type: Issue Panel
Topics: Health Policy & Regulatory, Medical Technologies, Patient-Centered Research
Level: Intermediate
ISSUE: In developing innovative, significant risk MDs, the need to further device design and/or functionality may require early-stage clinical investigations when non-clinical testing is either unavailable or not informative. Increased risk to patients may hamper these studies in many countries. The US FDA established an EFS Program in 2013 aimed to provide guidance, advice, and oversight to MD developers while safeguarding patients enrolled in these studies. The fragmented EU regulatory system creates challenges to conducting EFS and may hinder innovation. What can the EU and other global jurisdictions learn from the FDA experience to facilitate such studies in a safe and harmonized manner? OVERVIEW: The panel, made up of representatives from the FDA, industry, and academia aims to discuss lessons learned and the strengths and limitations of the FDA EFS Program. Prof. Rosanna Tarricone (10 minutes) will moderate the session and present the rationale for EFS and their global diffusion. Dr. Andrew Farb (TBC) (15 min.) will highlight the scope, challenges, performance, and best practices developed from the first ten years of FDA EFS Program implementation. Mr. Kevin Drisko (10 min.) will offer insights into the advantages of EFS as one integrated step in the process of MD clinical evidence generation. Prof. Giuditta Callea (10 min.) will discuss the challenges of pre-market clinical research for MDs in the EU representing multi-stakeholder perspectives from patients, trialists, and hospitals and will present findings of the HEU-EFS project. In the last 15 minutes, Prof. Tarricone will direct audience questions to the panelists in a roundtable.Many stakeholders will benefit from attending this session, including regulators, healthcare providers, patient associations, academic and research organizations, CROs, ethical and legal experts, and technology developers.
Moderator
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Rosanna Tarricone, PhD
Bocconi University, Rome, Italy
Speakers
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Andrew Farb, MD
US Food and Drug Administration, Silver Spring, MD, United States
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Kevin Drisko, Mr.
Edwards Lifesciences, Irvine, CA, United States
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Giuditta Callea, PhD
SDA Bocconi School of Management, Milano, Italy
Patient-Reported Outcomes in Clinical Trials and Routine Healthcare
Session Type: Research Podiums
Despite increasing interest in patient-reported outcomes (PROs), their use in clinical trials and everyday care is still relatively poorly embedded. This session aims to review current practices relating to the use of PROs in clinical trials and clinical care to to identify next steps in more effectively incorporating PROs into these areas.
Integrating Patient-Reported Outcomes in Clinical Care - Opportunities and Roadblocks From the Patient Perspective: A Scoping Review
OBJECTIVES: The explosion of digital technologies and focus on patient-centered care enable the integration of patient-reported outcomes (PRO) in clinical care. PROs are routinely requested in healthcare decision-making but evidence respecting their use in routine clinical care is fragmented. This scoping review summarized how patients perceive the use of PROs (i.e., benefits of and barriers to) in their interactions with clinicians and overall care, across disease areas and settings.
METHODS: Embase and MEDLINE were searched in November 2024 for publications dating to 2014. Eligible papers were full-text commentaries and primary/secondary research on patient benefits, impact in clinical care management at the patient (individual) level and patient-perceived barriers. PRO psychometric properties and analysis were beyond the review scope. Supplementary searches employed a snowballing method, and websites of key organizations were manually searched. Thematic analysis by PRO category, outcomes, study design, and other contextual factors was conducted. Screening and extraction were conducted by a trained reviewer and validated by a senior reviewer.
RESULTS: After de-duplication, 1,303 articles were screened at the title/abstract level; 14 were included for full-text review and 14 were identified through snowballing. In total, 12 articles were included (theoretical analyses, data driven analyses, reviews [n=3 each], commentaries [n=1], expert survey [n=1]). Publications were heterogeneous in terms of objectives and settings. Across the included studies, the greatest PRO impact was on improving patient-clinician communication, information provision, encouraging positive health behaviors and enhancing patient self-management. Barriers related to accessibility issues (language proficiency, health and digital literacy) and administrative burden (time to complete PROs) were noted.
CONCLUSIONS: This scoping review demonstrated the consensus on the positive impact of PRO data in improving healthcare from the patient perspective. PRO implementation strategies in clinical practice by removing structural barriers that may perpetuate existing health disparities will ensure equitable improvement in patient health.
Are Pediatric Trials Including More Patient-Centered Outcomes?
OBJECTIVES: To describe child, family or caregiver-important outcomes in pediatric randomized controlled trials, from peer-reviewed literature, over a 10-year period.
METHODS: The search was conducted in Ovid MEDLINE from 2014 to June using a strategy to identify pediatric trials. Included trials: i) had clustered or individualized randomization, ii) focused on infants, children, adolescents or youth <25, or ii) were maternal-infant or parental trials including at least one endpoint of the infant/child. In phase 1 (2014-2019), all abstracts were screened and data extracted. In phase 2 (2019-2024), only 25% of abstract and full-text screening of the search was conducted by 2 reviewers.The data extracted were: i) report of patient engagement in trial endpoint selection or development; ii) inclusion of psychosocial, or perceived health or quality of life endpoints coded using standardized procedures, and iii) the tool, agent or respondent of the primary co-primary, and secondary outcomes. Trial characteristics such as: ID/registration #, inclusion age at eligibility, unit of randomization (individual or clustered), intervention type (pharmacological, surgical, medical-technology, other), trial region, and funding type (industry, NGO, government), were extracted.
RESULTS: 1100 randomized clinical trials demonstrated low rates of cited child, family or caregiver input or selection with trial endpoints <10% in each trial year. Specific child or youth engagement, (as opposed to parent/caregiver) increased from 3 to 8% over the 10-year period. Inclusion of psychosocial, perceived health or quality of life primary endpoints ranged from 31-40%, but increased for secondary endpoints from 15 to 30%.
CONCLUSIONS: Despite global initiatives to increase patient engagement in pediatric trials, child, parent, or caregiver engagement in selection of trial endpoint remains low. The doubling of psychosocial, perceived health or quality of life as secondary endpoints demonstrates potential for increasing demand for evidence based on patient-important outcomes.
Comparative Analysis of Large Language Models for Extracting Patient-Reported Outcome Measures From Clinical Trial Protocols in Lymphoma
OBJECTIVES: Patient-reported outcome measures (PROMs) are essential in clinical trials as they directly capture data on patients' experiences with their health conditions. Collecting information on the types of PROMs used in clinical trials face challenges due to varying terminologies and fragmented data. The current study aimed to evaluate the performance of large language models (LLMs) in extracting PROMs from protocols from the ClinicalTrials.gov database in lymphoma and compare their performance against an expert-established reference standard, utilizing a zero-shot approach.
METHODS: A sample of outcome list of 300 protocols from lymphoma clinical trials was independently reviewed by domain experts to identify PROMs, establishing a gold standard. Three LLMs - gemma-2-9b-it, llama-3.3-70b, and chatgpt-4o-mini-2024-07-18 - were then applied to the same dataset using a tailor-made prompt to extract PROMs. Accuracy, precision and recall were calculated to evaluate the performance of the LLMs against the gold standard.
RESULTS: Among the three LLMs, llama-3.3-70b demonstrated the highest performance, achieving an accuracy of 73.36%, a precision of 90.48%, and a recall of 79.50%. The gemma-2-9b-it model showed moderate performance (63.25% accuracy, 80.27% precision and 74.90% recall), while gpt-4o-mini-2024-07-18 achieved the lowest accuracy of 62.36%, but maintained a relatively high precision of 87.23% and 68.62% recall. Notably, all models made characteristic mistakes (e.g., confusing EQ-5D versions, including FACT-G when it was part of another PROM), which can be addressed through standard downstream data curation steps.
CONCLUSIONS: LLMs, notably llama-3.3-70b can serve as effective tools for identifying PROMs from protocols of clinical trials in lymphoma, potentially reducing the manual effort required for systematic evidence synthesis. Beyond direct extraction, these tools can support live evidence management of PROMS, help generate synthetic training data for simpler models and facilitate automated pipelines for tracking of PROM usage trends in clinical research. These findings demonstrate a strong baseline for further studies to enhance LLM performance.
Introduction of Distress Thermometer (DT) Screening in the US Community Oncology Setting: A Retrospective Study of Electronic Health Records (EHR) Integration
OBJECTIVES: The DT is a well-validated instrument for screening psychological distress and health-related social concerns among patients with cancer and other chronic conditions. Integrating the DT into EHRs may facilitate providers’ ability to address these health determinants as part of routine care, improving outcomes and quality of life. This study evaluated DT utilization following EHR implementation in 2023 across a large network of US community oncology clinics.
METHODS: This was a retrospective, observational study of patients treated within The US Oncology Network following integration of the DT into the iKnowMed EHR. Adult patients with cancer who visited a clinic between 7/1/2023-11/30/24 were classified as having or lacking DT screening during this period. Patterns of DT utilization were assessed descriptively.
RESULTS: Among 235,761 eligible patients, 29,062 (12%) completed DT screening in the EHR and 206,699 (88%) did not, including 2,704 who declined. EHR documentation of DT screening rates were 16% (n=9,232) and 11% (n=19,830) for patients with (n=57,234) and without metastases (n=178,527), respectively. Clinically elevated initial distress (score≥4) was observed in 23% (n=6,698) overall, as well as in 28% (n=2,601) and 21% (n=4,097) of those with and without metastases, respectively. Overall, physical concerns were most frequently reported (45%; n=12,963), followed by emotional (33%; n=9,551) and practical concerns (25%; n=7,248). Among patients with multiple screenings, improved distress at follow-up was observed among 17% (n=1,747) and 66% (n=1,989) of those with an initial DT score of <4 and ≥4, respectively.
CONCLUSIONS: In this community oncology population, approximately one in four patients reported elevated distress, underscoring psychosocial screening’s importance in clinical practice. Although utilization of the DT in the EHR was limited during this early phase of integration, patients with multiple screenings often reported improvements, especially those with elevated distress. Further investigation should examine how DT integration into an EHR may influence intermediate- and long-term patient outcomes.
When One Size Doesn’t Fit All: Incorporating the Child’s Perspective in Health Technology Assessment in North America
Session Type: Issue Panel
Topics: Patient-Centered Research, Health Technology Assessment, Economic Evaluation
Level: Introductory
ISSUE: There are methodological and normative issues associated with valuing health-related quality of life (HRQoL) in children and adolescents. The objective of this panel is to explore both the similarities and differences in how to approach child health valuation using the EQ-5D-Y in Canada and the USA, and the implications for health technology assessment. Attendees will gain understanding of the current state of measuring and valuing child health, which will be of interest to HEOR researchers, payers, and manufacturers. OVERVIEW: Dr Feng Xie will moderate the panel. He will provide the audience with a 15-minute overview of methodological and normative challenges in measuring and valuing child health. He will also highlight the unique North American perspective within the context of global research being conducted for the EQ-5D-Y. Dr Simon Pickard will present the program of research related to valuation of the EQ-5D-Y valuation study in the USA. The US study was the first to engage patient, clinical, and policy stakeholders and subsequently reengaged them after the study regarding decisions around source, framing, and modeling of preferences. Dr Brittany Humphries will follow by discussing the research program for the EQ-5D-Y valuation in Canada. This includes stakeholder engagement and the collection of both qualitative and quantitative data on eliciting preferences directly from children and adolescents. Dr Jesse Elliot will then discuss how these recent developments in the measurement and valuation of child health affect health technology assessment and what this means for incorporating the child’s perspective in reimbursement recommendations. At the end of the discussion, the audience will have 15 minutes to ask questions.
Moderator
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Feng Xie, PhD
McMaster University, Hamilton, ON, Canada
Speakers
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A Simon Pickard, PhD
University of Illinois, Chicago, Chicago, IL, United States
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Brittany Humphries, BA, MSc, PhD
McMaster University, Kanata, ON, Canada
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Jesse Elliott, PhD
CADTH, Ottawa, ON, Canada
Cost-Effectiveness Evaluation of Medical Therapies
Session Type: Research Podiums
This session highlights cost-effectiveness evaluations of a broad range of therapies for physcial and mental health conditions. Using trial-based economic evaluations and Markov models, these evaluations studied cognitive behavioral therapy after brain injury, pharmacological treatment for active lupus nephritis and transthyretin amyloid cardiomyopathy, and antipsychotic long-acting injectables.
Cost-Effectiveness Analysis of Second-Generation Antipsychotic Long-Acting Injectables in Patients with Schizophrenia in the United States
OBJECTIVES: Second-generation antipsychotic (SGA) long-acting injectables (LAIs) have shown promise in preventing relapses compared to traditional oral medications, largely due to improved medication adherence achieved through long-acting formulations. Our objective was to compare the cost-effectiveness of four intramuscular SGA LAIs (aripiprazole, aripiprazole lauroxil, olanzapine pamoate, and risperidone) to paliperidone palmitate in patients with schizophrenia from the US health care sector perspective.
METHODS: A Markov model with 90-day cycles was developed to simulate the progression of 40-year-old adults transitioning among stable treated, stable non-treated, and relapse health states, and death over 5 years at a discount rate of 3%. The base case utilized a 5-year time horizon due to uncertainty in long-term treatment changes, adherence, and schizophrenia progression. Patients transitioned to additional lines of therapy (another SGA LAI and then clozapine) when they experienced relapse or intolerance to side effects. Relapse transitional probabilities were estimated from an analysis using administrative claims. Other treatment related input parameters were derived from clinical trials and observational studies. Health state utilities and disutilities were obtained from published literature. Drug costs were estimated from Medicare Average Sales Price. All costs were standardized to 2024 US dollars. One-way and probabilistic sensitivity analyses were conducted.
RESULTS: Compared to paliperidone (3.20 quality-adjusted life-years [QALYs]), all other SGA LAIs had slightly lower to similar QALYs ranging from 3.04 to 3.21. Total health care sector costs were comparable across the SGA LAIs. Risperidone was dominant compared to paliperidone with similar QALYs but slightly lower costs. One-way sensitivity analyses resulted in utility inputs and drug costs being most influential to the model.
CONCLUSIONS: Our estimation of 5-year costs and outcomes demonstrated similar total costs and QALYs across the SGA LAIs. Further studies to refine model inputs are needed to better differentiate between the SGA LAIs and to validate our findings.
Trial-Based Economic Evaluation of the BrainACT Study: Acceptance and Commitment Therapy for Anxiety and/or Depressive Symptoms After Acquired Brain Injury in the Netherlands
OBJECTIVES: Following acquired brain injury (ABI), individuals often experience anxiety and/or depressive symptoms. BrainACT is an adapted form of Acceptance and Commitment Therapy (ACT) tailored to this target group. The current study is a trial-based health-economic evaluation comparing BrainACT to a psycho-education and relaxation control treatment.
METHODS: An economic evaluation from a societal perspective was conducted in the Netherlands alongside a multicenter randomized controlled two-armed parallel trial including seventy-two participants. A cost-utility and cost-effectiveness analysis was conducted where incremental costs, quality-adjusted life-years (QALY), and anxiety/depression (HADS score - Hospital Anxiety and Depression Scale), were collected and presented over a 1-year follow-up period. Bootstrapping, scenario, and subgroup analyses were performed to test the robustness of the results.
RESULTS: The BrainACT arm reported non-significant lower total costs (incremental difference of €-4,881; bootstrap interval €-12,139 to €2,330) combined with significantly decreased anxiety/depression (HADS) (3.2; bootstrap intervals 0.7 to 5.7). However, total QALYs were non-significantly lower (-0.008; bootstrap interval -0.060 to 0.042) for BrainACT. The probability of the intervention being cost-effective was 86 percent at a willingness-to-accept threshold of €50,000/QALY. The scenario and subgroup analyses confirmed the robustness of the results.
CONCLUSIONS: BrainACT may be a more cost-effective alternative to a psycho-education & relaxation intervention for anxiety and/or depressive symptoms following ABI. Despite limitations, BrainACT appears to be a promising addition to treatment options in the Netherlands. Further research is needed to validate these findings, and consideration should be given to implementing BrainACT in Dutch clinical settings with ongoing monitoring.
Cost-Effectiveness of Transthyretin Stabilizing Agents for the Treatment of Transthyretin Amyloid Cardiomyopathy (ATTR-CM)
OBJECTIVES: Tafamidis and acoramidis are transthyretin stabilizing agents (TTR-SA) indicated for transthyretin amyloid cardiomyopathy (ATTR-CM). We assessed the cost-effectiveness of TTR-SAs added to supportive care (SC) compared to SC alone in managing ATTR-CM from the US healthcare-sector perspective.
METHODS: Based on New York Heart Association (NYHA) Functional Classes I-IV, a Markov model simulated ATTR-CM disease progression with and without TTR-SAs over a lifetime horizon with 6-month cycles and 3% discount rate for health outcomes and costs. Cardiovascular-related hospitalizations were incorporated as transient events. Transition probabilities were sourced from a French Health Technology assessment of tafamidis. Mortality was modeled using US lifetables, published NYHA class-specific mortality hazards, and clinical trial survival. The annual medication cost was $163,000, estimated by discounting the acoramidis wholesale acquisition price by 27.5%. Outcomes were total life years (LYs), quality-adjusted life years (QALYs), equal value life years (evLYs), costs, and years in NYHA Class I/II. Sensitivity and scenario analyses were conducted.
RESULTS: Compared to SC alone, TTR-SAs plus SC had an incremental total cost of $663,000, an additional 1.4 LYs, 0.9 QALYs, 1.2 evLYs, and 0.9 years in NYHA Class I/II. Incremental cost-effectiveness ratios (ICERs) were $740,000 per QALY gained, $479,000 per LY gained, $532,000 per evLY gained, and $635,000 per additional year in NYHA Class I/II. At the non-discounted $225,000 annual drug price, an 88.8% discount would be required to achieve an ICER of $150,000 per QALY gained. Results were sensitive to NYHA-state utility, mortality hazards, cohort age, hospitalization costs, and NYHA Class IV hospitalization disutility inputs. In all probabilistic sensitivity analyses iterations, TTR-SAs were not cost-effective at common thresholds ($50,000-$200,000 per QALY).
CONCLUSIONS: Treatment with TTR-SAs plus SC led to improved health outcomes at higher costs compared to SC alone. At the assumed price, TTR-SAs would require a substantial discount to achieve commonly used cost-effectiveness thresholds in the US.
Cost-Effectiveness of Belimumab for the Treatment of Adults With Active Lupus Nephritis in Canada
OBJECTIVES: To evaluate the costs and health outcomes of belimumab plus standard therapy (ST) versus ST alone for the treatment of adults with active lupus nephritis (LN) in Canada from a healthcare payer perspective.
