HEOR at US Federal Agencies: State of the Science
Speakers
Peter Neumann, ScD, Tufts Medical Center, Boston, MA, United States; Laura Pizzi, MPH, PharmD, ISPOR, Lawrenceville, NJ, United States; Donna Rivera, MSc, PharmD, Canal Row Advisors, Washington, DC, United States; Kakoli Roy, MA, PhD, CDC National Center for Chronic Disease Prevention and Health Promotion, Atlanta, GA, United States; Rachael Fleurence, MSc, PhD, Apodeixis Strategies, LLC, Boston, MA, United States
ISPOR stands firmly committed to advancing rigorous, transparent, and policy-relevant health economics and outcomes research (HEOR) and to strengthening its appropriate use across U.S. federal agencies. HEOR methods—including real-world evidence (RWE), pragmatic study designs, patient-centered evidence, and applied economic analysis—have matured rapidly and are increasingly visible in regulatory, public health, and coverage and payment contexts. Yet the pace and direction of HEOR integration varies across agencies, and external narratives often obscure how HEOR science is actually evolving within US federal institutions.
This session, co-moderated by Laura Pizzi, Chief Science Officer of ISPOR, and Peter J. Neumann, Chair-Elect of ISPOR’s Health Science & Policy Council, will convene senior experts representing diverse federal perspectives. Invited panelists include Donna Rivera (former FDA; real-world evidence and regulatory science), Kakoli Roy (Centers for Disease Control and Prevention; applied health economics), and Rachael Fleurence (former NIH, science policy and evidence governance).
Panelists will share their views about 1. what aspects of HEOR within the agencies are expanding, plateauing, or contracting; 2. where the greatest opportunities exist for HEOR researchers to contribute to high-quality, decision-relevant evidence through grant funding and/or job opportunities; and 3. how ISPOR can further support HEOR methods, workforce development, and effective evidence translation in these agencies.
Topic
Epidemiology & Public Health, Organizational Practices, Real World Data & Information Systems