James Wharam
Instructor in the Department of Medicine

Dr. Frank Wharam is a general internist and health policy researcher. He studies the impact of national and state policies on the health outcomes of chronically ill and vulnerable populations. His research often examines effects of health insurance benefit designs such as value-based, consumer-directed, and high-deductible health plans. Dr. Wharam also focuses on interventions that affect people with substance use disorders, diabetes, obesity, mental illness, and respiratory diseases. Other interests include the adverse effects of wasteful health care spending on medical and non-medical outcomes. He has expertise in rigorous quasi-experiment research designs, causal inference in observational data, and large claims data analyses.

Dr. Wharam is core faculty member in the Margolis Center and Professor of Medicine in the Division of General Internal Medicine. He directs a new center devoted to analyzing large-scale health policy effects in order to inform a more efficient and equitable health care system.   

Dr. Wharam joins Duke after 17 years at the Harvard Medical School Department of Population Medicine. There he held the Martin Robison Delany endowed chair and was Director of the Division of Health Policy and Insurance Research. Before Harvard, he completed Internal Medicine residency at Duke in 2004. 

Current Research Interests

Dr. Frank Wharam is a general internist and health policy researcher. He studies the impact of national and state policies on the health outcomes of chronically ill and vulnerable populations. His research often examines effects of health insurance benefit designs such as value-based, consumer-directed, and high-deductible health plans. Dr. Wharam also focuses on interventions that affect people with substance use disorders, diabetes, obesity, mental illness, and respiratory diseases. Other interests include the adverse effects of wasteful health care spending on medical and non-medical outcomes. He has expertise in rigorous quasi-experiment research designs, causal inference in observational data, and large claims data analyses.

Current Appointments & Affiliations

Contact Information

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