METHODS: A cohort-level Markov model was developed with health states classified by estimated glomerular filtration rate (eGFR; mL/min/1.73 m2) and dialysis/renal transplant status. Population characteristics and treatment effects were based on the BLISS-LN trial. Transition probabilities were informed by published sources. Long-term renal function was based on eGFR slope during BLISS-LN. ST comprised intravenous cyclophosphamide induction followed by azathioprine maintenance (CYC→AZA) or mycophenolate mofetil (MMF) alone. Cost (2021/2022 $CAD) and health outcomes were discounted at 1.5%. One-way sensitivity and scenario analyses were performed to evaluate robustness of results. The base-case analysis was probabilistic. Pairwise comparisons were performed for belimumab plus CYC→AZA versus CYC→AZA and belimumab plus MMF versus MMF alone.
RESULTS: Belimumab plus CYC→AZA and belimumab plus MMF were more costly and more effective than CYC→AZA and MMF alone, with mean incremental cost-utility ratios (ICURs) of $515,277 and $345,269, respectively. Patients receiving belimumab incurred lower disease management costs (versus CYC→AZA: -$57,909; versus MMF: -$84,151), mainly due to a reduction in hospitalizations and dialysis/renal transplants, and lower flare management (versus CYC→AZA: -$2,554; versus MMF: -$2,658). Overall, belimumab was associated with increased quality-adjusted life years (QALYs) (versus CYC→AZA: 0.41; versus MMF: 0.57) due to reduction in disease progression (versus CYC→AZA: +0.28; versus MMF: +0.47), reduced flares (versus CYC→AZA: +0.08; versus MMF: +0.08), and steroid sparing (versus CYC→AZA: +0.06; versus MMF: +0.02).
CONCLUSIONS: Although belimumab’s cost-effectiveness results did not align with conventional willingness-to-pay thresholds in Canada, belimumab was associated with a reduction in disease management due to slower disease progression, steroid sparing, and reduced disease flares.
FUNDING: GSK (GSK Study 218218). Editorial support (GSK-funded): Fishawack Indicia Ltd., UK, part of Avalere Health.
Identifying Gaps and Establishing a Development Plan for Consensus Real-World Data Standards
Session Type: Workshop
Topics: Real World Data & Information Systems, Organizational Practices
Level: Intermediate
PURPOSE: Standards provide technical specifications which are voluntarily used to demonstrate that products, services, or processes meet a certain level of quality, safety, and/or reliability. While international standards organizations exist (e.g., European Committee for Standardization, US National Institute of Standards and Technology), standards are often developed by stakeholders who need to utilize them.Within HEOR, studies using real-world data (RWD) such as healthcare claims, electronic health records (EHR), registries, device-derived data, or other patient-generated data may be subject to healthcare interoperability standards, regulatory or payer study data submissions standards, as well as standards for data semantics, syntax, transport, security, and services. Development of validated algorithms in claims/EHR, performance measures using wearables, and prediction using artificial intelligence/machine learning (AI/ML) provide examples with nuanced considerations. While the needs may change based on the overarching purpose of the study, a basic set of consensus standards for all RWD used for HEOR is imperative to establish the viability, credibility, and acceptance of these data for increased use in healthcare research and decision making. DESCRIPTION: This panel will introduce types of data standards used across fields and highlight those already available for RWD. The discussion leaders will introduce known gaps in the data standards for RWD and solicit additional information about gaps from the audience. Through polling, participants will identify and prioritize the most pressing needs for developing consensus data standards for RWD. Three examples (claims/EHR, wearables, AI/ML) will be used to illustrate key nuances to consider for standards development. Group brainstorming of potential tactics, stakeholders to engage, and decision-makers to consider will be followed by solicitation of interest in participating in RWD standards development.
Moderator
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Mitch Higashi, PhD
ISPOR, Villanova, PA, United States
Speakers
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Mary Beth Ritchey, MSPH, PhD
CERobs Consulting, LLC, Philadelphia, PA, United States
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Eberechukwu Onukwugha, MSc, PhD
University of Maryland, School of Pharmacy, Baltimore, MD, United States
Eberechukwu Onukwugha, PhD is a Professor in the Department of Practice, Sciences, and Health Outcomes Research and Executive Director of Pharmaceutical Research Computing at the University of Maryland School of Pharmacy. She received a Doctor of Philosophy in economics (concentration: econometrics) from Virginia Polytechnic Institute and State University (Virginia Tech). Dr. Onukwugha completed a two-year postdoctoral fellowship in pharmacoeconomics and health outcomes research at the University of Maryland School of Pharmacy. She was a recipient of the PhRMA Foundation’s Post-Doctoral Fellowship in health economics and outcomes research. Dr. Onukwugha’s research interests are in cost analysis, health disparities, and medical decision-making by individuals and institutions. She has approximately 20 years of experience conducting health economics and outcomes research using administrative medical and pharmacy claims, hospital discharge, and prospectively-collected data. Dr. Onukwugha has authored or co-authored over 140 peer-reviewed articles in health economics and outcomes research. She is an Editorial Board member for PharmacoEconomics and an Associate Editor for Ethnicity & Disease. Dr. Onukwugha serves as President, ISPOR Board of Directors, 2024-2025, and serves on the Maryland Prescription Drug Affordability Board.
Best Research Practice: Does the Practice of Implementation Sciences Have a Place in Industry-Sponsored Research?
Session Type: Workshop
Topics: Study Approaches, Health Service Delivery & Process of Care, Organizational Practices
Level: Introductory
PURPOSE: The adoption and integration of new medicines and treatment regimens within healthcare delivery can take more than a decade. This workshop will focus on the use of implementation science (IS) research to bridge this gap between the availability of new therapeutics and use in routine clinical practice. Participants will understand the importance of IS to accelerate the application in industry-sponsored research and improve the use of research evidence and new treatment options in routine care. DESCRIPTION: In this foundational session, workshop attendees will be introduced to IS: 1) specific definitions and concepts; 2) theories, models, and frameworks (TMFs); and 3) applications through case study. Dr. Rodriguez-Leboeuf will chair the session and introduce the core principles of IS, including new guidance for the use of IS principles for regulatory decision-making (European Medicines Agency) (10 min). Dr Gaglio will emphasize the importance of adequate TMFs underpinning research and will describe key TMFs that can help organize and understand context as well as why and how an intervention succeeded or failed (15 min). Ms Zahid will highlight the use and benefits brought by IS to gaps in implementing industry relevant research evidence into routine care using a case study as a supportive example. Factors influencing implementation success and tailoring of effective interventions to different settings will be discussed (15 min). In the practical session, the audience will have the opportunity to analyze a hypothetical case study and engage in critical thinking while applying their newly acquired knowledge for the successful implementation of new treatment options or other research evidence for improved care.
Moderator
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Ana Maria Rodriguez-Leboeuf, BSc, MSc, PhD
IQVIA, Madrid, Spain
Speakers
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Ana Maria Rodriguez-Leboeuf, BSc, MSc, PhD
IQVIA, Madrid, Spain
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Mahrukh Zahid, PhD
Novartis, on behalf of Consortium on Implementation Science (CIS) Models, Methods & Measures in Drug, Basel, Switzerland
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Bridget Gaglio, MPH, PhD
Evidera, Wilmington, NC, United States
Integrating Financial Risk Protection Into Economic Evaluation and Policy Decision-Making: What, Why, and How?
Session Type: Workshop
Topics: Economic Evaluation, Patient-Centered Research, Health Policy & Regulatory
Level: Intermediate
PURPOSE: Policymakers aim to achieve health system objectives that not only improve health outcomes but also protect individuals and families from financial risks associated with illness, including out-of-pocket health costs and non-health-related expenses. There is growing recognition of the importance of incorporating financial risk outcomes into economic evaluations, making them a critical criterion for selecting priority interventions and informing insurance coverage decisions. This workshop will explore two key questions: What are appropriate measures of financial risk? And how can financial risk protection (FRP) be integrated into economic evaluation frameworks to guide coverage decisions? DESCRIPTION: Verguet will open the workshop with an overview of the importance of FRP in priority setting, current methods for measuring FRP, and key questions for advancing research (12 minutes). Khor will present on the financial toxicity of therapeutic innovations in oncology (12 minutes). By linking cancer registry data with financial credit records, she will explore whether rapid introduction of new treatments exacerbated trade-offs between survival and financial burden. Lavelle will focus on the financial burdens associated with productivity losses experienced by patients and caregivers (12 minutes). She will discuss methods for capturing these burdens in economic evaluations and examine the broader implications for families and society. Jiao will introduce a framework for integrating the value of health insurance in mitigating financial risks into cost-effectiveness analysis (12 minutes). The session will include interactive real-time polling, where participants will respond to questions based on specific case studies that illustrate approaches to incorporating financial risks and their implications. The polling results will guide an interactive discussion on the role of financial risks in economic evaluations and their impact on coverage policy decisions (12 minutes).
Moderator
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Stéphane Verguet, PhD
Harvard T.H. Chan School of Public Health, Boston, MA, United States
Speakers
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Sara Khor, PhD
University of Washington, Stanford, CA, United States
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Tara Lavelle, PhD
Tufts Medical Center, Boston, MA, United States
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Boshen Jiao, MPH, PhD
University of Southern California, Los Angeles, CA, United States
To What Extent Will the Inflation Reduction Act (IRA) Impact Innovation and Access to Rare Disease Treatments—Did the IRA Temporarily Spook Industry or Will It Have a Permanent Influence?
Session Type: Issue Panel
Topics: Health Policy & Regulatory, Patient-Centered Research, Organizational Practices
Level: Intermediate
ISSUE: The introduction of the IRA concerns rare disease stakeholders as the only exemption from Medicare negotiations applies to orphan drugs with a single approved indication. Many medicines launched in rare conditions are eventually approved in multiple indications, ultimately allowing for a greater financial return on investment. Following the IRA’s 2022 rollout, there was a knee-jerk reaction by rare disease stakeholders, including Eli Lilly and Alnylam Pharmaceuticals which suspended clinical programs in rare diseases. The National Organization for Rare Disorders subsequently declared in an open 2023 letter to the CMS that the IRA could inadvertently reduce investment, and subsequently access, to rare disease therapies. Three years after the IRA’s introduction, this issue panel will address to what extent these concerns will impact investment, access, and pricing in rare diseases. Has the rare diseases community seen further signs of reduced investment that will result in access to fewer therapies? Or where these concerns an ‘overreaction’ with the IRA now expected to have a smaller impact on innovation and access than what was initially anticipated? OVERVIEW: Kate will provide a 10-minute overview highlighting the IRA’s influence on orphan drugs and concerns from the rare diseases community. Richard will share real-life examples demonstrating how the IRA is leading to reduced investment in orphan drugs, and its anticipated impact on pricing and patient access to new therapies. Sara will highlight Chiesi’s global rare disease’s commitment to their rare diseases pipeline and drugs, including the current impact of the IRA on US access and Chiesi’s investment in R&D. John O’Brien will discuss the IRA’s intended benefits for ensuring greater affordability, along with how CMS could mitigate any of the unintended consequences the IRA will have on innovation and access for rare disease treatments. There will be interactive polling and a 20-minute Q&A session with the audience.
Moderator
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Kate Hanman, MSc
Costello Medical, Cambridge, United Kingdom
Speakers
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Richard Xie, PhD
RA Capital Management, Newton, MA, United States
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Sara Hovland, MBA, MS, PharmD
Chiesi, St Louis Park, MN, United States
Sara is currently the Lead, US HEOR, Global Rare Disease at Chiesi. Sara has nearly 2 decades of experience in the US Healthcare system spanning from practicing as a pharmacist, Pharmacy Benefit Management work, field-facing and in-house US/Global HEOR work.
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John O'Brien, MPH, PharmD
National Pharmaceutical Council, Washington, DC, United States
2:45 PM - 3:15 PM
Thursday Afternoon Coffee and Connect (Exhibit Hall)
Session Type: General Meeting
Head to the exhibit hall to refuel, recharge and connect with fellow attendees and exhibitors over a steaming cup of coffee. Provided by ISPOR.
3:00 PM - 3:30 PM
Gen AI Powered Evidence Generation: Implementing Advanced RAG Architecture for Sensitive Data in HEOR Applications
Session Type: Exhibit Hall Theaters
Topics: Methodological & Statistical Research
Level: Introductory
3:15 PM - 4:15 PM
Qualitative Research in Rare Disease Populations: Optimizing Data Collection for Different Stakeholders Including Patients, Caregivers, Regulators, and HTA Agencies
Session Type: Forums
Topics: Patient-Centered Research, Methodological & Statistical Research
Level: Introductory
Qualitative research enables the in-depth exploration of the patient or caregiver experience of living with a disease. This is particularly valuable in rare diseases, where little is known about the burden of disease and impact on individuals and caregivers. However, conducting such research can be challenging, due to the small number of potential participants and competing demands on the time of individuals and caregivers.
This forum will discuss the value of qualitative research in rare disease, along with solutions for overcoming challenges with recruitment, and strategies for optimizing data collection for multiple stakeholders, including patients and caregivers, regulators, and health technology assessment (HTA) agencies.
Sarah Acaster (moderator) will start by introducing the topic and highlighting the value of qualitative research in rare disease populations, and why it is important to optimize data collection for different stakeholders.
Paige Nues will provide a patient advocate perspective, describing her experience as a caregiver to a daughter with Rett syndrome, and discussing the value of qualitative research to patients and caregivers.
Asia Sikora Kessler will provide an industry perspective, with examples of different qualitative research designs, including standalone and in-trial qualitative interviews. She will highlight how each can provide unique ways of generating data for regulators, as well as solutions of overcoming barriers to implementation.
Kate Williams will present results from a novel multi-country qualitative study in aromatic L-amino acid decarboxylase (AADC) deficiency, where qualitative data was optimized for multiple audiences, including to describe the experience of living in different health states associated with an economic model, to support an HTA submission.
The session will conclude with a Q&A and a discussion with the audience on their experiences in conducting qualitative research in rare diseases.
Moderator
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Sarah Acaster, MSc
Acaster Lloyd, London, United Kingdom
Speakers
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Paige Nues
International Rett Syndrome Foundation, Cincinnati, OH, United States
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Asia Sikora Kessler, PhD
Ionis, Carlsbad, CA, United States
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Kate W Williams, BSc, MSc, PhD
Acaster Lloyd Consulting, London, United Kingdom
Kate is a director of patient-centred outcomes research at Acaster Lloyd Consulting Ltd. She has over 15 years’ experience in patient-centred research in academia, consulting and the pharmaceutical industry. Her main research interests are in the design and conduct of qualitative and mixed methods research studies to capture the patient voice. She also has expertise in the development of clinical outcome assessment (COA) strategies for clinical studies. She has experience across a range of therapeutic areas, with a particular interest and expertise in rare diseases and neurological conditions. Kate holds a PhD in Psychology from University College London. She has more than 30 peer-reviewed publications and has presented at multiple conferences. Kate is currently Associate Editor at the Journal of Patient-Reported Outcomes and is Chair-Elect of the ISPOR Clinical Outcome Assessment Special Interest Group.
The Evolution of Patient-Reported Outcome (PRO) Collection in Oncology: Will the Need for Multistakeholder Alignment Prevent Improved Patient-Centered Care?
Session Type: Forums
Topics: Patient-Centered Research
Level: Introductory
Despite the considerable effort to improve patient centricity in oncology, effective scientific evaluation of the treatment experience through patient-reported outcomes (PROs) continues to be challenging given the differential implementation needs across multiple stakeholders (e.g., patients, physicians, industry, HTA bodies). While there is significant interest in improving PRO measurements given the clear benefit to patient care, efforts do not include the multistakeholder perspective and the optimal path forward remains unclear. PRO measures (PROMs) have become a fundamental component of clinical oncology. Well-established historical PROMs are included in clinical studies for regulatory evaluation and market access; however, they may not fully capture the patient experience and inclusion of several PROMs may impact compliance. While PROMs are being incorporated into clinical practice to increase patient centricity, the optimal instruments from a health-system perspective may increase physician burden without allowing accurate characterization of the patient experience. Patients are also looking to PROMs to improve their care journey in real-time but are highlighting the need to evolve past historical measures to novel PROMs, which may not be fully validated from a methodological standpoint. Accordingly, the evolution of PROMs is currently limited by differing value perspectives of key stakeholders, which will need to be resolved to advance patient-centric care.
Dr. Kristi Bertzos will spend 10 minutes presenting the industry perspective on inclusion of PROMs in clinical studies. Abeer Al-Rabayah will spend 10 minutes discussing the incorporation of PROs in clinical practice in the Middle East and North Africa. Eva Villalba will spend 10 minutes on the patient perspective of how to better capture PROs. Presentations will be followed by discussion and audience engagement.
Moderator
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Brittany Carson, BSc, PhD
ApotheCom, New York, NY, United States
Speakers
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Abeer A Al Rabayah, MBA, MSc
King Hussein Cancer Center, Amman, Jordan
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Kristi Bertzos
Johnson and Johnson, Harelysville, PA, United States
Kristi has over 20 years of experience in various roles in the pharmaceutical industry supporting the selection and implementation of clinical outcome assessments (COAs) in drug development programs. For nearly 15 years she worked at a leading contract research organization, where she provided expert consultancy to sponsors on COA selection, translation, and implementation, and trained clinicians to administer COAs. She has been with Johnson and Johnson since 2021 and is a Director on the Patient-Reported Outcomes (PRO) team. She is currently responsible for shaping PRO strategies for the bladder cancer portfolio. Throughout her career she has been active in publishing rigorous and compelling data with over 50 manuscripts, book chapters, and oral and poster presentations.
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Eva Villalba
Quebec Cancer Coalition, Montreal, QC, Canada
Clinical Trial Design, Beyond the Regulatory
Session Type: Forums
Topics: Health Technology Assessment, Study Approaches, Patient-Centered Research
Level: Introductory
After regulatory approval, clinical trials serve several important purposes, such as demonstrating the value of the medicine to payers, reimbursement agencies, healthcare professionals, and other stakeholders. Patient-generated data, including for example, patient-reported outcomes (PROs) are vital, offering insights directly from patients about their disease and treatment experiences, and the impact of these on their health-related quality of life. Clinical trials provide essential data for economic models required by many reimbursement agencies. Ensuring trials can be used for comparative effectiveness research—comparing new treatments with the existing standard of care—is crucial at the design stage. While statistical methods are advancing, they cannot always overcome challenges posed by trials not designed for this purpose.
A broad range of topics will be considered in relation to clinical trial design, including anticipated stakeholder needs and planning for future value message generation, exploring the patient perspective, and considering future inputs for economic evaluations such as utility estimates and comparative efficacy estimates. Additionally, the need for single-arm trials and approaches to select and generate external control arms will be discussed.
