Harvard Public Health

Researchers are now harnessing vast amounts of information to assess what works in medicine and public health. In this week's podcast, we explore why this approach holds promise—but why it also comes with potential risks. You'll hear from Miguel Hernan, Kolokotrones Professor of Biostatistics and Epidemiology, who is a leading expert in the field of causal inference, which includes comparative effectiveness research to guide policy and clinical decisions. We discussed how researchers are using big data to answer important questions about health—and the safeguards that need to be in place to avoid misleading results.