About this Event
This webinar will examine how generative AI is reshaping core HTA methods that are especially relevant for an SMDM audience of decision scientists and clinicians. It will use practical examples to show how genAI can accelerate evidence synthesis, support health economic model conceptualization and coding, and inform HTA reports and guidelines, while critically assessing risks such as bias and hallucinations. The session will also present practical guardrails— including human-in-the-loop validation and alignment with emerging HTA and AI governance initiatives— to help decision scientists determine when to trust, verify, or reject AI-assisted outputs in medical decision making.
Faculty
Jagpreet Chhatwal, PhD, is the Director of the Center for Health Technology Assessment at Mass General Brigham and an Associate Professor at Harvard Medical School. He is also a core faculty member of the Center for Health Decision Science at Harvard T.H. Chan School of Public Health. He has co-authored over 140 research articles, and his work has been cited in leading media outlets, including NPR, Forbes, Wall Street Journal, and New York Times. His work has directly informed policy at the White House, the CDC, multiple state health departments, and the World Health Organization. Dr. Chhatwal received the inaugural 2025 ISPOR Impact Award, and 2026 John M. Eisenberg Award from the Society of Medical Decision Making, two prestigious recognitions honoring his multi-year contributions to hepatitis C elimination research in the United States. He co-led the ISPOR Task Force on the use of Generative AI for systematic literature reviews, which produced influential guidance on the use of large language models for evidence synthesis.