School of Medicine
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Alan M. Garber
Henry J. Kaiser Jr. Professor and Professor of Medicine, Emeritus
Current Research and Scholarly Interests Topics in the health economics of aging; health, insurance; optimal screening intervals; cost-effectiveness of, coronary surgery in the elderly; health care financing and delivery, in the United States and Japan; coronary heart disease
Associate Professor of Medicine (Primary Care & Outcomes Research)
Bio Jeremy Goldhaber-Fiebert, PhD, is an Associate Professor of Medicine, a Core Faculty Member at the Centers for Health Policy/Primary Care and Outcomes Research, and a Faculty Affiliate of the Stanford Center on Longevity and Stanford Center for International Development. His research focuses on complex policy decisions surrounding the prevention and management of increasingly common, chronic diseases and the life course impact of exposure to their risk factors. In the context of both developing and developed countries including the US, India, China, and South Africa, he has examined chronic conditions including type 2 diabetes and cardiovascular diseases, human papillomavirus and cervical cancer, tuberculosis, and hepatitis C and on risk factors including smoking, physical activity, obesity, malnutrition, and other diseases themselves. He combines simulation modeling methods and cost-effectiveness analyses with econometric approaches and behavioral economic studies to address these issues. Dr. Goldhaber-Fiebert graduated magna cum laude from Harvard College in 1997, with an A.B. in the History and Literature of America. After working as a software engineer and consultant, he conducted a year-long public health research program in Costa Rica with his wife in 2001. Winner of the Lee B. Lusted Prize for Outstanding Student Research from the Society for Medical Decision Making in 2006 and in 2008, he completed his PhD in Health Policy concentrating in Decision Science at Harvard University in 2008. He was elected as a Trustee of the Society for Medical Decision Making in 2011.
Past and current research topics:
- Type 2 diabetes and cardiovascular risk factors: Randomized and observational studies in Costa Rica examining the impact of community-based lifestyle interventions and the relationship of gender, risk factors, and care utilization.
-Cervical cancer: Model-based cost-effectiveness analyses and costing methods studies that examine policy issues relating to cervical cancer screening and human papillomavirus vaccination in countries including the United States, Brazil, India, Kenya, Peru, South Africa, Tanzania, and Thailand.
- Measles, haemophilus influenzae type b, and other childhood infectious diseases: Longitudinal regression analyses of country-level data from middle and upper income countries that examine the link between vaccination, sustained reductions in mortality, and evidence of herd immunity.
- Patient adherence: Studies in both developing and developed countries of the costs and effectiveness of measures to increase successful adherence. Adherence to cervical cancer screening as well as to disease management programs targeting depression and obesity is examined from both a decision-analytic and a behavioral economics perspective.
- Simulation modeling methods: Research examining model calibration and validation, the appropriate representation of uncertainty in projected outcomes, the use of models to examine plausible counterfactuals at the biological and epidemiological level, and the reflection of population and spatial heterogeneity.
Mary Kane Goldstein
Professor of Medicine (Center for Primary Care and Outcomes Research) at the Palo Alto Veterans Affairs Health Care System
Current Research and Scholarly Interests Health services research in primary care and geriatrics: developing, implementing, and evaluating methods for clinical quality improvement. Current work includes applying health information technology to quality improvement through clinical decision support (CDS) integrated with electronic health records; encoding clinical knowledge into computable formats in automated knowledge bases; natural language processing of free text in electronic health records; analyzing multiple comorbidities