In the era of Electronic Health Records, it is possible to examine the outcomes of decisions made by doctors during clinical practice to identify patterns of care—generating evidence from the collective experience of patients. We will discuss methods that transform unstructured EHR data into a de-identified, temporally ordered, patient-feature matrix. We will also review use-cases, which use the resulting de-identified data, for pharmacovigilance, to reposition drugs, build predictive models, and drive comparative effectiveness studies in a learning health system.