Kati Copley-Merriman will moderate the session, providing insights into trial design with a focus on value message generation, the importance of considering current available evidence, and creating an evidence strategy. Lynda Doward will emphasize the need for patient-centered trial design and data collection, ensuring trials include study endpoints that address key areas of disease and treatment impact from the patient perspective while being less burdensome. Emma Hawe will discuss considerations for ensuring the future feasibility of analyses to generate inputs for cost-effectiveness models, with a focus on relative efficacy estimates, and utility estimates by health state. Shannon Cope will discuss and offer practical considerations based on past submissions of ECAs for reimbursement.
Moderator
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Kati Copley-Merriman
RTI Health Solutions, Ann Arbor, MI, United States
Speakers
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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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Emma Hawe
RTI Health Solutions, Manchester, United Kingdom
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Shannon Cope, MSc
PRECISIONheor, Vancouver, BC, Canada
4:00 PM - 4:45 PM
Real-World Evidence Poster Tour
Session Type: Research Posters
This tour will take place during Poster Session 4, Posters will be hung from 4:00 - 7:00 PM.
Posters featured in this tour:
PT37: Operationalizing an Outcomes-Based Market Access Agreement Using Real-World Data From the Canadian Neuromuscular Disease Registry
PT38: Assessing the Impact of Digital Ecosystem Engagement on Outcomes in Sickle Cell Disease (SCD) Patients
PT39: Best Practices and Standards to Enhance the Quality of Rare Disease Registries in Canada
PT40: Insurance Type, Income Level, and Cost-Related Disparities Influencing Medication Adherence in a United States Metropolitan Patient Population
PT41: Structured Evaluation of Oncology Real-World Data Quality for Practical Applications
PT42: Designing Value-Based Dental Insurance: A Multicriteria Decision Analysis
EQ-5D Developments Poster Tour
Session Type: Research Posters
This tour will take place during Poster Session 4, posters will be hung from 4:00 - 7:00 PM.
Posters featured in this tour:
PT31: Psychometric Testing of the ICECAP-A in Patients With Coeliac Disease: A Comparative Analysis With EQ-5D-5L
PT32: Mapping the EQ-5D-5L and SF-6Dv2 From FACT-G in Cancer Patients
PT33: Reliability and Validity of EuroQol-5 Dimensions-5 Levels in Patients With Hematologic Malignancies: A Cross-sectional Study
PT34: Response Performance of General Chinese Children Aged 6-11 to EQ-5D-Y-3L: A Multicenter Study
PT35: The Measurement Properties of Self and Proxy-Completed EQ-5D-Y-3L, EQ-5D-Y-5L, and Four Bolt-on Items in ADHD
PT36: Is There Psychometric Evidence to Support the Use of the EQ-5D in Long COVID? A Systematic Review
4:00 PM - 7:00 PM
Poster Session 4
Session Type: Research Posters
5:00 PM - 6:00 PM
Implementation of Performance Outcome (PerfO) Assessments in Clinical Trials: Final Recommendations From the ISPOR PerfO Task Force
Session Type: Workshop
Topics: Clinical Outcomes, Patient-Centered Research, Health Policy & Regulatory
Level: Intermediate
PURPOSE: As task-based measures, PerfO assessments pose unique implementation challenges that impact study design, data collection, and data management compared to other clinical outcome assessments (COAs). Task force members will present their good practice recommendations for ensuring high-quality data generation along with the types of evidence needed to evaluate the appropriateness of a PerfO assessment in a specific context of use. DESCRIPTION: Ideally, PerfO assessments are used when the optimal means of capturing clinical benefit is through the completion of defined tasks involving physical, cognitive, and/or sensory function that reflect activities that are meaningful in daily life. The importance of standardization and the unique data collection considerations inherent in many PerfO assessments (eg, space requirements, specialized equipment) increase the complexity of implementation in clinical trials, impacting trial design. Participants will be invited to complete a small portion of both a cognitive and physical function PerfO assessment. Verbal fluency tasks, widely used in Alzheimer’s and dementia trials, are used to measure word finding difficulties and aspects of executive function; the TUG assessment is used to evaluate balance and ability to perform everyday movements. Via demonstration and completion of these exercises, the complexities related to task administration, standardization, administrator training, conduct, and scoring of assessments will be illustrated.Speakers will discuss and demonstrate through practical exercises, their recommendations on: 1) areas where PerfO assessments pose unique implementation challenges; 2) standardization and potential threats to a measure’s validity and interpretation; 3) the role of digital health technologies (DHTs) in PerfO assessments; and 4) the regulatory perspective and their expectations regarding clinical trial design and evidence that a PerfO assessment is fit-for-purpose. Audience Q&A will follow.
Moderator
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Elizabeth (Nicki) Bush, MS
OPEN Health, Zionsville, IN, United States
Speakers
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Bill Byrom, PhD
Signant Health, Nottingham, United Kingdom
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Sonya Eremenco, MA
Critical Path Institute, Tucson, AZ, United States
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Michelle Campbell, PhD
US Food and Drug Administration, Silver Spring, MD, United States
Pharmaceutical Policy Provisions of the Inflation Reduction Act: Beyond Drug Negotiation
Session Type: Issue Panel
Topics: Health Policy & Regulatory, Health Service Delivery & Process of Care, Real World Data & Information Systems
Level: Intermediate
ISSUE: Benefits, limitations, and implementation challenges of the pharmaceutical provisions of the Inflation Reduction Act implemented in 2025.
OVERVIEW: The Inflation Reduction Act introduced important reforms to the Medicare Part D benefit beyond the well-known negotiation of drug prices. These include 1) the redesign of the Part D benefit, including a $2,000 out-of-pocket cap; 2) the ability to “smooth out” beneficiary payments throughout the calendar year; 3) the introduction of a $35 copayment cap for insulin products. While these reforms were well-intended to improve drug access, some may have unintended consequences or face implementation challenges. For instance, Part D redesign may result in the replacement of fixed copayments with co-insurance (%) for branded drugs. Medicare Part D beneficiaries may not be aware of the ability to smooth out-of-pocket payments during the year, which will preclude their enrollment. Finally, copayment caps may not make a difference for the large share of beneficiaries already paying amounts below the proposed caps. The panelists will present timely data on the impact of these provisions, supporting a balanced debate of the limitations and benefits of these reforms.
Dr. Anderson (10-12 min) will discuss the implementation of insulin copayment caps and their impact on beneficiary out-of-pocket spending. Dr. Patterson (10-12 min) report changes in formulary design in 2025 by the leading Part D sponsors. Dr. Sepassi (10-12 min) will present projections for Medicare Part D beneficiaries benefiting from the $2000 out-of-pocket cap and the ability to smooth payments throughout the year. Dr. Hernandez will provide remarks on the interactions of these provisions (6-8min) and open the floor for questions (20 min). The moderator will seek inclusion of the panel on the Women in HEOR ISPOR list of events, as it features the novel and impactful research of women in the field.
Moderator
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Inma Hernandez, PhD
UCSD, La Jolla, CA, United States
Inmaculada (Inma) Hernandez is a pharmaceutical health services researcher and a Professor with tenure at the University of California, San Diego. She has authored more than 140 scientific articles. Her research has focused on the study of medications for stroke prevention and the examination of drivers of drug prices. She has made major contributions to improving transparency in the drug pricing and reimbursement system. She currently serves as the National Academy of Medicine Fellow in Pharmacy.
Speakers
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Kelly Anderson, MPP, PhD
University of Colorado Anschutz Medical Campus, Aurora, CO, United States
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Aryana Sepassi, PharmD
University of California, Irvine, School of Pharmacy & Pharmaceutical Sciences, Carlsbad, CA, United States
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Julie Patterson, PharmD, PhD
National Pharmaceutical Council, Richmond, VA, United States
Emerging Innovations in Health Services: Can Value Assessment Unlock Their Potential?
Session Type: Issue Panel
Topics: Health Service Delivery & Process of Care, Economic Evaluation, Health Technology Assessment
Level: Intermediate
ISSUE: Innovation in health services, driven by advancements in technology and care models, is accelerating alongside pharmaceutical innovation. Notable examples include the integration of artificial intelligence into clinical decision-making and the early incorporation of palliative care into cancer treatment pathways, both of which hold significant potential to enhance population well-being. However, these advancements present challenges to the healthcare ecosystem, particularly in developing reimbursement models that encourage the adoption of high-value innovations while deterring low-value services. The ongoing shift from fee-for-service to value-based reimbursement in the United States offers a key opportunity to align payments with value. Robust value assessment serves as the foundation for these models but faces significant hurdles, including unclear definitions of "value" and limited effectiveness and cost data. This panel will discuss and debate the benefits and challenges of applying value assessment to health services innovation, providing actionable insights to inform reimbursement strategies. OVERVIEW: The session will begin with the moderator providing an overview of the current state of innovation in health services and perspectives on value assessment (5 minutes). Brett McQueen will address challenges in measuring the effectiveness and costs of health service interventions, proposing solutions to prioritize patient-centered outcomes and improve evidence generation (13 minutes). Nathaniel Hendrix will explore the challenges of performing economic evaluation on artificial intelligence-based clinical decision support (13 minutes). Xin Hu will present a case study on the value assessment of an early palliative care model for advanced-stage cancer, highlighting challenges in adoption, the role of value-based models, and the quantification of critical value elements (13 minutes). The panel will feature interactive real-time polling to engage participants and conclude with an audience discussion.
Moderator
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Boshen Jiao, MPH, PhD
University of Southern California, Los Angeles, CA, United States
Speakers
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William V Padula, PhD
University of Southern California, Los Angeles, CA, United States
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Nathaniel Hendrix, PhD
American Board of Family Medicine, Washington, DC, United States
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Xin Hu
Emory University, Atlanta, GA, United States
Frontiers in Survival Analysis for Health Technology Assessment
Session Type: Research Podiums
This session explores advanced methods for survival analysis in health technology assessment and comparative effectiveness research. Presentations will cover incorporation of external opinion in survival extrapolations, transportability of population-adjusted treatment effects, reconstruction of individual patient data from Kaplan-Meier curves, and application of patient-level surrogacy models.
IPDvariate: Reconstructing Patient Characteristics and Survival Data from Kaplan-Meier Curves for Subgroup Analysis
OBJECTIVES: In economic evaluations, obtaining subgroup survival data from clinical trials is sometimes necessary to conduct subgroup analyses. To address this need, we propose a workflow to reconstruct unreported subgroup survival data from published Kaplan-Meier (KM) survival curves and forest plots.
METHODS: We developed IPDvariate, an R package that uses Monte Carlo simulation and optimization techniques to model the relationship between patient characteristics and survival outcomes. We reconstruct subgroup-specific KM survival curves by incorporating information from forest plots as constraints. The accuracy of IPDvariate in reconstructing subgroup KM survival curves was assessed by comparing the reconstructed curves with the original survival data from published datasets. Multiple simulation repetitions were conducted to evaluate the reproducibility and error bounds of the IPDvariate results.
RESULTS: When comparing the reconstructed Progression-Free Survival (PFS) KM curve for the PD-L1 subgroup from the KEYNOTE-859 trial with the published PFS KM survival curve, the curves were visually very similar. In the published data, the median PFS for the intervention group was 6.9 months (6.0-7.2), and for the comparator, it was 5.6 months (5.4-5.7), with a hazard ratio (HR) of 0.72 (0.64-0.82). After reconstruction with IPDvariate, the median PFS for the intervention group was 6.95 months (6.42-7.45), and for the comparator, it was 5.57 months (5.49-5.79), with an HR of 0.725 (0.644-0.817), showing minimal error.
CONCLUSIONS: IPDvariate demonstrates the potential for reconstructing unreported subgroup survival data, providing a valuable tool for economic evaluations without original subgroup data.
Transportability of Treatment Effect Measures for Binary Outcomes in Population-Adjusted Indirect Comparisons
OBJECTIVES: Population-adjusted indirect comparisons (PAICs) of binary outcomes are typically quantified in terms of odds ratios (ORs). While conditional log ORs (LORs) are independent of baseline risk and population (hence, transportable) under certain conditions in PAICs, marginal LORs vary by population. In some cases, relative risks (RRs) or risk differences (RDs) may be needed to address the research question. We examine the transportability of population-average conditional and marginal log RRs (LRRs) and RDs in PAICs using a simulated example.
METHODS: We specified a logistic model characterizing the relative effects of treatments from an index study comparing treatment B vs. A and a comparator study comparing C vs. A, corresponding to the type of model commonly fitted in ML-NMR. Each study population was defined by X, a uniformly distributed covariate that is both prognostic and effect modifying (shared effect for B and C). The population-average conditional and marginal effects were estimated for B vs. C in the index population where X has a Uniform(-1,1) distribution, and the comparator’s where X is Uniform(-1.5,0.5).
RESULTS: The conditional LOR for B vs. C was 1 in both populations, but the marginal LOR decreased from 0.725 to 0.526 in the comparator population. Both the conditional (0.876 vs. 0.677) and marginal LRRs (0.636 vs. 0.357) differed in the index and comparator populations. Similarly, the conditional and marginal RDs differed across populations and increased from 0.078 to 0.114 in the comparator population.
CONCLUSIONS: In PAICs of binary outcomes based on logistic models, the conditional LOR is the only effect measure independent of covariate distributions, making it transportable. Marginal LORs and LRRs and RDs vary by population and, therefore, are not transportable. Thus, when these effects are derived in MAICs or STCs, they are only applicable in the comparator population. ML-NMR is preferable as it can compute relative effects in any population.
Predicting Overall Survival (OS) from Time to Recurrence (TTR) Using a Copula-Based Patient-Level Surrogacy Model with Parametric Marginal Survival Distributions: Application to Adjuvant Treatment of Patients with Colon Cancer
OBJECTIVES: Cost-effectiveness analyses for health technology assessment require OS predictions over a lifetime horizon. When OS data are unavailable and trial-level surrogate relationships cannot be established, individual-level surrogacy relationships can be used. The study objective is to evaluate an individual-level surrogacy model versus a single hazard ratio (HR) approach to predict OS based on TTR in patients with colon cancer in the adjuvant setting.
METHODS: We used individual patient data from a three-arm randomized controlled trial investigating levamisole (L), L+fluoroacil (F) and observation (OBS) for stage III colon cancer (929 patients; median follow-up, 6.5 years). OS was assumed known for OBS, and unknown for L and L+F. Patient-level TTR-OS surrogacy was evaluated using the joint frailty-copula model following Wu-2020; baseline hazard functions were estimated using sex- and age-adjusted Weibull distributions. Patient-specific OS was simulated using the covariate-adjusted failure function, conditional on recurrence status, described by Berardi-2024. Individuals were censored when <5% of sample was at risk of events, reducing reliance on event-free tails. Simulations were performed assuming pre-recurrence death events were either known or unknown. The HR approach predicted L/L+F OS based on TTR and the TTR-OS HR estimated in the OBS arm. Performance was compared using area between simulated and observed OS (Δ OS).
RESULTS: TTR was associated with OS (Kendall’s tau: 0.67; 95%CI: 0.58-0.74). OS was predicted best by the surrogacy model with known pre-recurrence deaths (ΔOS-OBS: 1.42%, ΔOS-L: 2.61%, ΔOS-L+F: 2.69%) and unknown ones (ΔOS-OBS: 3.77%, ΔOS-L: 3.48%, ΔOS-L+F: 6.37%). The HR approach resulted in substantially greater differences (ΔOS-OBS: 9.25%, ΔOS-L: 8.09%, ΔOS-L+F: 7.08%). The individual-level surrogacy approach was able to capture the non-proportionality in hazards between OS and TTR, whereas the HR method could not.
CONCLUSIONS: In the adjuvant setting, where non-proportional hazards between time-to-event outcomes are likely, the predictive individual-level surrogacy may offer a credible methodology to predict OS.
Incorporating External Opinion in Survival Extrapolations to Inform Long-Term Survival Projections for Health Technology Assessment
OBJECTIVES: Accurate long-term survival estimation is critical for health technology assessments (HTA), yet many trials lack sufficient follow-up, necessitating extrapolation to inform decision making. This study assessed the incorporation of expert opinion on survival extrapolations, using data from CheckMate-214 investigating nivolumab plus ipilimumab (NIVO+IPI) for advanced renal cell carcinoma as a case study.
METHODS: A three-state partitioned survival model was developed using digitized trial data to evaluate overall survival (OS) and progression-free survival (PFS). Standard parametric survival models were initially fit to these data and assumed hypothetical expert opinions were then incorporated by penalizing the likelihood function. Cost-effectiveness was assessed from the UK National Health Service perspective over a lifetime time horizon. Both deterministic and probabilistic sensitivity analyses were used to assess the robustness of the results.
RESULTS: Incorporating hypothetical expert opinion at one time point which indicated a clear survival benefit for the intervention arm reduced uncertainty in OS predictions and lowered the incremental cost-effectiveness ratio (ICER) for NIVO+IPI from £41,893 / quality-adjusted life year (QALY) to £27,685 / QALY. Patients receiving NIVO+IPI experienced increased incremental QALYs due to prolonged survival. The ICER fell below the £30,000 willingness-to-pay threshold, suggesting cost-effectiveness under these hypothetical survival assumptions. Deterministic and probabilistic sensitivity analyses were in accordance with the base-case results.
CONCLUSIONS: In the absence of long-term trial data, expert opinion can enhance long-term accuracy and reduce uncertainty in survival extrapolations. In this case study, expert-elicited insights sufficiently improved the ICER to fall below the commonly accepted threshold. However, only one method for incorporating expert opinion was examined, warranting further exploration of alternative methods to validate and expand these findings. Linking these efforts to structured expert elicitation, could enhance the reliability of findings compared to informal methods. Further research should refine these methods and assess their broader impacts on HTA decision making.
Moving Beyond Market Access to Patient Access: What Are the Unintended Consequences of the IRA/DPN?
Session Type: Issue Panel
Topics: Health Policy & Regulatory
Level: Introductory
ISSUE: The Inflation Reduction Act (IRA), coupled with the implementation of Medicare Drug Price Negotiations (DPN), marks a pivotal shift in the U.S. healthcare landscape. The policy aims to reduce drug prices and ensure more equitable access to essential medications, particularly for those enrolled in Medicare. That said the broader impact on US healthcare system including drug development, the US payers and patient access warrants exploration. This panel will debate how these policies are shaping up to impact patients, the industry, and the US payers, and ultimately the unintended consequences on patient access to medicines. OVERVIEW: Jennifer will share a brief update on the IRA/DPN and evolving impact to the healthcare system. Panelists will share their perspectives and actionable insights with the audience. Following this session ISPOR members should have a clear understanding of the challenges the IRA/DPN poses to patients, payers and the industry, and considerations for strategies to mitigate these issues. Payer Perspective: Jessica will discuss the downstream implications of the IRA on US payers including the impact to patients with respect to the donut hole and caps on coverage. Patient Perspective: Joe will share how these policies impact individual patients, which may be much greater than not being able to access a single medicine in a single condition. Joe will offer insights into how the patient experience can inform decisions about where investment and research funding are allocated, which can change the landscape of future therapies for patients if not accounted for in the negotiation process. Industry Perspective: Ravinder will share the pharmaceutical industry perspective. While the industry recognizes the need for cost reduction in the healthcare system, there are concerns how these policies and the reduced revenue may lead to changes in R&D, innovation, and access to cutting-edge therapies. He will share the industry observed changes and considerations to enable innovation and market access.
