Anne V. Grossestreuer, PhD

Anne V. Grossestreuer, PhD

Director of Epidemiology and Data Science, Center for Resuscitation Science
agrosses@bidmc.harvard.edu

About Anne Grossestreuer

Dr. Anne Grossestreuer is a Research Scientist in the Department of Emergency Medicine at Beth Israel Deaconess Medical Center, an Assistant Professor of Emergency Medicine at Harvard Medical School, and the Director of Epidemiology and Data Science at the Center for Resuscitation Science. She received her doctorate in Epidemiology from the Center for Clinical Epidemiology and Biostatistics at the University of Pennsylvania. Dr. Grossestreuer’s research interests center on the definitive/supportive care that patients receive following successful resuscitation, outcomes after patients leave the hospital following critical illness, and the role of novel epidemiological methods in observation studies in critical care. She has served as Principal Investigator on awards from Harvard Catalyst and the American Heart Association. She serves as lead statistician for many of the CRS trials and provides statistical support for a variety of other studies within Emergency Medicine and Critical Care as well as the BIDMC Data Abstraction Core. Dr. Grossestreuer is a member of the Editorial Board of Resuscitation and the American Heart Association’s Get with the Guidelines – Resuscitation Adult Research Taskforce. Her research has won awards at the American Heart Association Resuscitation Science Symposium and the European Resuscitation Council Congress. She has additional research training in medical anthropology, in which she received an MSc from the University of Pennsylvania, and experience in health services research as a fellow at the Leonard Davis Institute of Healthcare Economics and health policy as a fellow at the Center for Emergency Care Policy Research.

Topics for Talks by Anne Grossestreuer

  • Adaptive Clinical Trials
  • Sensitivity and Specificity
  • Introductory Biostatistics (short overview)
  • Presentation of Data
  • Types of Research Studies
  • Power and Sample Size Calculations
  • Immortal Time Bias