Development and validation of techniques for phenotyping ST-elevation myocardial infarction encounters from electronic health records.

Link: https://doi.org/10.1093/jamiaopen/ooab068
Authors: Somani, Sulaiman; Yoffie, Stephen; Teng, Shelly; Havaldar, Shreyas; Nadkarni, Girish N; Zhao, Shan; Glicksberg, Benjamin S

Abstract: Classifying hospital admissions into various acute myocardial infarction phenotypes in electronic health records (EHRs) is a challenging task with strong research implications that remains unsolved. To our knowledge, this study is the first study to design and validate phenotyping algorithms using cardiac catheterizations to identify not only patients with a ST-elevation myocardial infarction (STEMI), but the specific encounter when it occurred. We design and validate multi-modal algorithms to phenotype STEMI on a multicenter EHR containing 5.1 million patients and 115 million patient encounters by using discharge summaries, diagnosis codes, electrocardiography readings, and the presence of cardiac catheterizations on the encounter. In this study, we demonstrate that the incorporation of percutaneous coronary intervention increases the PPV for detecting STEMI-related patient encounters from the EHR.