Dr. Admon's research applies causal inferential methods to observational data to improve the organization and delivery of inpatient care. His work is built upon the premise that modern analytical techniques can be applied to observational data resources to inform design decisions in hospital care delivery where randomized experiments are often difficult or impossible. To do so, he uses research methods from epidemiology, biostatistics, economics, and computer science attentive to complex causal structures, complex temporal relationships, and other challenges in observational study design.
- M.D., University of Michigan
- M.Sc., Health and Health Care Research, University of Michigan
- M.P.H., Quantitative Methods, Harvard University
- B.S., Sociology, University of Michigan