COVID-19 and Substance Misuse Case Identification using Data Science: A Retrospective Cohort Study

This project will provide novel and critically important tools in artificial intelligence for the detection of substance misuse and COVID-19 from the electronic health record (EHR). Development and validation of a digital classifier would enable a standardized approach to perform screening on all patient encounters on a daily basis in health systems. We will rigorously develop and test the classifier retrospectively on an existing dataset of 60,000 patients who have been screened for COVID-19. This will serve as the first step towards a comprehensive universal screener that leverages available data in the EHR.