Moderator
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Jennifer Whiteley, EdD
Oracle Health & Life Sciences, South San Francisco, CA, United States
Speakers
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Joe Vandigo, MBA, PhD
Applied Patient Experience, Greensburg, PA, United States
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Ravinder Dhawan, PhD
Merck Sharp & Dohme International Service B.V., Rahway, NJ, United States
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Jessica Daw, MBA, PharmD
Sentara Health Plans, Virginia Beach, VA, United States
How Do We Generate RWE in Rare Diseases or Targeted Subgroups? Use of Multi-Modal Data and Methodologies
Session Type: Issue Panel
Topics: Real World Data & Information Systems, Methodological & Statistical Research, Study Approaches
Level: Introductory
Rare diseases pose significant challenges to patients who are affected, to the providers who manage them, to the payers who reimburse treatments, to the investigators who study them, and to the healthcare system in general. In US, ~7,000 rare diseases exist affecting 25-30 million, altogether 9-12% of US population. Simultaneously, investment in research on targeted subgroups of prevalent diseases may also impose similar challenges when attempting to identify and evaluate these patients. While this approach poses several challenges, a primary issue/challenge to investigators is assembling cohorts of patients with rare/targeted diseases for an observational study to generate real-world evidence (RWE). This session will discuss the issues in RWE generation in rare diseases and present potential solutions by utilizing different databases and methodologies.
Overview of rare/targeted diseases and the challenges in RWE generation will be provided by the moderator (5 min). The panel will discuss the use of different multi-modal real-world databases including claims (closed and open claims), chargemaster database, Electronic Health Records (EHR), providers’ notes, medical charts, clinicogenomics and disease registries for patient selection and assembling cohorts of patients with rare diseases (15 min). Additionally, the panel will discuss different quantitative (including AI/ML) and qualitative (including grounded theory) methodologies and the importance of feasibilities studies in rare/targeted diseases (15 min). Moreover, the panel will discuss linkages of different databases, and tokenization of patients in generating RWE for rare/targeted diseases (15 min). Where necessary, the panelists will present examples from their current work. To conclude, the panel will recommend best practices for utilizing multi-modal databases and innovative methodologies in designing observational studies to generate critical insights into real-world clinical practice/management of patients with rare/targeted disease subgroups.
Moderator
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Phani Veeranki, MPH, DrPH, MD
Optum Life Sciences, CYPRESS, TX, United States
Speakers
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Amy Duhig, PhD
Takeda, Salem, WI, United States
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Arpita Nag, MBA, MS, RPh, PhD
AstraZeneca, Sudbury, MA, United States
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Lucinda Orsini, MPH
COMPASS Pathways, Skillman, NJ, United States
How Should Artificial Intelligence (Not) Be Used in Health Preference Research?
Session Type: Issue Panel
Topics: Patient-Centered Research
Level: Intermediate
ISSUE: Health preference studies have successfully informed various decisions across medical product development, such as endpoint selection, regulatory benefit-risk assessment, and reimbursement. The studies typically require the design of a new preference elicitation instrument that is resource-intensive to design, pre-test, field, and analyse. Artificial intelligence (AI) could provide efficiencies and allow novel approaches for health preference elicitation.
OVERVIEW: The panel will discuss the value of AI in health preference research. Prof. Marshall will open the panel by introducing key stages of health preference studies where AI is expected to bring value. Dr. Heidenreich will then discuss the use of AI in designing study materials using real-life examples. Dr. Boeri will discuss how existing literature can be reviewed with AI to support the development of health preference studies. Dr. Tervonen will discuss the use of AI in the analysis of qualitative preference data and social media listening. The panel will close with a discussion between panellists and the audience on their experience with artificial intelligence in health preference research. HEOR scientists benefit from attending this intermediate panel.
Moderator
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Deborah Marshall, PhD
University of Calgary, Calgary, AB, Canada
Speakers
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Sebastian Heidenreich, BSc, MSc, PhD
Evidera, London, United Kingdom
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Marco Boeri, BSc, MSc, PhD
OPEN Health, London, United Kingdom
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Tommi Tervonen, PhD
Kielo Research, Zug, Switzerland
Less Is More? Understanding and Rewarding the Full Value of Long-Acting Therapies
Session Type: Issue Panel
Topics: Health Technology Assessment, Health Service Delivery & Process of Care, Patient-Centered Research
Level: Intermediate
ISSUE: Long-acting (LA) therapies have the potential to transform treatment paradigms for various chronic conditions. However, current health technology assessment (HTA) frameworks struggle to fully capture their broader impacts, such as benefits to healthcare capacity, productivity, impact on carers, supply chain stability, and environmental sustainability. These limitations may affect patient access, product uptake, health system sustainability, and pharmaceutical innovation.
OVERVIEW: This Issue Panel will explore the methodological, evidentiary, pricing and reimbursement challenges of LA therapies affecting current HTA and payer decisions, as well as the implications for patients, healthcare systems, and society. The debate aims to identify practical strategies to better align HTA and reimbursement frameworks with the transformative potential of LA therapies, fostering more comprehensive, sustainable and equitable decision-making.
The moderator will introduce topic by providing a brief overview of challenges in valuing LAtherapies and sharing examples of current practices in North America and Europe (6 mins). Each panellist will then provide their perspective in about 8 mins each. Interactive audience engagement (incl. polling) will be done throughut the session (5 min). The session wil conclude with audience Q&A (25 min).
Moderator
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Lotte Steuten, MSc, PhD
Office of Health Economics, London, United Kingdom
Speakers
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Jody Jollimore, MSc
CATIE, Toronto, ON, Canada
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John O'Brien, MPH, PharmD
National Pharmaceutical Council, Washington, DC, United States
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Sean D Sullivan, PhD
University of Washington, Seattle, WA, United States
Personalizing Race and Ethnicity Data to Improve Real-World Evidence Relevance and Reliability
Session Type: Workshop
Topics: Real World Data & Information Systems, Methodological & Statistical Research, Study Approaches
Level: Intermediate
PURPOSE: Understanding health disparities by race and ethnicity is a priority for government, payers, industry, and healthcare delivery systems. Moreover, ensuring that research is representative is critical to have more inclusive, culturally sensitive, trustworthy, and equitable treatments and care. To address those topics, accurate and complete data on race/ethnicity is key. However, there are uncertainties regarding the reliability of those data in real-world data (RWD) sources, given the sensitive, debatable, and (inter)personal nature of such data. We will discuss the accuracy of race/ethnicity data in RWD, the implications for research, healthcare, regulatory and policy-making and personalized solutions to ensure accurate race/ethnicity data. DESCRIPTION: Martina Furegato will discuss ways to capture race/ethnicity in the RWE space, specifically in RWD and the importance of having reliable information captured in large scale data sources used for decision making processes and regulatory bodies. She will present a study that evaluated the quality of race/ethnicity in Oracle EHR RWD compared with self-reported data from a large population-based US survey. Carla Rodriguez-Watson will share how the RAISE (Real-world Accelerator to Improve the Standard of collection and curation of race and Ethnicity data in healthcare) Action Framework can help health systems implement priorities and strategies to improve race/ethnicity data. She will discuss tools and incentives available at the national level to improve infrastructure to collect and exchange race/ethnicity data; and examples of how different organizations have leveraged those tools.Rachele Hendricks-Sturrup will discuss various types of real-world patient-generated health data (RWPGHD) that can be used in conjunction with EHR data, and implications for patient subgroup analysis. She will discuss implications regarding the regulatory use and acceptability of RWPGHD to support clinical trial diversity goals and RWE reliability and quality.
Moderator
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Lysel Brignoli, MS
Oracle Life Sciences France, Paris, France
Lysel has over a decade of expertise in Real-World Evidence (RWE) and epidemiologic studies. Currently dedicated to designing and overseeing RWE studies, she also focuses on optimizing Oracle Life Sciences RWE offerings, with a particular emphasis on registries and innovative approaches.
Her extensive background includes leading international non-interventional studies spanning diverse disease areas such as dermatology and rare diseases. Specializing in developing direct-to-stakeholders studies, Lysel possesses deep experience in incorporating Patient-Reported Outcomes (PROs) into research initiatives. Her proficiency extends to the publication of research findings in congresses and peer-reviewed journals.
Speakers
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Martina Furegato, MSc
Oracle Life Science, Este, France
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Carla Rodriguez-Watson, PhD, MPH
Reagan Udall Foundation for the FDA, Washington, DE, United States
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Rachele Hendricks-Sturrup, MA, MSc
Duke-Margolis Center for Health Policy, Washington, DC, United States
Assessing the Broader Economic Impact of Investment in Healthcare Interventions – How Input-Output Modeling Complements HTA
Session Type: Issue Panel
Topics: Economic Evaluation, Study Approaches, Health Policy & Regulatory
Level: Intermediate
ISSUE: Recently, discussions about health investments focus on immediate costs, overlooking the connectedness with economic growth. We present and discuss opportunities to integrate macroeconomic viewpoints in traditional evaluation to address the repercussions of capital injection into the health sector. The panel underscores the need for innovative analytical concepts and confers about their applicability from different perspectives. OVERVIEW: M.M. introduces the topic sharing impressions from conversations with health ministries and the G20 Health and Development Partnership about systematic measurement of value creation through health investments(10min). The presenters emphasize different viewpoints(30min). D.G. explains how broader value analysis supports ISPOR Latin America Consortium and promotes action of FIFARMA to enable equal access to medicines for all patients regardless their socioeconomic conditions. B.L. shares his extensive experience in Input/Output modelling, presenting recent research across 51 US regions. He assesses state level health industry effects: the economic footprint of the pharmaceutical industry and its supply chains and further health impacts (improved survival and reduced sick time) that translate into a healthier, more productive workforce, and improve social and economic outcomes. V.D. provides insights on value assessment of investment in Alzheimer treatment in the US. He systematically integrates Input/Output modelling in traditional HTA and illustrates the political relevance of broader economic value quantification. Following this, the speakers will be interviewed about their key messages and debate about challenges and limitations of the introduced concepts(10min). We close with an interactive discussion with the audience(10min). This panel provides valuable insights for researchers, pharmaceutical industry stakeholders, and decision makers on how novel evidence-based strategies could be utilized to align health investments with national and regional development goals.
Moderator
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Malina Müller, BA, MA, PhD
WifOR Institute, Darmstadt, Germany
Speakers
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Diego Guarin, MPH, MSc, MD
Merck, Rahway, NJ, United States
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Karam Diaby, BSc, MSc, PhD
Otsuka, Princeton, NJ, United States
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Billy Leung, MA
REMI, Amherst, MA, United States
Current Trends and Advances in Health Preference Methods and Insights from Health Preference Studies
Session Type: Research Podiums
Stated preference methods are commonly used to better understand patient, physician and other stakeholder preferences for healthcare interventions. This session covers current trends and advances in health preference methods and insights. The session will start with a review of probabilistic attribute presentation in discrete choice experiments (DCEs) (presentation #1), followed by study using fusion analysis of pooled existing preference data for benefit transfer (presentation #2). The second half of the session will present a study on health preference research insights to facilitate shared-decision making (presentation #3) and conclude with a comparative preference study of patient and physician preferences in type 2 diabetes using a DCE and Best Worst Scaling (BWS).
Probabilistic Attribute Presentation in Discrete Choice Experiments (DCEs): A Review of Current Practice
OBJECTIVES: How probabilities are presented in discrete choice experiments (DCEs) has been shown to impact how participants interpret information. This study aimed to synthesize current practice in presenting probabilities in DCEs, and report the nature of attributes, framing, and visual presentation.
METHODS: A scoping review was performed to identify DCEs which included probabilistic attributes for health-related interventions from October 2022 through August 2024. Articles were identified from Medline, Embase, Web of Science, EconLit, and PsychINFO, with titles/abstracts and full-texts subsequently screened. Relevant studies were extracted using a pre-specified framework.
RESULTS: Data from 98 studies were extracted. DCEs spanned a range of therapeutic areas, most commonly oncology (30%), endocrinology (11%), and dermatology (7%). Most studies included patients (83%), were focused on assessing treatment preferences (81%), and reported some pre-testing (83%). The majority of DCEs included 5-7 attributes (70%) and 1-3 probabilistic attributes (77%).
More DCEs included probabilistic risk attributes (85%) than probabilistic benefit attributes (64%). Risks were most frequently presented as proportions alongside percentages (37%), and benefits most frequently as percentages only (30%). All risk attributes used absolute framing, whereas 16% of benefit attributes used relative framing. Graphics were used more often to present risks than benefits (59% v 46%); within these, arrays of person-like figures were used in 72% of risks and 71% of benefits. Exclusively male figures were used for 80% of benefits and 87% of risks. Blue (31%) and red (27%) colors were most used for risks, and blue (38%) and green (28%) for benefits.
CONCLUSIONS: Current practices of presenting probabilistic attributes were generally consistent in following good practice in pre-testing and using some visual representation. The variety of graphics used to display probabilistic risks and benefits, specifically gender/shape, and color, indicate that work to understand how participants interpret different presentations may assist critical DCE design decisions.
Using What We Already Know:Fusion Analysis of Primary Patient-Preference Data for Benefit Transfer
OBJECTIVES: We undertook the first fusion or data-enrichment analysis to pool primary patient-preference data from multiple benefit-risk discrete-choice experiments to use the results for preference benefit transfer in a novel application.
METHODS: Robust benefit-transfers require multiple previous studies to facilitate transferring either a consensus unit value or a function. The maturation of health-preference research is indicated by the number of published studies that have accumulated in inflammatory bowel disease. The studies all included remission and serious-infection risk attributes, which facilitates obtaining a consensus measure of maximum acceptable infection risk for a given period of remission. However, the data-fusion model required several assumptions to harmonize variable definitions. Using the pooled data, we estimated scale-adjusted, latent-class, random-parameters logit models and used a 7-study fusion model to predict estimates for 2 hold-out studies.
RESULTS: A poolability test failed to reject similarity in the ratio of efficacy (months of remission) to risk of serious infection, allowing for all other study-specific attributes to vary. The pooled dataset combined 2,249 respondents and 25,094 choice questions. 5 studies surveyed patients with Crohn’s disease and 4 studies surveyed patients with ulcerative colitis. We identified 2 distinct preference classes plus a third statistically uninformative (also called task non-attendant or “garbage”) class. For the Crohn’s-disease hold-out study the mean maximum acceptable infection risk for 12 months of remission was 7.2% (5.6 - 8.7), with a predicted value of 7.2% (6.6 - 7.8). For the ulcerative-colitis hold-out study the maximum acceptable risk was 9.8% (7.5 - 12.2), with a predicted value of 14.2% (9.8 - 18.5).
CONCLUSIONS: LCRPL models are an effective tool for organizing and synthesizing multi-study evidence bases. Similar to clinical evidence bases, this information is useful to inform decision-making in situations where de novo preference studies are not possible, given time and cost constraints.
Patient Preferences on Understanding Medical Tests and Monitoring Equipment in Hospitalized Care
OBJECTIVES: This survey investigates hospitalized patients' perspectives on comprehending medical tests, monitoring equipment, and their preferences for information sharing. We aimed to identify key factors that influence patient engagement and their sense of control over treatment planning and care decisions.
METHODS: A US-based online survey was conducted in 2024; data collection ceased when 1000 complete responses were received (2 weeks). Respondents self-identified as having been hospitalized; the survey focused on comprehending medical tests, equipment used, and information provided by clinicians. Key questions addressed patients' desire for explanations about monitoring devices at the bedside, measured hemodynamic parameters, and potential health risks associated with abnormal readings. Further, patients were asked about their concerns regarding monitoring equipment and what factors could enhance their inclusion in treatment planning.
RESULTS: Results indicate that 94.9% of patients believe it is important to comprehend medical tests they are undergoing, with the majority expressing a desire for explanations about the function of devices at their bedside. Participants reported wanting prompt feedback on hemodynamic parameters. Additionally, 70% of patients desired detailed explanations regarding potential health issues related to abnormal measurements. Concerns regarding the accuracy and reliability of monitors, as well as comfort level while being monitored, were prevalent. Nearly half cited increased involvement in treatment planning and being informed about progress as key contributors to participants' sense of control.
CONCLUSIONS: Patients desire increased transparency regarding diagnostic procedures and monitoring devices. Clear and comprehensible information sharing is crucial for enhancing patient engagement, mitigating concerns, and fostering a sense of autonomy in health management. Healthcare institutions are strongly advised to implement strategies that effectively deliver this information in a manner that is easily understood by patients, thereby empowering them to assume a more active role in their own healthcare.
Is There Any difference in Preferences Between Patients and Physicians? Evidence From Anti-Hyperglycemic Medications Choices for Type 2 Diabetes
OBJECTIVES: This study aimed to investigate differences in preferences between Chinese patients with type 2 diabetes (T2DM) and physicians when choosing anti-hyperglycemic medicine.
METHODS: The study collected preference data through a discrete choice experiment (DCE). Patient data were collected via face-to-face surveys at 28 healthcare institutions, selected from two cities each in the eastern, central, and western regions of China. Physician data were collected through online questionnaires, covering a total of seven provinces. Seven medication attributes—treatment efficacy (HbA1c reduction), risk of hypoglycemia, gastrointestinal side effects, weight change, cardiovascular benefits, mode of administration, and out-of-pocket cost—were developed through literature review, expert consultation, and best-worst scaling with T2DM patients. Data were analyzed using Conditional-Logit and Mixed-Logit models to calculate marginal willingness to pay (mWTP). The preference heterogeneity was explored using a latent class model (LCM).
RESULTS: A total of 1,793 valid patient questionnaires and 168 valid physician questionnaires were collected. The results showed that out-of-pocket cost, treatment efficacy (β=1.18, p=0.00), and risk of hypoglycemia (β=1.11, p=0.00) were the primary concerns for patients, while physicians prioritized the risk of hypoglycemia (β=0.98, p=0.00), cardiovascular benefits (β=0.93, p=0.00), and out-of-pocket cost. Regarding mWTP, patients showed the highest willingness to pay for medications offering a 2.5% HbA1c reduction (mWTP=¥295), while physicians preferred medications with a 1.5% HbA1c reduction (mWTP=¥372). Additionally, physicians exhibited a willingness to pay (mWTP=¥864) for medications providing cardiovascular protection, 3.1 times higher than patients’ (mWTP=¥277). A strong preference for out-of-pocket cost was observed in a patient subclass, whereas physicians exhibited a lower preference.
