Development and evaluation of an EHR‐based computable phenotype for identification of pediatric Crohn's disease patients in a National Pediatric Learning Health System (original) (raw)

Learning Health Systems, 2020

Abstract

ObjectivesTo develop and evaluate the classification accuracy of a computable phenotype for pediatric Crohn's disease using electronic health record data from PEDSnet, a large, multi‐institutional research network and Learning Health System.Study DesignUsing clinician and informatician input, algorithms were developed using combinations of diagnostic and medication data drawn from the PEDSnet clinical dataset which is comprised of 5.6 million children from eight U.S. academic children's health systems. Six test algorithms (four cases, two non‐cases) that combined use of specific medications for Crohn's disease plus the presence of Crohn's diagnosis were initially tested against the entire PEDSnet dataset. From these, three were selected for performance assessment using manual chart review (primary case algorithm, n = 360, primary non‐case algorithm, n = 360, and alternative case algorithm, n = 80). Non‐cases were patients having gastrointestinal diagnoses other than ...

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