We are delighted to welcome a former Duke Internal Medicine resident, Dr. Frank Wharam, after 17 years at Harvard Medical School’s Department of Population Medicine where he held the Martin Robison Delany endowed chair and was Director of the Division of Health Policy and Insurance Research. As a general internist and health policy researcher, Dr. Wharam studies the impact of national and state policies on the health outcomes of chronically ill and vulnerable populations.
Dr. Wharam is a Professor of Medicine in Duke General Internal Medicine and will be a clinician-educator in the Duke Outpatient Clinic. He is also a core faculty member with the Duke-Margolis Center for Health Policy and will be directing a new center devoted to analyzing large-scale health policy effects in order to inform a more efficient and equitable health care system.
The new center will focus on three areas:
- Scientific rigor
- Improving health outcomes through policy research especially in vulnerable populations
- Collaboration across Duke with a focus on mentorship and training the next generation
"I hope that the center’s findings will inform health policy changes that promote health, equity, and efficiency," says Wharam.
Wharam noted the combination of Duke as a leading medical center and the Duke-Margolis Center’s national policy presence will benefit a research center seeking to study chronically ill populations, address real-world system challenges, and disseminate results to key audiences.
"We're trying to produce strong evidence that policy makers could look at, understand, and act on."
Dr. Wharam's research often examines the effects of health insurance benefit designs, such as value-based, consumer-directed, and high-deductible health plans. He also focuses on interventions that affect people with substance use disorders, diabetes, obesity, mental illness, and respiratory diseases. His other interests include the adverse effects of wasteful health care spending on medical and non-medical outcomes. Dr. Wharam has expertise in rigorous quasi-experiment research designs, causal inference in observational data, and large claims data analyses.