CONCLUSIONS: The study indicates significant differences in medication preferences between patients and physicians, particularly regarding efficacy, administration mode, weight change, and cardiovascular benefit. Out-of-pocket cost and gastrointestinal side effects are common concerns for both groups. Clinical decision-making should consider patients’ medication preferences to enhance shared decision-making and patient-centered care.
6:00 PM - 7:00 PM
Montreal Street Festival supported by ISPOR's Year-Round Sponsors (Exhibit Hall)
Session Type: General Meeting
Experience the vibrant flavors of the city at our "Montreal Street Festival," a dynamic reception where each participating sponsor booth offers Montreal-inspired food and beverage. Sponsored by ISPOR's year-round sponsors."
Women in HEOR Reception (Exhibit Hall)
Session Type: General Meeting
Continue the inspiring conversations from the Women in HEOR session at ISPOR 2025 in Montreal! Join us for networking and collaboration with fellow professionals who share your passion for advancing women's roles in heath economics and outcomes research. This is a unique opportunity to connect, share ideas, and foster relationships that can lead to impactful initiatives within our field. All attendees are welcome!
Fri May 16
7:00 AM - 8:00 AM
Friday Morning Coffee and Connect
Session Type: General Meeting
It may be the last day, but there is still so much to learn! Head to the breakout rooms for the final session banks and an opportunity to share your thoughts with fellow attendees. Provided by ISPOR.
7:00 AM - 1:00 PM
Registration Hours
Session Type: General Meeting
8:00 AM - 9:00 AM
Are Social Determinants of Health (SDoH) Data Ready for Primetime?
Session Type: Issue Panel
Topics: Real World Data & Information Systems, Clinical Outcomes, Study Approaches
Level: Intermediate
ISSUE: Social determinants of health (SDOH) are nonmedical factors that influence health outcomes, encompassing elements like education, employment, housing, and food insecurity. It is well-established that SDOH impact health outcomes and are associated with health disparities. The importance of understanding the impact of SDOH on access to healthcare and health outcomes is undisputed. However, whether electronic SDOH data capture within electronic health records is fit for purpose to address health disparities and enhance clinical trial diversity for individuals impacted by SDOH is uncertain.
OVERVIEW: FDA recently issued draft guidance for the industry on “Diversity Action Plans to Improve Enrollment of Participants from Underrepresented Populations in Clinical Studies.” SDOH create challenges for active participation in health care and research. Gaining a better understanding of this relationship is the first step in developing interventions to address disparities that negatively impact health equity. However, barriers remain in our ability to comprehensively study the impact of social determinants on access and outcomes due to gaps in the data, particularly robust measures of SDOH. The collection of SDOH data has been increasing, and with it, research on its impact on health outcomes. This session will debate the readiness of SDOH data to inform our efforts to address health disparities in the US. Smita Kothari-Talwar will provide an overview of the issue, including a historical perspective. Amy O’Sullivan will argue that the collection of SDOH measures has improved in recent years, citing examples of research demonstrating the impact of SDOH on diagnosis, treatment, and outcomes. C. Daniel Mullins will take the opposing view that the data are not yet ready to be used to inform decisions regarding interventions to address heath disparities. The outcome of this debate will help illuminate the current state of SDOH data readiness and guide future efforts to effectively combat health disparities.
Moderator
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Smita Kothari, PhD
Merck Sharp & Dohme International Service B.V., Rahway, NJ, United States
Speakers
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Amy K O'Sullivan, PhD
Ontada, Boston, MA, United States
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C. Daniel Mullins, PhD
University of Maryland Baltimore, Baltimore, MD, United States
C. Daniel Mullins is a Professor at the University of Maryland School of Pharmacy. He is Founder and Executive Director of the University of Maryland PATient-centered Involvement in Evaluating effectiveNess of TreatmentS (PATIENTS) Program, a community-academic partnership for patient-driven research. Dr. Mullins has received approximately $25 million in funding as a Principal Investigator from AHRQ, FDA, NCI, NHLBI, NIA, NIMHD, the Patient-Centered Outcomes Research Institute (PCORI) and various patient advocacy organizations and pharmaceutical companies. At the University of Maryland Baltimore (UMB), he received the Dr. Patricia Sokolove Outstanding Mentor Award and the Dr. Martin Luther King Jr. Faculty Diversity Award. He was named Researcher of the Year at UMB and was awarded a University System of Maryland Wilson H. Elkins Professorship. At ISPOR, he has served as Editor-in-Chief of Value in Health since 2010 and received the Marilyn Dix Smith Leadership Award in 2017.
Addressing Information Bias in Electronic Health Records and Claims Data: What Can the Literature Tell Us and How Should We Respond?
Session Type: Workshop
Topics: Real World Data & Information Systems, Organizational Practices, Study Approaches
Level: Intermediate
PURPOSE: Recently, there has been increased consideration of real-world data (RWD) and real-world evidence (RWE) in regulatory and health technology assessment (HTA) decision-making. However, information bias (i.e., measurement error, variable and outcome misclassification) can hinder the effective use of RWD. It is thus important for researchers to understand how information bias can impact the validity of RWE and work to mitigate it in their studies. This workshop will provide an overview of information bias in RWD studies, with a focus on electronic health records (EHR) and claims data. Participants will learn about current strategies for information bias mitigation and potential paths forward for best practices. DESCRIPTION: Workshop attendees will obtain a working knowledge of information bias in general and nuances specific to the impact of information bias on studies utilizing EHR/claims data. This workshop will review the recent literature and selected case studies to provide a comprehensive overview. Dr. Arena will chair the session and introduce the topic, highlighting the various ways information bias can impair studies (5 minutes). Mr. Sun will discuss their organization’s strategies for mitigating information bias and present findings from a recent targeted literature review on the topic (15 minutes). Dr. Esposito will then discuss how they address information bias in vaccine studies through both design and quantitative bias analysis (15 minutes). Finally, Dr. Tadros will examine case studies to illustrate practical approaches to addressing information bias in real-world scenarios using Canadian data (15 minutes). Audience participation will include assessment of a proposed tool for information bias mitigation (10 minutes); audience feedback will be used to refine the tool and contribute to proposed best practices. This methods workshop will be of interest to RWE researchers and knowledge users who are concerned about the impact of information bias on their studies.
Moderator
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Patrick Arena
Aetion, New York, NY, United States
Patrick (Pat) Arena, PhD, MPH, is a Director of Science at Aetion, Inc. with more than five years of industry experience. Since joining Aetion in 2022, he has applied epidemiologic expertise to original RWD research, advanced the role of RWE in regulatory and HTA decision-making, and provided regulatory consulting support for pharmaceutical clients. Prior to Aetion, Pat worked as a contractor at Pfizer, where he contributed to post-marketing studies and Phase II/III vaccine clinical trials. He has also conducted global health research in Southeast Asia and Central Africa.
Throughout his career, Pat has published RWD studies across multiple jurisdictions, including the US, China, Africa, and Europe, and has developed thought leadership on RWD/RWE transferability and transportability. He earned his BS from Boston College, MPH from Columbia University, and PhD in Epidemiology from UCLA. His doctoral training focused on maternal immunization safety, COVID-19, and pharmacovigilance.
Speakers
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Yezhou Sun, MS
Merck & Co. Inc, Boston, MA, United States
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Mina Tadrous, MS, PharmD, PhD
University of Toronto, Toronto, ON, Canada
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Daina B Esposito
Moderna, Westford, MA, United States
Can Pre-Launch Collaboration With Payers Address Uncertainty in Value Assessments Amid Growing Regulatory and Access Gaps?
Session Type: Issue Panel
Topics: Health Technology Assessment, Health Policy & Regulatory, Economic Evaluation
Level: Intermediate
ISSUE: Recent years have seen significant changes in the regulatory landscape, with the FDA and EMA becoming more open to innovative clinical trial designs in oncology and rare diseases. These advancements have facilitated earlier patient access to treatments. However, such shifts are not always embraced by payers. The uncertainty surrounding the value of these medicines, regarding population impact, comparative effectiveness, and long-term outcomes, often remains unclear at launch. Furthermore, the high price tags associated with these treatments pose additional challenges for payers, complicating reimbursement decisions and delaying access.Can closer collaboration between pharmaceutical companies and payers help bridge the gap between regulatory advancements and access challenges by reducing uncertainty regarding short-term budgets and long-term outcomes? This issue is not just about trust; it also involves barriers related to accounting systems, data transparency, privacy concerns, revenue uncertainty, and a reluctance to share risk. OVERVIEW:This panel will explore potential solutions for developing a comprehensive strategy to demonstrate the value of medicines at launch while ensuring pricing reflects their true value for all stakeholders. Moderated by Cristina Masseria, the discussion will gather perspectives from various stakeholders. Brian Solo and Brian O’Rourke will address the barriers and opportunities for value demonstration in the USA and globally, examining the evolving relationship between payers and pharmaceutical companies. Are payers resisting current pricing strategies, and which barriers may be more easily overcome? Can cross-country collaboration in data generation, horizon scanning, and negotiations provide a path forward? Diane Munch will share the pharmaceutical company’s perspective, discussing pricing and evidence generation strategies, as well as potential solutions for deeper collaboration with national, regional, and local stakeholders throughout a product’s lifecycle.
Moderator
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Cristina Masseria
Aesara, Madrid, Spain
Speakers
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Brian O'Rourke, BSc, PharmD
Brian O'Rourke Health Care Consulting Inc., Ottawa, ON, Canada
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Brian Solow, MD
Optum Life Sciences, Irvine, CA, United States
With more than 30 years of experience as a physician executive, Dr. Solow is a national thought
leader and recognized as a passionate and innovative visionary leader with extensive managed
care experience working with primary care, specialty physicians, clients and medical facilities,
and health plans.
Most recently, Dr. Solow served as the Chief Medical Officer of Optum Life Sciences, a
segment of UnitedHealth Group. In his Chief Medical Officer role, Dr. Solow oversaw all clinical
aspects of the business including data and insights, clinical research, scientific consulting,
value-based contracting, and the digital research network. Optum Life Sciences leverages
advanced data, analytics, and cross-industry health care expertise to serve payer, provider and
life sciences clients.
Dr. Solow also has served as the Chief Medical Officer at OptumRx, one of the world’s largest
pharmacy care services organizations, where he oversaw clinical services including formulary
development and management. Prior to joining Optum, Dr. Solow was an active member of a
physician-owned medical group, maintaining a full-time practice while also holding management
roles.
Dr.Brian Solow is a well-known national and international speaker on a range of health care
topics and has served as the US representative of the HTA Council for the International Society
for Pharmacoeconomics and Outcomes Research (ISPOR). He is a fellow of the American
Academy of Family Physicians, has served as a member of the U.S. Pharmacopeia (USP)
Medicare Model Guideline Expert Panel Advisory Committee and on FDA advisory panels.
Dr. Solow earned his undergraduate degree at the University of California, San Diego and
completed his MD at New York Medical College. He did his family practice residency at UCLA/
Northridge Medical Center
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Diane Munch, PhD, MD
Pfizer Inc, New York City, NY, United States
Rare but Common: Generative AI’s Potential on Data, Evidence, and Insight Generation in Rare Diseases
Session Type: Workshop
Topics: Patient-Centered Research, Health Policy & Regulatory, Study Approaches
Level: Intermediate
PURPOSE: This panel explores the potential of Generative AI (GenAI) in addressing the unique challenges of rare diseases. The discussion focuses on three key areas: 1) Data: Unlocking data through GenAI and large language models (LLMs) to enrich research data on rare diseases. 2) Evidence: Developing rare disease-specific knowledge graphs to better represent natural history and disease pathways. 3) Insights: Generating actionable insights to address unmet patient needs and support early trial recruitment, ultimately improving patient outcomes and healthcare decision-making. DESCRIPTION: About 10% of individuals worldwide are affected by rare diseases (more than 7,000 rare diseases). Rare diseases, while individually uncommon, are collectively more prevalent than often realized. For example, over 60% of oncology drugs are approved based on specific biomarkers, redefining certain cancer subtypes as rare diseases. The evolving evidence underscores the complexity of clinical research for rare diseases, compounded by limited patient populations, scarce evidence, and high treatment costs. Generative AI may offer a new opportunity to address these challenges. Dr. Xu (Yale) will open the session with an overview of GenAI advancements, focusing on how LLMs can generate more data for rare diseases and their phenotypes from clinical notes. Dr. Wang (Tulane) will discuss leveraging LLMs and knowledge graphs to extract data from clinical, literature and social media, enabling a deeper understanding of disease history and pathways. Dr. Weng (Columbia) will present the use of fine-tuned LLMs for early diagnosis of rare diseases and genetic testing recommendations using RAG models. Finally, Dr. Wang-Silvanto (Astellas) will provide an industry perspective on the alignment of robust data and evidence to address unmet needs, inform early trial recruitment and support decision-making in pharmaceutical settings. The session concludes with an interactive Q&A and digital polling to encourage audience participation.
Moderator
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Xiaoyan Wang, PhD
IMO health, Westport, CT, United States
Speakers
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Hua Xu, PhD
Yale University, New Haven, CT, United States
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Chunhua Weng, Ph. D
Columbia University, New York, NY, United States
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Jing Wang-Silvanto, PhD
Astellas Pharma Europe Ltd, Addlestone, United Kingdom
Access and Affordability
Session Type: Research Podiums
This session explores various aspects of healthcare access, resource utilization, and treatment optimization. Presentations will cover topics on strategies for optimizing biosimilar use in oncology practices, on recent Medicaid policy changes and their impact on postpartum coverage, on access to care and affordability of treatments for adults with obesity, shedding light on potential disparities in healthcare access, and on claims-reported pruritus in patients with primary biliary cholangitis. These presentations will offer valuable perspectives on improving healthcare access, optimizing treatment decisions, and addressing challenges in various patient populations and healthcare settings.
Alignment Between CDA Recommendations and pCPA Negotiation Outcomes: Exploring Factors Influencing Reimbursement Success
OBJECTIVES: This study assesses the alignment between Canadian Drug Agency (CDA) reimbursement recommendations and pan-Canadian Pharmaceutical Alliance (pCPA) negotiation outcomes. It examines factors contributing to failures in pricing negotiations for drugs considered to provide sufficient value to the Canadian healthcare system.
METHODS: CDA and pCPA websites were screened to identify and match publicly available reimbursement reviews and negotiation projects. HTA reports were analyzed to extract CDA’s conditions for reimbursement. Exploratory analysis, hypothesis testing (Chi-squared and Wilcoxon tests), and text pattern detection were performed using R (version 4.4.2).
RESULTS: As of January 2024, 921 projects were published on the pCPA website: 69.5% concluded with an agreement, 11.2% without agreement, 5.1% under active negotiations, and the rest not pursued. After matching CDA recommendations to completed negotiations, 355 projects from May 2005 to June 2024 were analyzed, with 301 (91.8%) receiving positive CDA recommendations (reimburse with conditions) and 20 (8.2%) negative recommendations (do not reimburse). A statistically significant association was found between CDA recommendations and pCPA negotiation results (p = 0.0022). Notably, 19 (5.4%) of projects with negative recommendations reached an agreement, while 39 (11%) with positive recommendations failed to secure one. Among positive CDA recommendations that failed in negotiations, 14 (38%) were contingent on price reductions to improve cost-effectiveness (ranging from 50% to 97%, averaging 82.5% of the submitted price), while 23 (62%) were contingent on referencing against the lowest-cost treatment alternative. Failed negotiations had a median duration of 226 days, significantly longer than the 143.5 days for successful ones (p = 0.00154).
CONCLUSIONS: The CDA's reassessment of cost-effectiveness analysis often results in substantial price reduction recommendations—up to 97%—to ensure a technology provides value for money. This may lead to unsuccessful negotiations with the pCPA due to manufacturers' reluctance to accept these conditions, potentially limiting patient access to valuable medicines.
Impact of Medicaid Enrollment Provisions on Postpartum Coverage and Resource Use in Three US States
OBJECTIVES: To explore changes in postpartum Medicaid coverage and resource use following two federal provisions that expanded eligibility in three US states.
METHODS: Medicaid financed live births from 1/1/2018-12/31/2023 with a Georgia, Florida, or South Carolina state of residence at the time of delivery were identified in a dataset that includes administrative claims data for 3 million mother-infant pairs. The proportion of mothers with at least six months continuous postpartum coverage was evaluated for three time periods: 1) pre-COVID-19 public health emergency (when each included state had a 60-day postpartum coverage limit for those eligible through pregnancy alone), 2) birth during Families First Coronavirus Response Act (FFCRA, which prohibited Medicaid termination), 3) birth occurring after state-specific adoption of American Rescue Plan Act (ARPA, federal matching funds available for postpartum coverage expansion). For those with at least six months postpartum coverage, baseline comorbidities and postpartum resource use occurring between 60 days and six months following childbirth was evaluated and compared between pre-COVID and ARPA adoption time periods.
RESULTS: 96,025 pregnancy episodes were identified (40% pre-COVID-19, 39% FFCRA, 21% ARPA). The proportion of mothers with at least six months postpartum coverage increased from 41.05% pre-COVID-19 to 95.34% and 95.63% during FFCRA and ARPA, respectively. Compared with pre-COVID-19, pregnancy episodes following ARPA adoption had fewer office visits (1.95 vs. 2.90, p<0.01) and a similar rate of hospitalization (1.00% vs. 1.17%, p=0.12). A higher proportion of ARPA pregnancy episodes had pre-existing obesity (26.51% vs. 24.92%, p<0.01), however, fewer had hypertensive heart disease (10.31% vs. 11.43%, p<0.01) and type 2 diabetes mellitus (1.88% vs. 2.25%, p=0.02).
CONCLUSIONS: States that extended pregnancy-related Medicaid eligibility postpartum experienced a substantial gain in coverage continuity. Further research is needed to determine whether an observed decrease in preventative resource utilization following ARPA adoption is due to population-level clinical differences or unmeasured barriers to access.
Access to Care and Ability to Afford Prescription and Medical Treatment Among Adults With Obesity in the United States
OBJECTIVES: Obesity rates continue to rise in the United States, representing a substantial public health threat. Although effective pharmacologic treatments are now available for weight loss, very few adults with obesity are treated. Within this context, understanding the healthcare experiences of people with obesity is increasingly important. This research aims to evaluate the accessibility and affordability of medical care and prescription medications for US adults with obesity.
