Jose Zubizarreta, PhD, is an associate professor in the Department of Health Care Policy at Harvard Medical School and a faculty affiliate in the Department of Statistics at the Faculty of Arts and Sciences at Harvard University. His work centers on the development of statistical methods for causal inference and impact evaluation to advance research in health care and public policy. In his methodological work, Dr. Zubizarreta uses tools from modern optimization to develop new matching and weighting methods for causal inference as alternatives to commonly used regression methods. In his health care work, he is interested in assessing the quality of care provided by hospitals and physicians using health outcomes and operations measures. His research interests also encompass comparative effectiveness research and health program impact evaluation.
Dr. Zubizarreta received his PhD in statistics at The Wharton School at the University of Pennsylvania in 2013, focusing on optimal designs for observational studies using mathematical programming, with applications to health care and policy. As a doctoral student, he was honored with the J. Parker Memorial Bursk Prize for excellence in research and a President Gutmann Leadership Award. He was a Fulbright Scholar and has also received several student and young investigator awards from the American Statistical Association (ASA), including awards from the Biometrics, Epidemiology, Health Policy Statistics, and Social Statistics, Government Statistics and Survey Research Methods Sections of ASA. He has also been a recipient of the Tom Ten Have Memorial Award for “exceptionally creative or skillful research on causal inference” at the Atlantic Causal Inference Conference.
Dr. Zubizarreta’s methodological research has been published in the Journal of the American Statistical Association, the Annals of Applied Statistics, the American Statistician, Statistics in Medicine, the Journal of the Royal Statistical Society, and Biometrika. His research in medicine and healthcare has appeared in the Journal of the American Medical Association, the Annals of Surgery, and the Journal of Perinatology, among others. His work on reducing sensitivity to unmeasured bias through study design was awarded the Kenneth Rothman Award for the best publication in Epidemiology in 2013. His methodological research has been funded by the Alfred P. Sloan foundation. He has written several software packages making his statistical methods widely available.
Before joining HCP, Dr. Zubizarreta was an assistant professor in the Division of Decision, Risk, and Operations and the Department of Statistics at Columbia Business School, where he taught MBA and PhD students basic and advanced courses in statistics.