Podcast Episode
February 2, 2026
No items found.

47: A Visit with Michael Harhay

Play video
Scott Berry, Ph.D.
President & Senior Statistical Scientist
In this episode of "In the Interim…", Dr. Scott Berry speaks with Dr. Michael Harhay, Associate Professor at the University of Pennsylvania and Director of the Center for Clinical Trials Innovation.

In this episode of "In the Interim…", Dr. Scott Berry speaks with Dr. Michael Harhay, Associate Professor at the University of Pennsylvania and Director of the Center for Clinical Trials Innovation. The conversation explores Dr. Harhay’s progression through neuroscience, philosophy, epidemiology, and statistics, examining how this academic path shapes his work in clinical trial methodology. They discuss the Center’s role in addressing unresolved methodological questions arising from pragmatic, health system-based trials, including challenges with cluster and factorial randomized designs. The episode focuses on statistical and conceptual issues in endpoint selection for critical care, such as the analysis of informatively truncated outcomes, composite endpoints including organ support-free days, and the application of the win ratio. The increasing use of Bayesian methods in trial design is addressed.

Key Highlights

  • Dr. Harhay’s academic background and transition into clinical trial methodology at Penn.

  • The mission of the Center for Clinical Trials Innovation to support methodologic research and training, particularly among statisticians participating in multi-center health system trials.

  • Discussion of hospital-level and provider-level randomization strategies in cluster and factorial designs within health systems.

  • Ongoing challenges in analysis of composite and informatively truncated endpoints, especially in critical care, exemplified by ventilator-free and organ support-free days.

  • Evaluation of analytic strategies including survival average causal effect, composite endpoints, and the win ratio, with emphasis on the need for clinical rather than purely statistical weighting of outcomes.

  • Consideration of the conceptual strengths of Bayesian methods and their integration into modern trial design and decision analysis.

Download PDF
View