METHODS: This cross-sectional study utilized data from the 2022 Medical Expenditure Panel Survey (MEPS) to identify individuals aged 18 and older with obesity (BMI ≥ 30). Obesity was categorized into classes I (BMI 30-34.9), II (BMI 35-39.9), and III (BMI ≥ 40). Logistic regression models assessed associations between BMI categories and three outcomes: having a usual source of healthcare, affordability of medical care, and affordability of prescription medications while adjusting for age, sex, and race/ethnicity. Personal weights were applied to obtain national estimates.
RESULTS: Among 10,601 eligible respondents, 3,711 (representing 50.9 million US adults) had obesity. Compared to normal-weight individuals, those with obesity were more likely to have a usual source of healthcare, with the odds increasing across obesity classes and reaching significance in Obesity Class III (OR = 1.84, 95% CI: 1.39-2.43). While cost-related barriers to medical care did not significantly differ across obesity classes, the odds of experiencing medication affordability issues increased with the obesity class. Specifically, adults in obesity class III had the highest odds of delaying medications due to cost (OR = 2.38, 95% CI: 1.50-3.77) and being unable to afford medications (OR = 1.92, 95% CI: 1.18-3.12).
CONCLUSIONS: While adults with obesity engage more with the healthcare system, they face significant barriers to medication affordability. Targeted interventions and policies are needed to improve access to affordable care and support effective obesity management.
Biosimilar Optimization in Community Oncology Practices
OBJECTIVES: Biosimilars reduce the burden of cost on patients and payers, thereby increasing access to life-saving care. Nevertheless, biosimilar uptake in the US has been inconsistent. Previous studies revealed favorable biosimilar perceptions among oncologists, however, research on predictors of biosimilar use is limited. We examined how biosimilar utilization differs across oncology care provider and provider group characteristics, as well as patient clinical factors.
METHODS: This retrospective cohort study used data from a community oncology network spanning 25 provider groups. The outcome was biosimilar utilization. Operational predictors, or predictors associated with practice infrastructure and clinical decision-making, included patient age, gender, diagnosis, line of therapy, clinical trial participation, provider time in practice, practice payer mix, and drug class (e.g., rituximab and its biosimilars). Economic predictors, or financial factors, included patient payer type, and Oncology Care Model (OCM) status. A generalized linear mixed model estimated the odds ratios (ORs) for biosimilar utilization.
RESULTS: A total of 478,709 drug administrations were analyzed. Biosimilar utilization was predicted by diagnosis, line of therapy, clinical trial participation, provider time in practice, OCM status, practice payer mix, patient payer type, and drug class. Patients diagnosed with lymphoma had the highest odds of receiving a biosimilar (OR=2.20, p<0.01). Patients in their first line (1L) of therapy were less likely to receive a biosimilar when compared to 2L (OR=1.55, p<0.01), 4L and above (OR=1.38, p=0.02), adjuvant setting (OR=1.84, p<0.01), and neoadjuvant setting (OR=2.53, p<0.01). The odds of receiving a biosimilar decreased for clinical trial participants (OR=0.01, p<0.01) and increased for OCM practices (OR=1.40,p<0.01). Patients continuing a class of therapy were more likely (OR=8.27, p<0.01) to receive a biosimilar than those starting a new class.
CONCLUSIONS: In a setting where provider perceptions toward biosimilars are generally favorable and barriers are infrequent, operational and economic factors may drive biosimilar optimization.
Prescription Drug Affordability Boards (PDABs): Are There Opportunities for Robust and Transparent Engagement?
Session Type: Issue Panel
Topics: Health Policy & Regulatory
Level: Introductory
ISSUE: The Colorado Prescription Drug Advisory Board (PDAB), arguably one of the most advanced, has now completed 5 drug affordability reviews. Are there opportunities to improve the ways key stakeholders engage with PDABs, and provide evidence to support PDAB affordability reviews? We delve into the perspectives of a PDAB advisory council member, manufacturers and a patient group.The panelists agree that open and fair dialogue is essential for PDAB processes, using the experience of the Colorado PDAB thus far as an example to provide constructive advice for those engaging or about to engage in the process. The panel seeks to explore how patient groups and manufacturers can effectively engage with PDABs to allow a fair and transparent review of selected medicines. OVERVIEW: The moderator will provide an overview of PDABs and how they fit into the broader access landscape in the US. In increasingly challenging times of healthcare spending, States are seeking ways to curtail and manage their expenditure on prescription drugs. PDABs have emerged as a policy solution in multiple states. This panel seeks to explore how stakeholders, including patient groups and manufacturers, can effectively engage with PDABs to support a consistent, fair and transparent review of selected medicines.
Moderator
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Elaine Tate
Cencora, Royston, United Kingdom
Speakers
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Robert B McQueen, BA, MA, 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. He is active in ISPOR through contributions to short courses, workshops, issue panels, and research presentations.
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Tiffany Westrich-Robertson, BS
International Foundation for AiArthritis, Saint Louis, MO, United States
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Justin Nedzesky, MS, PharmD
Neurocrine Biosciences, San Diego, CA, United States
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Kathryn Chandra, MA
Genentech USA, Inc., Washington, DC, United States
Kathryn (Katie) Chandra serves as the Senior Director of State Policy on Genentech's US Policy & Evidence Team. In this role, she leads the state policy team in proactive and reactive strategy development and engagement on state policies affecting Genentech's business and patient access to medications.
The Intended and Unintended Consequences of Societal Perspective Cost-Effectiveness Analyses
Session Type: Issue Panel
Topics: Economic Evaluation, Health Technology Assessment, Health Policy & Regulatory
Level: Intermediate
ISSUE: A societal perspective analysis in cost-effectiveness intends to capture, in a quantitative way, the health and non-health impact of a health intervention compared to alternatives reflecting relevant budgets, other constraints, and policy objectives across sectors. Costs and potential benefits outside of the health sector are increasingly being called out as missing from cost-effectiveness analysis with a potential consequence of not capturing the full value of a health intervention. Less often emphasized are the potential unintended consequences, including the need for equally expanded consideration of opportunity costs for different outcomes and in different sectors, and the difficulty in attributing societal improvements to a specific health intervention. This panel will debate the intended and unintended consequences of a societal perspective cost-effectiveness analysis, appropriate approaches to implementation, and highlight considerations to move the field forward in a balanced way. OVERVIEW: Alex Haines (10 minutes) will introduce the debate by outlining what it means to undertake a societal perspective cost-effectiveness analysis and what the potential intended and unintended consequences are. Marina Richardson (12 minutes) will share the Institute for Clinical and Economic Review’s (ICER) cautious optimism for societal perspective analyses and its view on the role that such a perspective should play. Simone Sutherland (12 minutes) will highlight considerations from a technology developers’ perspective and why intentional consideration of societal domains in the cost-effectiveness analysis outweighs the potential unintended consequences. Mark Sculpher (12 minutes) will reflect on both perspectives and share work that aims to ensure the intent of the broader analysis is inclusive of considerations for opportunity cost. The floor will then be open to interactive polling and audience Q&A to discuss priorities for a meaningful and balanced inclusion of societal impacts in cost-effectiveness analysis.
Moderator
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Alex Haines, BSc, MSc
CDA-AMC, Ottawa, ON, Canada
Speakers
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Marina Richardson
ICER, Boston, MA, United States
Marina Richardson is an associate director, Health Technology Methods and Health Economics with the Institute for Clinical and Economic Review (ICER). In her role, Marina leads and oversees the development of economic models to inform pricing and reimbursement decision-making and identifies and executes opportunities to enhance ICER's methodology and processes within Health Technology Assessment (HTA) and Health Economics. Prior to joining ICER, Marina led and contributed to reimbursement review reports and recommendations at Canada's Drug Agency (CDA-AMC), formerly CADTH. Marina has a PhD in Health Services Research from the University of Toronto and is an active contributor to the field including as a deputy editor for the International Journal of Technology Assessment in Health Care (IJTAHC), a member of the Ontario Immunization Advisory Committee (OIAC) in Ontario, Canada, and as a co-chair of the International Scientific Program Committee for Health Technology Assessment International (HTAi) 2025.
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C Simone Sutherland, BSc, MSc, PhD
Health Economist, Basel-Stadt, Switzerland
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Mike Paulden, PhD
University of Alberta, Edmonton, AB, Canada
Novel Concepts and Frameworks in Health Economic Evaluations
Session Type: Research Podiums
This session introduces novel Health Technology Assessment (HTA) frameworks to address ethical complexities and integrate multi-indication evidence, as well as the use of innovative payment/pricing schemes and health benefit metrices to quantify treatment value. Collectively these new frameworks and approaches can help inform decision-making in healthcare evaluation, reimbursement, regulation.
Moderator
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Rahul Mudumba, BA, MS
USC ISPOR Student Chapter, Union City, CA, United States
Quantifying Treatment Value Using Alternative Health Benefit Metrics: A Case Study of Adjuvant Osimertinib for Elderly Patients with EGFR mutated NSCLC Following Resection
OBJECTIVES: Traditional cost effectiveness analysis uses quality-adjusted life years (QALYs) to assess health benefits, however alternative measures are being considered as alternatives for evaluating healthcare interventions. We quantified the economic value of adjuvant osimertinib in completely resected elderly patients with EGFR-mutated NSCLC using four different quantitative health benefit measures.
METHODS: A 5-health-state state-transition model compared the lifetime costs and health gains of adjuvant osimertinib with placebo among completely resected Stage IB-IIIA EGFR-mutated NSCLC patients aged ≥65 over a 35-year time horizon. Efficacy and safety were drawn from the ADAURA trial (NCT02511106) and costs obtained from the literature. A US payer perspective and societal perspective incorporating productivity and caregiver impacts, was used. Three novel metrics for health gains were equal value of life years gained (evLYG), health years in total (HYT), and generalized risk-adjusted quality-adjusted life years gained (GRA-QALYs). EvLYG is akin to QALY but assigns a utility value of 0.851 to life-extension, HYT values survival gains at full health (1.0) and incorporates post-survival quality of life improvements, GRA-QALY adjusts risk preferences and disease severity. Willingness-to-pay (WTP) thresholds were $150,000 per QALY and per evLYG, corresponding to a WTP threshold of $89,000 per HYT and $122,107 per GRA-QALY.
RESULTS: The incremental health benefits of osimertinib (vs. placebo) were 0.71 QALYs, corresponding to 0.84 evLYG, 1.03 HYT gained and 0.86 GRA-QALY gained. The incremental costs associated with Osimertinib were $101,862 from a payer perspective, and $71,617 from a societal perspective. From a payer perspective, the incremental cost-effectiveness ratio (ICER) for osimertinib was $144,160/QALY, $120,690/evLYG, $98,548/HYT, and $118,054/GRA-QALY. When considering the societal perspective, which includes productivity and caregiver impact, the ICERs improved to $101,355/QALY, $84,853/evLYG, $69,287/HYT, and $83,001/GRA-QALY.
CONCLUSIONS: Compared to placebo, adjuvant osimertinib is cost-effective using various health benefit measures in completely resected EGFR mutated NSCLC elderly patients.
A Health Technology Assessment Framework for Ethics Analysis in Drug Reimbursement Reviews at Canada's Drug Agency
OBJECTIVES: In order to address the ethical complexities of certain drugs submitted for reimbursement review at Canada’s Drug Agency (CDA-AMC), we developed a comprehensive framework for the assessment of the ethical dimensions of drug products. This Health Technology Assessment framework is intended to recognize the embedded nature of ethical considerations, and identify relevant elements for decision-making.
METHODS: We developed a series of guiding questions identified from the EUnetHTA Core Model 3.0, Ethics Domain, and Benkhalti et al’s 2021 Equity Checklist for Health Technology Assessment. These questions or prompts were divided into four analytic domains covering ethical considerations across the technology and drug reimbursement lifecycle and adapted to the specific context of each review. The framework addresses ethical considerations in:
- Disease context, including considerations related to disparities in incidence, treatment, or outcomes; challenges or burdens related to diagnosis or clinical care; factors that might prevent patients from gaining access to therapies;
- The evidence used to evaluate the drug product, including the representativeness of clinical trials, the appropriateness of outcome measures and analytical methods used, data or assumptions in the economic evaluation;
- Clinical use and implementation, including considerations related to benefits and harms to patients, relatives, caregivers, clinicians, and society, as well as considerations related to access to the drug;
- Health system impact, including considerations related to the just distribution of healthcare resources.
RESULTS: This framework has been applied to 31 CDA-AMC drug reimbursement reviews as of December 2024. Modified versions of this approach are being trialed and implemented across an increasing number of review types. Alongside clinical and economic evaluations, the ethics report is used as one of the inputs to inform deliberative committees and other decision-makers.
CONCLUSIONS: This framework offers a consistent and transparent way to highlight ethical considerations for drug products under review at CDA-AMC.
A Policy Framework for Multi-Indication Evidence Synthesis in Oncology Health Technology Assessment (HTA)
OBJECTIVES: Health Technology Assessment (HTA) typically disregards evidence of a treatment’s effect on other indications, even when relevant, leading to high uncertainty. This study introduces a novel framework to guide HTA in appropriately considering multi-indication evidence to improve decisions and reduce uncertainty.
METHODS: The framework addresses key elements of multi-indication evidence synthesis, including selection of appropriate methods and incorporation of expert judgements. It builds on recent research, including an application to bevacizumab in oncology and a simulation study examining the performance of alternative methods. The framework quantifies cost-effectiveness impacts for two of bevacizumab’s appraisals.
RESULTS: Multi-indication evidence synthesis can improve decision making by increasing precision while generating unbiased and calibrated estimates. Important precision gains were shown in bevacizumab’s case study, even in early indications. For example, even the weaker hierarchical methods yielded an Overall Survival (OS) hazard ratio in breast cancer of 0.88 (95% credible interval: 0.78, 0.98), compared to 0.89 (0.73, 1.04) using only target indication evidence alone, leading to a reduction in decision uncertainty.
Under heterogeneity, where strong sharing assumptions may not hold, the sparseness typical of HTA data structures (few studies per indication and few indications overall) limits the applicability of complex methods like mixture or surrogacy models. While hierarchical models can still provide unbiased estimates in such cases, precision gains may be low making the burden of evidence identification and analyses potentially unjustified.
The framework further outlines when and how to share, what to share on (whether OS or surrogacy) and how to gather and incorporate clinical judgement.
CONCLUSIONS: Sharing information from plausibly related indications can strengthen HTA decisions. This framework defines a structured approach to integrating multi-indication evidence into HTA decision making.
How Can We Make Innovative Payment and Pricing Schemes Work? Findings of the European Union Research Project HI-PRIX
OBJECTIVES: Innovative payment schemes have been widely proposed as a solution for dealing with uncertainties, in cost and outcomes, associated with the introduction of new health technologies. However, payers’ and manufacturers' experiences with these schemes are mixed. This research explores how to increase the success of these schemes
METHODS: A work package of the Health Innovation Next Generation Payment and Pricing Models (HI-PRIX) project has obtained new evidence on the design and implementation of these schemes by (i) undertaking a scoping review and classification of existing schemes, supplemented by interviews with national experts to identify schemes not in the published or grey literature, (ii) conducting a Delphi exercise with the key stakeholder groups involved in these schemes (payers, patient representatives, technology manufacturers and healthcare decision-makers), to identify the barriers and facilitators to developing schemes (iii) undertaking case studies of several key technologies.
RESULTS: Around 200 innovative pricing schemes/applications have been identified, across a broad range technologies, including financed-based and outcomes-based schemes, from 19 countries. In addition, a 21-item classification has been developed to enable policy makers to search for schemes meeting specific objectives, or having particular characteristics. Analysis of the database of schemes, the Pay-for-Innovation Observatory (hiprixhorizon.eu), and feedback from stakeholders suggests that is possible to determine schemes with certain characteristics that are more likely to be successful when applied to certain types of technologies (eg cell and gene therapies, rare disease treatments, medical devices), or designed to meet particular objectives, including equity-enhancing purposes.
CONCLUSIONS: Despite the challenges, innovative payment and pricing schemes still represent one of the best approaches for facilitating the cost-effective introduction of new technologies under uncertainty. If policy makers can be assisted in selecting the best schemes to meet their particular objectives, and are better informed of the main barriers and facilitators, the success rate of these schemes will increase.
Alternative Recruitment Options for Patient Preference Studies: Thinking Outside the Market Research Panel Box
Session Type: Other Breakout Session
Topics: Patient-Centered Research, Methodological & Statistical Research, Study Approaches
Level: Intermediate
PURPOSE: This session will discuss opportunities and challenges to recruiting patient preference study participants in alternative ways to ensure a high-quality sample in a fit-for-purpose study. DESCRIPTION: Patient preference studies were historically used in market research and post-launch settings. Online market research panels provide a source of cost-effective and time-efficient recruitment for preference studies; however, these widely used online panels incur barriers such as difficulty obtaining medical information and physician-confirmed diagnoses, and potentially lower data quality (e.g., speeding, bot, etc.). As patient preference studies are increasingly used earlier in the medical product development lifecycle for industry, regulatory, and payer decision-making, recruitment and data quality are coming under increased scrutiny from health authorities. Preference researchers increasingly seek to gather confirmation of diagnoses and other medical information, ensure data quality, and recruit more narrowly-defined and/or more representative samples. This raises questions about what alternatives exist to online market research panels and how to design the most adequate recruitment approach. The session will start with introducing different modes of recruitment, including examples from regulatory on collecting a robust sample for a fit-for-purpose preference study (8 minutes, Bozzi). Then, a case example regarding a real-world evidence registry for patients with Irritable Bowel Disease will be shown (14 minutes, Johnson). The panel will continue with examples of partnering with patient advocacy organizations to recruit study samples (14 minutes, Poulos). Afterwards, there will be detailed discussions about considerations for recruitment from a clinical trial for a regulatory patient preference study (14 minutes, Heidenreich). Lastly, an interactive discussion with audience participation on potential barriers for a fit-for-purpose study and questions on different recruitment options (10 minutes).
