#5-53E. Unmasking Causal Effects: A Clinician’s Guide to Difference-in-Differences (JAMA, 2026)

How can we reliably isolate the true causal impact of a new healthcare policy or hospital intervention when a randomized controlled trial is not feasible? This methodological guide highlights difference-in-differences as a robust strategy to filter out baseline differences and shared trends, yet warns that its validity hinges on the untestable parallel trends assumption and fails when policies affect all groups simultaneously. Ultimately, understanding these statistical nuances empowers physicians to critically evaluate health policy literature and make better-informed decisions in clinical and health system administration.

Citation: Alyssa Bilinski, Shuo Feng, Laura A. Hatfield. Estimating Intervention Effects With Difference-in-Differences. JAMA. 2026. DOI: 10.1001/jama.2026.12551

URL: https://doi.org/10.1001/jama.2026.12551

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