Speaker
David Madigan, Columbia University
Abstract
Observational health care data, such as administrative claims and electronic health records, play an increasingly prominent role in health care. Pharmacoepidemiologic studies in particular routinely estimate temporal associations between medical product exposure and subsequent health outcomes of interest and such studies influence prescribing patterns and health care policy more generally. Some authors have questioned the reliability and accuracy of such studies, but few previous efforts have attempted to measure their performance. The Observational Medical Outcomes Partnership (OMOP, omop.org) has conducted a series of experiments to empirically measure the performance of various observational study designs with regard to predictive accuracy for discriminating between true drug effects and negative controls. In this talk, I describe the past work of OMOP, explore opportunities to expand the use of observational data to further our understanding of medical products, and highlight areas for future research and development.