Moderator
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Laura M Bozzi, MS, PhD
Janssen, Raritan, NJ, United States
Speakers
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Reed Johnson, PhD
Duke Clinical Research Institute, Durham, NC, United States
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Sebastian Heidenreich, BSc, MSc, PhD
Evidera, London, United Kingdom
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Christine Poulos, PhD
RTI Health Solutions, Research Triangle Park, NC, United States
Navigating Complexities in Calculating Therapeutic Alternative Starting Points in CMS Data
Session Type: Issue Panel
Topics: Health Policy & Regulatory
Level: Intermediate
ISSUE: This panel addresses the complexities of interpreting CMS claims data for drug price negotiations under the Inflation Reduction Act, particularly across unique characteristics of classes of products (e.g., chronic vs. acute, Part B vs. Part D, biomarkers and lines of therapy embedded in indications, and combination and regimen use) and the impact on equivalent comparison to therapeutic alternatives . Particularly, panelists will explore the challenges posed by structures and differences in Part B and Part D claims data for identifying and assigning diagnosis, billing units, and days supply. The discussion will focus on challenges and innovative approaches to issues such as estimating days supply for Part B, interpreting therapeutic use of Part D alternatives without claim level diagnosis data, and handling regimen and combination use. Insights will aim to enhance data transparency and accuracy, promoting equitable drug pricing decisions. OVERVIEW: The session will open with a 10-minute overview by moderator Milena Sullivan, who will detail the concerns and implications of how CMS calculates 30-day drug prices, particularly in the context of the structural differences between Part B and Part D claims data and implications for negotiated product manufacturers. This introduction will frame the key challenges, and their impact on CMS negotiation analysis, including negotiated product benchmarks and value comparison to therapeutic alternatives. Following the overview, the moderator will engage the panelists with targeted questions addressing both technical and practical aspects of these challenges. Discussions will explore methodologies for addressing key uncertainties in methodology presented by CMS guidance and availability of information in claims data. The session will also examine the implications for manufacturers navigating CMS pricing processes and strategies for improving data accuracy to support equitable and informed pricing decisions.
Moderator
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Sarah Moselle, MA, MPH
Avalere, Washington, DC, United States
Speakers
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Shanthy Krishnarajah, MPH, MBA/MS,PhD
Johnson and Johnson, New Hope, PA, United States
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Neil Lund, BS
Avalere Health, Washington, DC, United States
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Jordan T Banks, BS, MPP, PhD
Avalere Health, Canoga Park, CA, United States
8:30 AM - 10:00 AM
Networking Breakfast Bites
Session Type: General Meeting
Join us for Networking Breakfast Bites, designed to kickstart the final day of ISPOR 2025, with light refreshments and valuable networking opportunities.
8:30 AM - 11:30 AM
Poster Viewing & Exhibit Hall Hours
Session Type: General Meeting
9:00 AM - 11:30 AM
Poster Session 5
Session Type: Research Posters
9:15 AM - 9:45 AM
The Need for Data Never Ends: A Conversation About Meeting the Requirements of Post-Approval Safety Studies
Session Type: Exhibit Hall Theaters
Topics: Real World Data & Information Systems, Health Policy & Regulatory, Health Service Delivery & Process of Care
Level: Intermediate
10:00 AM - 11:00 AM
Advancing Accuracy and Transparency in Health Economic Evaluation
Session Type: Research Podiums
This session includes of topics related to the accurate and transparent development and interpretation of economic analyses. Topics presented will cover estimation of transition probabilities from aggregate data, synthesis of utility values, interpretation of published cost-effectiveness ratios, and artificial intelligence-assisted model replication.
Application of Bayesian Meta-Analysis in Synthesizing Health State Utility Values for QALY Estimation in Health Economic Evaluations: A Case Study on Advanced Neuroendocrine Tumors
OBJECTIVES: Health state utility values (HSUVs) are crucial inputs in economic models. Multiple HSUVs from different studies often exist and a single study may not represent the best available evidence to inform policy decisions. We utilized a Bayesian meta-analysis (BMA) framework in synthesizing HSUVs aiming to provide unified estimates for both pre-progression (PFS) and post-progression (PPS) in patients with neuroendocrine tumors (NET).
METHODS: An existing systematic literature review was utilized to identify HSUVs and its measure of variance for PFS and PPS. A BMA was conducted using ‘brms’ package. Missing variances were imputed using ‘mice’ package. We used flat priors on the mean HSUVs and a half-Cauchy prior on between-study-variance. Adequacy of priors was evaluated using ‘pp-check’ function. Model convergence was assessed through ‘rhat’, a value greater than 1.1 indicating non-convergence. Sensitivity analyses were conducted using complete case and the frequentist framework.
RESULTS: Of the identified studies, 11 reported HSUVs for PFS and six for PPS. One study did not report the measure of variance. The EuroQol-5D (EQ-5D) was the most common instrument, though dimensions (3L or 5L) were often unspecified. Pooled HSUVs from BMA were 0.74 (95% credible interval [CrI]: 0.68-0.78) for PFS and 0.70 (95%CrI: 0.60-0.79) for PPS, with no notable heterogeneity (tau <0.5 for both health states). Sensitivity analyses showed comparable results for the complete case analysis (PFS: 0.77; PPS: 0.73) and the frequentist analysis (PFS: 0.78; PPS: 0.72).
CONCLUSIONS: This study provided a methodological framework to generate unified HSUV estimates for health economic evaluations. BMA accounts for confounding in the estimates and offers flexibility in adding external information from real-world studies, reducing the need of multiple sensitivity analyses in estimating the quality-adjusted life years. This approach can be valuable for policy makers by providing consistent and robust inputs for decision-making.
Feasibility of Replicating a Published Health Economic Model From an ICER Report Using Generative AI
OBJECTIVES: Generative AI has a potential to automate complex tasks, including health economic modeling. This study aimed to evaluate the feasibility and accuracy of replicating a previously published health economic model using generative AI for Alzheimer’s disease, using the Institute for Clinical and Economic Review (ICER) report as a benchmark.
METHODS: We replicated a Markov model for Alzheimer’s disease from the report using ValueGen.AI, a GPT-4-based platform with multi-agent pipelines (CrewAI, LangChain, and OpenAI libraries). Python facilitated large language model interactions, and the extracted parameters were implemented in the Heemod package in R to construct and run the Markov model, comparing Lecanemab+supportive-care against supportive-care-alone. To validate the AI-based model, we compared delta costs, delta QALYs, and incremental-cost-effectiveness-ratio and calculated error margins for these outcomes.
RESULTS: The Generative AI platform extracted health states and transition probabilities from the report but faced challenges with baseline health state distribution, requiring manual implementation in the R code. The lack of detailed age distribution data necessitated using only the mean age, limiting the accuracy of age-related adjustments. General population costs were not explicitly reported, and the absence of cited references restricted AI’s extraction capabilities and human involvement. Despite these limitations, the AI-based model estimated the incremental-cost-effectiveness-ratio for Lecanemab+supportive-care versus supportive-care-alone at $279,637, compared to $254,000 in the report, with a 10.1% error margin. The delta cost and delta QALY error margins were 4.6% ($120,244 vs. $126,000) and 14% (0.43 vs. 0.50), respectively.
CONCLUSIONS: This study demonstrates the feasibility of using Generative AI to replicate complex health economic models. While it showcases Generative AI's ability to approximate key outcomes, it also highlights the dependency on the clarity and completeness of model inputs,, emphasizing the need for standardized reporting in HEOR. Future research should replicate more decision-analytic models to validate and refine this approach.
Frequency of ICER Miscalculation and Misinterpretation in Published Cost-Effectiveness Analysis Comparing More Than Two Alternatives
OBJECTIVES: Incremental Cost Effectiveness Ratios (ICERs) are used in Cost-Effectiveness Analyses (CEAs). With two interventions, the calculation is straightforward, but is less obvious with additional interventions. We sought to determine the frequency and type of ICER miscalculation/misinterpretation in published CEAs comparing more than two alternatives.
METHODS: A PubMed search identified CEAs published in 2017. Article titles and abstracts were screened by at least two reviewers and excluded if they compared only two interventions, were not a CEA, or lacked an abstract. Remaining articles were reviewed in full-text by two reviewers using a sequential protocol to identify errors in ICER calculation/interpretation. Errors assessed, in order, were: 1) calculating average cost-effectiveness ratios (ACERs), 2) calculating ICERs comparing all alternatives to a common one, 3) calculating ICERs combining multiple disease states or other overlapping populations, 4) failing to provide a willingness-to-pay (WTP) value in deciding cost-effectiveness, 5) misapplying the WTP, and 6) making other ICER calculation/interpretation errors. Only the first error identified in this sequence was recorded. If none were found, the article was coded as correct.
RESULTS: Our search identified 815 publications. After exclusions, 132 articles were reviewed and 62% (82) contained an error. Of these 132 articles, 35.6% compared all interventions to a single comparator; 15.9% used ACERs. Failing to include, or misapplying, a WTP were less common (3.8% each) as were ICER calculations using overlapping populations or other errors in mathematical or dominance calculations (1.5% each).
CONCLUSIONS: Publications using incorrect economic methods may have implications for health system efficiencies. Our findings likely underestimate total errors in the CEA literature because our protocol focused exclusively on ICER calculation and interpretation. The high frequency of error may cast doubt on the usefulness of CEAs for healthcare decision-making and should be addressed so that they have the requisite integrity to inform decisions.
A Bayesian State-Transition Model-Based Approach to Estimate Transition Rates From Aggregated Survival Data
OBJECTIVES: Typically, trial publications only provide aggregated overall survival (OS) and progression-free survival (PFS) rates, and no access to IPD. We developed a state-transition model (STM)-based approach to estimate the rates of progression and progression-specific mortality from aggregate clinical trial survival data using Bayesian calibration methods.
METHODS: We developed a four-state, time-dependent STM specified in continuous-time tosimulate a hypothetical cohort of progression-free (PF) patients in discrete time. Individuals in the model face a progression rate that follows a Weibull distribution as a function of age. Those who progress (P) face a time-constant excess progression-specific mortality rate. Individuals in the PF and P states are also at risk of age-, and sex-specific mortality from other causes. The model derives the time-dependent transition probability matrix by solving the Kolmogorov equations. We estimated the shape and scale of the Weibull hazard dictating the cancer progression and the exponential cancer progression rates by calibrating the STM to OS and PFS from a clinical trial of adjuvant chemotherapy for colon cancer using Bayesian methods. We used the Incremental Mixture Importance Sampling (IMIS) algorithm to draw a sample of 1,000 parameter sets from the posterior distribution.
RESULTS: The expected survival times from the trial’s data were 5.76 for the OS and 5.0 years for the PFS. The model estimated survival times were 5.85 [95% Credible Interval (CrI): 5.64-6.06] years for OS and 5.01 [95% CrI: 4.75-5.25] for PFS. The time-dependent progression rate decreased over time, with estimated scale and shape parameters of the Weibull hazard of 1.50 [95% CrI: 0.50-2.50] and 0.45 [95% CrI: 0.25-0.65], respectively. The estimated progression- specific mortality rate was 0.59 [95% CrI: 0.42-0.76].
CONCLUSIONS: Our method estimates rates of disease progression and progression-specific mortality from aggregated survival data in the absence of IPD. This method can be adapted to STMs with similar structures.
Fit-for-Purpose Real-World Data for Medical Device Decision Making: Hype or Hope?
Session Type: Issue Panel
Topics: Medical Technologies, Study Approaches, Organizational Practices
Level: Intermediate
ISSUE: Real-world evidence (RWE) is increasingly evaluated for regulatory and reimbursement decisions regarding medical devices. While numerous RWE guidance documents have been published, what constitutes “fit-for-purpose (FFP)” or “fitness for use” of real-world data (RWD) in generating RWE to inform decisions remains uncertain. Moreover, most guidance fails to differentiate between RWE for pharmaceuticals and devices. There are differences in what can be observed between pharmaceuticals and devices in RWD and in the decision making due to varying regulatory pathways and benefit\risk and value assessments. There are also differences in ability to demonstrate data is FFP by device type and data source. Often, devices are only identifiable at a class level in claims data; clinical information may be missing even within EHRs; privacy considerations may limit data validation. However, these data are valuable for RWE generation for numerous reasons like sample size and follow-up duration. This session will compare regulator, HTA, and US payers’ perspectives on demonstrating secondary RWD are FFP for regulatory and payer decision-making for devices. OVERVIEW: The moderator will summarize the issue and provide an overview of secondary RWD for devices. (8 mins) Each panelist will present their perspective on the use of secondary RWD and discuss how study designs and analytical methods offer solutions to challenges posed by secondary RWD, including machine learning and natural language processing; data linking that maintains deidentification; and identification strategies leveraging institutional context. They will also offer perspectives of regulators, HTAs, and payers to these proposed solutions and recommend analysis planning and design approaches and future directions for methods research and data curation that could help increase acceptance of medical device RWE. (42 mins) The remainder of the session will be reserved for audience questions. (10 mins)
Moderator
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Eric Barrette, MA, PhD
Medtronic, Washington, DC, United States
Speakers
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Farah Husein, BSc, MSc, PharmD
CDA-AMC, Toronto, ON, Canada
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Ami Buikema, MPH
Optum, Eden Prairie, MN, United States
Global Guidance for Evidence-Based Value Assessment of Innovative Health Technologies: Feasible Reality or Idealistic Dream?
Session Type: Issue Panel
Topics: Health Technology Assessment, Health Policy & Regulatory, Economic Evaluation
Level: Intermediate
Innovative technologies—such as cell and gene therapies, molecular diagnostics, and targeted treatments— harbour the potential to change patient lives and bring substantial benefits to health systems. Assessing and accurately measuring their value for patients, health systems, and society at large is critical. However, health technology assessment bodies face challenges in incorporating evaluation criteria and methodologies that capture extended sets of potential value drivers, such as those found in the ISPOR Value Flower and the Generalized Cost-Effectiveness Analysis (GCEA) framework. This session will debate if these novel value drivers are a feasible and indeed ethical solution for assessing innovative health technologies, and whether global guidance for their incorporation can be a pathway to strengthen value assessments for future-proof health systems.
Moderator
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Lidewij Vat, PhD
The Synergist, Brussels, Belgium
Speakers
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Alan Balch, MS, PhD
Patient Advocate Foundation and National Patient Advocate Foundation, Hampton, VA, United States
Dr. Balch has more than 20 years of executive leadership in the non-profit sector spanning multiple advocacy areas including access and affordability, health equity, prevention and early detection, and cancer research, He became the CEO of both PAF and NPAF in 2013 and has served as a member of both Boards of Directors since 2007. From 2006-2013, he served as Vice President of the Preventive Health Partnership -- a national health promotion collaboration between the American Cancer Society, American Diabetes Association, and American Heart Association. Prior to his work with the Preventive Health Partnership, Dr. Balch was the Executive Director of Friends of Cancer Research from 2003 to 2006.
Dr. Balch currently serves or recently served on dozens of selective boards, steering committees, and councils for an array of institutions to include the National Academies of Medicine, the National Quality Forum (NQF), National Committee for Quality Assurance (NCQA), the Institute for Clinical and Economic Review (ICER), the Clinical Pathways Congress, the Council for Affordable Health Coverage (CAHC), the Innovation and Value Initiative (IVI), Core Quality Measure Collaborative (CQMC), the Foundation for the Accreditation of Cellular Therapy (FACT), the Hutchinson Institute for Cancer Outcomes Research (HICOR), the Duke-Margolis Value-Based Payment Consortium, the Specialty Pharmacy Certification Board (SPCB), and the Pharmacy Quality Alliance (PQA). Most recently, Dr. Balch was selected as the Chair of the Global Patient Council for the American Patient Representatives Roundtable for the Professional Society for Health Economics and Outcomes Research (ISPOR) after serving as the Co-Chair of the North American Patient Representatives Roundtable.
Dr. Balch also serves on the editorial board and as a contributing editor for the Journal of Clinical Pathways and on the advisory board for the Journal of Oncology Navigation and Survivorship. He is frequently invited to peer review article submissions to various publications including the Journal of Health Care for the Poor and Underserved, Journal of Clinical Oncology, American Journal of Preventive Medicine, and the American Journal of Public Health.
He earned his PhD in 2003 from the University of California Santa Cruz, his master’s degree in 1997 from the University of Texas San Antonio; and his bachelor’s degree in 1994 from Trinity University in San Antonio.
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Marina Richardson
ICER, Boston, MA, United States
Marina Richardson is an associate director, Health Technology Methods and Health Economics with the Institute for Clinical and Economic Review (ICER). In her role, Marina leads and oversees the development of economic models to inform pricing and reimbursement decision-making and identifies and executes opportunities to enhance ICER's methodology and processes within Health Technology Assessment (HTA) and Health Economics. Prior to joining ICER, Marina led and contributed to reimbursement review reports and recommendations at Canada's Drug Agency (CDA-AMC), formerly CADTH. Marina has a PhD in Health Services Research from the University of Toronto and is an active contributor to the field including as a deputy editor for the International Journal of Technology Assessment in Health Care (IJTAHC), a member of the Ontario Immunization Advisory Committee (OIAC) in Ontario, Canada, and as a co-chair of the International Scientific Program Committee for Health Technology Assessment International (HTAi) 2025.
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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.”
Drug Shortages in Focus: Strategies and Policies for Sustainable Solutions
Session Type: Issue Panel
Topics: Health Policy & Regulatory, Health Service Delivery & Process of Care, Organizational Practices
Level: Introductory
ISSUE: Drug shortages are a critical issue impacting every facet of healthcare systems worldwide. In Canada, where their reporting is mandatory, one in four people are estimated to have personally experienced a drug shortage or know someone who has in the last two years. Drug shortages impact drugs of all indications, formulations, companies, and generic status, and have been found to harm patients and lead to premature death. While immediate causes of shortages are mostly related to disruptions along the supply chain of drugs, the resilience of supply chains can be impacted by factors such as regulation, economic incentives, geopolitical issues, natural disasters, and pandemics. Given the globalized pharmaceutical distribution system and the shrinking manufacturing capacity in most countries, actionable solutions to curb this problem are needed immediately. This session will clarify the underlying issues leading to drug shortages globally and highlight effective policies and interventions to mitigate them. OVERVIEW: Dr. Mina Tadrous will moderate the session and provide a 12-minute introduction of the problem from the North American and global perspectives. Dr. Tadrous will discuss examples of drug shortages and their international impact, highlighting why shortages are an important problem. Panelists will follow with 8-minute presentations. Dr. Étienne Gaudette will show current evidence on Canadian drug shortages and concentration in international generic drug markets, followed by policy solutions focusing on pricing and competition approaches. Dr. Katie Suda will explore underlying causes for drug shortage through the lens of a supply and demand framework and will share ongoing work to help understand characteristics of drugs at the greatest risk of shortage. Ms. Stephanie Di Trapani will discuss ongoing initiatives and regulatory work led by the Health Product Shortages Directorate of Health Canada. The session will conclude with a Q&A from panel members.
Moderator
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Mina Tadrous, MS, PharmD, PhD
University of Toronto, Toronto, ON, Canada
Speakers
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Etienne Gaudette
PMPRB, Ottawa, ON, Canada
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Katie Suda
University of Pittsburgh, Pittsburgh, PA, United States
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Stephanie Di Trapani, BSc
Health Canada, Ottawa, ON, Canada
Advancing the Definition and Reporting of Digital Health Interventions: From PICOTS-ComTeC to CHEERS-DHI
Session Type: Other Breakout Session
Topics: Medical Technologies, Study Approaches, Economic Evaluation
Level: Intermediate
PURPOSE: This breakout session introduces key tools, including PICOTS-ComTeC and CHEERS-DHI, designed to aid HEOR and HTA experts in evaluating Digital Health Interventions (DHIs) across various stages. The session focuses on bridging theory and practice through case studies and open discussions, demonstrating how these tools can support the development of comprehensive Health Technology Assessments (HTAs).
