Dr. Rebecca Hubbard’s research focuses on the development and application of methods to improve analyses using real world data sources including electronic health records (EHR) and claims data. The data science era demands novel analytic methods to transform the wealth of data created as a byproduct of our digital interactions into valid and generalizable knowledge. Dr. Hubbard’s research emphasizes statistical methods designed to meet this challenge by addressing the messiness and complexity of real world data including informative observation schemes, phenotyping error, and error and missingness in confounders. Her methods have been applied to support the advancement of a broad range of research areas through use of EHR and claims data including health services research, cancer epidemiology, aging and dementia, and pharmacoepidemiology. She is an elected Fellow of the American Statistical Association and recipient of the American Statistical Association Health Policy Statistics Section’s Mid-Career Research Award.
Dr. Hubbard received her B.S. in Ecology & Evolution from the University of Pittsburgh. She subsequently completed master’s work in Epidemiology at the University of Edinburgh and Applied Statistics at Oxford University. She obtained her PhD in Biostatistics from the University of Washington. Dr. Hubbard was a scientific investigator at the Group Health Research Institute (subsequently renamed Kaiser Permanente Washington Health Research Institute) for six years before joining the Biostatistics faculty at the University of Pennsylvania.
Dr. Hubbard lives in Philadelphia with her wife, calico cat, and collection of novels from the classic era of science-fiction. She enjoys long distance road running and discovering new vegan restaurants.