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Stephen C Resch, Ph.D.

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Biography
University of Connecticut, Storrs, CTBS05/1996Molecular Cell Biology
Yale School of Public Health, New Haven, CTMPH05/2001Health Policy
Harvard University, Cambridge, MAPhD03/2007Health Policy

Overview
Stephen Resch, MPH, PhD, is a Lecturer on Health Decision Science in the Department of Health Policy and Management at the Harvard T.H. Chan School of Public Health. He is a core faculty member of the Center for Health Decision Science.

Dr. Resch's research focuses on advancing the use of decision analytic approaches in health policymaking and health program management. As a generalist with a passion for practical applications of technical analysis to aid decision-making, he often works closely with global health organizations and government officials across a broad range of public health topics and settings. Internationally, his work has addressed policy issues related to resource requirements, financial sustainability, and economic efficiency of health programs to treat or prevent of HIV, TB, malaria, and hepatitis, as well as programs to improve maternal and neonatal survival in childbirth, and vaccination. Domestically, he has worked on evaluation of obesity prevention interventions, HIV testing and linkage to care for incarcerated populations, and evaluation of dental interventions to prevent tooth decay in high-risk children.

Dr. Resch's work often involves constructing decision analytic models and employing computer simulation to predict health benefits, costs and other social impacts of alternative policy options. His core motivation is to aid decision makers in identifying decision criteria consistent with their goals and providing evidence that clarifies relevant constraints, trade-offs and uncertainties. He holds and MPH from Yale University and a PhD from Harvard University. He teaches a course on economic evaluation in the decision science curriculum at the Harvard Chan School.

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Funded by the NIH National Center for Advancing Translational Sciences through its Clinical and Translational Science Awards Program, grant number UL1TR002541.