DESCRIPTION: In this session, the ISPOR Digital Health SIG will provide an overview of their recent work in advancing digital health definitions and health economic reporting. The focus will then shift to the introduction and application of the PICOTS-ComTeC framework for defining patient-facing DHIs. Real cases will be shared to show how it can be easily implemented. The PICOTS-ComTeC framework is then compared to other established DHI frameworks and guidelines with the aim to evaluate the degree of overlap, identify the unique contributions of PICOTS-ComTeC, and explore how these frameworks can complement one another in practical application. As the next step, the CHEERS-DHI project—aimed at extending the CHEERS reporting guideline for economic evaluations to address the unique challenges of DHI assessments —will be presented to facilitate dissemination and gather feedback.
In conclusion, an overview of the current HTA landscape will be provided by a representative from the EU-funded EDiHTA project (The European Digital Health Technology Assessment Framework).
The audience will actively participate through Q&A sessions and polls, with the opportunity to engage in the final discussion. This will allow them to share their experiences, provide feedback on the proposed CHEERS-DHI guidance.
Moderator
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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.
Speakers
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Rossella Di Bidino, MSc, PhD
Gemelli Teaching Hospital, Roma, Italy
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Don Husereau, BSc, MSc
University of Ottawa, Ottawa, ON, Canada
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Annette Champion, BSc, MBA
Healthcare Research Insights, Inc, Lake Forest, IL, United States
Health Policies and Process of Care: Examples from Europe, USA, and Canada
Session Type: Research Podiums
This session will explore the evolving landscape of health policies and processes of care across Europe, the United States, and Canada. Speakers will examine initiatives influencing drug approval, pricing, and reimbursement. Additionally, the session will highlight the increasing role of real-world evidence (RWE) in decision-making. Attendees will gain a deeper understanding of the opportunities and challenges in aligning health policies with patient needs within public and private healthcare frameworks.
Impact of JCA and Project Orbis on the European Revenue Potential of an Oncology Product
OBJECTIVES: To estimate the 5-year revenue impact that Joint Clinical Assessment (JCA) and Project Orbis may have on a new oncology product across the EU27 states (excluding Malta), Norway, Switzerland, and the United Kingdom (UK).
METHODS: Comparison of launch scenarios for a new oncology product to evaluate the potential impacts of JCA and Project Orbis against a base-case scenario. This base-case scenario is based on an analysis of the time-to-market and revenue potential of 48 oncology products launched between 2019 and 2022. Time to availability was determined by calculating the days between marketing authorization and product availability to patients in each market. Revenue potentials were estimated considering list prices, market size, pharmaceutical expenditure, and formal/informal international reference pricing (IRP) rules. The launch scenarios were developed considering the potential impact of JCA and Project Orbis on time-to-market availability. The corresponding revenue impacts were calculated for each launch scenario and compared against the base-case scenario.
RESULTS: In the best-case scenario, the time-to-market was accelerated by up to 40% due to the JCA. Conversely, in markets that typically submit immediately after receiving a positive Committee for Medicinal Products for Human Use (CHMP) opinion, the time-to-market was delayed by up to 3 months. Due to Project Orbis, the time-to-market was accelerated by up to 7 months for Switzerland and the UK. Although a faster erosion of list prices due to international reference pricing (IRP) was observed, the impact on total revenue appears minor over a 5-year period. A revenue sensitivity analysis across scenarios indicated a potential revenue increase of up to 14%.
CONCLUSIONS: Our analysis indicates that JCA and Project Orbis may present an opportunity for manufacturers to achieve higher revenues for new oncology products. Overall, the risk of faster price erosion is counterbalanced by the increased sales volume over a 5-year period.
Balancing Innovation and Affordability: Analyzing the Cost of Drugs for Rare Diseases in Canada
OBJECTIVES: As drug for rare diseases (DRDs) have become a growing focus of pharmaceutical development, their high costs pose significant challenges to healthcare budgets. This research aims to characterize key drivers influencing the feasibility and timing of adoption for DRDs in Canadian public reimbursement. We seek to determine whether rarity of conditions, competition, and potential benefits influences acceptability of DRDs’ substantial price tags, ultimately informing policy decisions that balance innovation, affordability, and equitable access.
METHODS: We extracted non-oncology DRDs designated as ‘orphan’ per the Orphanet portal with Canadian Drug Agency (CDA) recommendations between 2021 and 2024. DRDs were categorized as (1) rare or ultra-rare based on disease prevalence of 0.001%, and (2) first or subsequent entrant for the condition in Canada. Our internal market intelligence tool was used to gather CDA, pan-Canadian negotiation data, estimated three-year budget impact analyses (BIAs), quality-adjusted life years (QALYs), eligible patient numbers, and annual list price per-patient cost. We examined trends by disease prevalence and entry order and assessed timelines using the Kaplan-Meier method.
RESULTS: CDA reviewed 153 non-oncology drugs between 2021 and 2024, with 57 (37%) targeting DRDs, including 13 for ultra-rare indications and 21 as first entrants. The majority (51/57) received positive recommendations. Three-year projected BIAs at list prices ranged from cost savings of $49M to an added impact of $2.6B. Rare DRDs showed a higher median BIA ($52M) than ultra-rare DRDs ($25M). First entrant DRDs had a higher median BIA ($65M) than subsequent entrants ($29M), and required longer median time to complete negotiations (245 vs 147 days, p=0.0024).
CONCLUSIONS: While most DRDs have received positive reimbursement recommendations and completed pan-Canadian price negotiations, significant differences in their characteristics affect feasibility and timing of adoption. Novel, first entrant DRDs with high prices pose additional challenges for implementation and overall affordability within the healthcare system.
Implementation of the IRA: Evolving Perspectives from US Stakeholders
OBJECTIVES: In August 2022, the Inflation Reduction Act (IRA) was signed into law with provisions to improve Medicare through cost containment measures. These measures include mandatory negotiations for top selling Medicare drugs, Medicare beneficiary annual out of pocket cap over $2,000, and manufacturer penalty rebates if therapy prices are increased at a steeper rate than inflation.
On August 15, 2024, CMS released the results of the first round of negotiated prices for the IRA involving 10 Medicare Part D branded drugs which raised questions around future negotiations and how they may impact drug pricing strategies moving forward.
METHODS: This study presents the results of primary research from N=8 US payer stakeholders that provide current perceptions of the IRA and its potential impact on the pharmaceutical landscape. By exploring stakeholder concerns and expectations, this research identifies emerging trends and raises key questions around the evolving pharmaceutical landscape resulting from the CMS negotiations.
RESULTS: The first batch of CMS negotiations have yielded modest drug price cuts, primarily due to existing substantial rebates on the selected products. While expected, these outcomes highlight uncertainties surrounding future negotiation rounds. Payers emphasize the economic burden of IRA changes as a key concern (e.g., plan contribution for OOPs above the $2K cap). Uncertainties cited include which therapeutic areas will be impacted, whether manufacturers are expected to adapt life cycle management strategies (e.g., reformulating products to delay negotiations), and how payer dynamics may shift in response to these changes.
CONCLUSIONS: The broader impact of the IRA on Medicare and CMS negotiations is becoming clearer, though there remains ambiguity around how the pharmaceutical industry will respond. The impact of the IRA on the commercial sector remains uncertain, with stakeholders debating whether Medicare-focused policies will drive broader systemic changes or further exacerbate pricing challenges seen in healthcare.
Characteristics of RWE used in Regulatory Decision-Making for Marketing Authorization Applications (MAAs)
OBJECTIVES: Real-world evidence (RWE) is increasingly used to support regulatory decision-making. Numerous regulatory agencies including the FDA and EMA have issued guidance on evaluating RWE in MAAs, yet trends in its application in MAAs are not well characterized.
METHODS: We examined trends in RWE use and regulatory feedback on drug submissions containing RWE in MAAs from January 2021 to present, focusing on therapeutic areas, type of RWE, and common practices in submissions. Publicly available documents were extracted and reviewed. Two independent reviewers extracted and categorized the RWE. Descriptive analyses were performed to identify trends in the characteristics of drugs and of the RWE.
RESULTS: Seven medicines were analyzed: idecabtagene vicleucel (ide-cel), omburtamab, sotorasib, alpelisib, palovarotene, tacrolimus, and omaveloxolone. All medicines (100%) were orphan or ultra-orphan drugs. Three of the seven drugs (42.8%) were for oncology or hematology while the remainder (57.1%) were indicated for rare diseases. In the US, 5/7 (57.1%) were first-in-class for the respective therapeutic areas, while 2/7 (28.6%) were for additional indications. The majority (6/7) had substantial RWE in the MAAs. Trends revealed varying levels of reliance on RWE, with 4/7 (57.1%) MAAs containing externally controlled arms using real-world data. Two of the four ECAs were accepted by the FDA, of which one was post-hoc and confirmatory. MAAs for expanded indications had heavier reliance on RWE. Five MAA reviews noted either sponsor submission of patient-level data or FDA reanalyzing or evaluating the patient-level RWD. A total of 2/7 (28.6%) reviews noted FDA audits or site inspections related to the RWE/RWD submitted.
CONCLUSIONS: MAAs containing RWE submitted to the FDA were predominantly for rare diseases medicines and for first-in-class indications. Acceptability of RWE varied based on entire body of evidence. Further investigation into factors influencing RWE acceptability and its integration into MAAs across other regulators such as EMA is warranted.
From MAR to SMART: Advanced Methods for Integrating Patient Preferences in Regulatory Science
Session Type: Workshop
Topics: Patient-Centered Research, Health Policy & Regulatory
Level: Advanced
PURPOSE: This workshop aims to equip participants with the skills to calculate and interpret maximum acceptable risk (MAR) and minimum acceptable benefit (MAB) estimates. By understanding these measures, attendees will enhance their ability to integrate patient-preference information into regulatory reviews. The workshop aligns with recent FDA guidance, which emphasizes evaluating health technologies based on patient risk tolerance to improve the assessment of treatment benefits and risks. DESCRIPION: MAR and MAB are widely used to quantify patients’ risk tolerance and provide critical insights into their perspectives on new treatments. However, these estimates are influenced by factors such as patients’ baseline risk, how risks are presented, and the inclusion of opt-out options. Extensions of MARs and MABs, such as simultaneous MAR thresholds (SMARTs), enable the evaluation of tolerance for multiple risks collectively, providing a more comprehensive assessment of real-world risk tolerance.During the workshop, participants will explore extensions of basic MAR and MAB calculations and learn how to integrate them into benefit-risk assessments. They will use an interactive online calculator to analyze how varying assumptions impact risk-tolerance measures. Through this tool, participants will generate MARs, MABs, and SMARTs across different scenarios and engage in guided discussions with presenters on applying these measures to real-world regulatory contexts.By the end of the workshop, attendees will be equipped to effectively incorporate patient-preference data into regulatory decision-making, aligning with FDA expectations.Dr. Janssen will introduce MARs/MABs and moderate a discussion on the need to extend these estimates under various scenarios. Dr. Gonzalez will show how to use SMARTs to assess multiple risks and guide attendees in generating SMARTs. Dr. Boeri will present compensating variation, an alternative method for calculating MAR that is useful when an opt-out option is present.
Moderator
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Ellen M Janssen, BA, PhD
Janssen Research & Development, LLC, Baltimore, MD, United States
Speakers
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Juan Marcos Gonzalez, PhD
Duke Clinical Research Institute, Cary, NC, United States
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Marco Boeri, BSc, MSc, PhD
OPEN Health, London, United Kingdom
Ensuring the Validity of Real-World Evidence Studies: How Much Can You Check the Data Before You Start?
Session Type: Workshop
Topics: Methodological & Statistical Research, Epidemiology & Public Health, Study Approaches
Level: Intermediate
PURPOSE: Pre-specification of analyses in real-world evidence (RWE) studies is challenging due to the uncertainty of the size, completeness, and other factors involved in the generation of such data. At the same time, RWE studies that aim at causal inference, in particular, require a robust statistical analysis plan, defined beforehand, for these studies to provide robust scientific evidence and support claims. Fixing the analysis plan without any knowledge of the data is similar to taking a shot in the dark. The task would become easier if we knew something about the data. The workshop aims to help answer the question, how much of the data can we check before finalizing the analysis plan? DESCRIPTION: Dr. Olson will introduce (5 min) the problem statement and the minimal sample size estimation of eligible patients that is typically conducted. Dr. Mittmann will highlight uncertainties related to data explorations in RWE when used to support decision-making and provide a few examples (10 min). Prof. Wang will then propose boundaries around the kind of data that can be checked and how (15 min). Dr. Karcher will work through an example with the audience with multiple possibilities of data checks (10 min), and the other panelists will chime in and comment on scientific and operational feasibility, as well as regulatory acceptance of the checks.The audience will ideally be composed of real-world evidence researchers, epidemiologists, and statisticians, as well as decision-makers and regulators using and auditing RWE studies. The panel will prompt them to comment, in the case examples shown, on the type of data checks they estimate to be performed before registering the protocol and finalizing the main analysis of an RWE study (use of polling system). Additionally, a discussion on future regulations concerning real-world data checks is scheduled for the end of the session (10 min).
Moderator
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Melvin Skip Olson, ScD
Olson Strategies GmbH, Allschwil, Switzerland
Speakers
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Nicole Mittmann, MSc, PhD
Canada's Drug Agency, Toronto, ON, Canada
In her Chief Scientist role, Dr. Mittmann is responsible for ensuring that CDA (a.ka. CADTH) actively learns, ensures rigour and quality, mobilizes evidence, and links science to strategy. In her Scientific Evidence, Methodologies and Resources role, Nicole leads CDA’s shared science groups, including the Science and Methods, Health Economics, Research Information Services, Publishing, Early Scientific Advice and Real-World Evidence teams.
In her academic capacity, Dr. Mittmann holds an MSc and PhD in pharmacology from the University of Toronto. She holds a faculty position as an assistant professor at the University of Toronto in the Department of Pharmacology & Toxicology; and is cross-appointed to the Institute for Health Policy, Management and Evaluation. She is also an associate scientist at Sunnybrook Health Sciences Centre in Toronto, Canada. Dr. Mittmann has conducted and collaborated on notable research in the areas of economic evaluations, outcomes research, and drug/patient safety. Research methodologies include the examination of large databases, economic methodologies, and decision analysis.
She likes to link, leverage and liberate data and evidence.
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Shirley Wang, PhD
Brigham & Women's Hospital, Harvard Medical School, Boston, MA, United States
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Helene Karcher, PhD
Novartis AG, Basel, Switzerland
Value Assessment Is No Longer Just for Payers: Debating How Provider Health Systems Can Leverage HEOR Methods to Inform Decision-Making Under Value-Based Care and Alternative Payment Models
Session Type: Issue Panel
Topics: Economic Evaluation, Health Service Delivery & Process of Care, Health Policy & Regulatory
Level: Introductory
ISSUE: Value-based care (VBC) ties provider reimbursement to patient outcomes, emphasizing cost efficiency, quality of care and health equity. As the Centers for Medicare & Medicaid Services aim to enroll 100% of Medicare beneficiaries and most Medicaid recipients in alternative payment models (APMs) by 2030, providers must increasingly optimize care not only for clinical outcomes but also “value”. This panel will debate the role of health economics and outcomes research (HEOR) in informing provider decision-making within APM and VBC frameworks. OVERVIEW: Dr. Jason Shafrin will moderate the panel, beginning with an overview of the VBC landscape and its intersections with health economics. Dr. Anna Flattau will provide the provider health system and clinician perspective, describing how value-based reimbursement is reshaping provider decision-making on the ground level. She will examine where HEOR methods are useful and where they may fall short in informing provider health systems. Kyi-Sin Than will explore how specific value-based payment arrangements influence provider revenue and quality metrics. She will describe how established HEOR methods can be readily adapted to align with provider priorities under VBC and share a case study example. The panelists will debate where HEOR methodologies can provide real utility to provider health systems across and how this HEOR-based analyses would (or would not) be useful across different APM structures and disease contexts, highlighting both opportunities and barriers to its adoption in provider-focused value assessments.
Moderator
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Jason Shafrin, PhD
FTI Consulting, Los Angeles, CA, United States
Speakers
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Anna Flattau, MD Msc MS FAAFP
Jefferson Health, Philadelphia, PA, United States
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Kyi-Sin Than, MPH
FTI Consulting Center for Healthcare Economics and Policy, Philadelphia, PA, United States
10:00 AM - 11:15 AM
Cost Benefit Analysis in Value Assessment: Spotlight on Methods
Session Type: Spotlight
This session will provide an update on cost-benefit analysis, particularly their use for monetizing health benefits and evaluating financial tradeoffs between investing in health versus other sectors. Distinguished leaders in cost benefit analysis will share their insights into the latest methodological advancements and their implications for health policy and economic assessments.
Moderator
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Nancy Devlin, PhD
University of Melbourne, Melbourne, Australia
Speakers
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Eberechukwu Onukwugha, MSc, PhD
University of Maryland, School of Pharmacy, Baltimore, MD, United States
Eberechukwu Onukwugha, PhD is a Professor in the Department of Practice, Sciences, and Health Outcomes Research and Executive Director of Pharmaceutical Research Computing at the University of Maryland School of Pharmacy. She received a Doctor of Philosophy in economics (concentration: econometrics) from Virginia Polytechnic Institute and State University (Virginia Tech). Dr. Onukwugha completed a two-year postdoctoral fellowship in pharmacoeconomics and health outcomes research at the University of Maryland School of Pharmacy. She was a recipient of the PhRMA Foundation’s Post-Doctoral Fellowship in health economics and outcomes research. Dr. Onukwugha’s research interests are in cost analysis, health disparities, and medical decision-making by individuals and institutions. She has approximately 20 years of experience conducting health economics and outcomes research using administrative medical and pharmacy claims, hospital discharge, and prospectively-collected data. Dr. Onukwugha has authored or co-authored over 140 peer-reviewed articles in health economics and outcomes research. She is an Editorial Board member for PharmacoEconomics and an Associate Editor for Ethnicity & Disease. Dr. Onukwugha serves as President, ISPOR Board of Directors, 2024-2025, and serves on the Maryland Prescription Drug Affordability Board.
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Robert J Brent, PhD
Fordham University, Bronx, NY, United States
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Thomas G Poder, PhD
University of Montreal, Montreal, QC, Canada
11:00 AM - 11:30 AM
Break (Exhibit Hall)
Session Type: General Meeting
11:30 AM - 12:45 PM
Closing Plenary Session
Session Type: Plenary
