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Using Phecodes for Research with the Electronic Health Record: From PheWAS to PheRS

Lisa Bastarache

2021Annual Review of Biomedical Data Science222 citationsDOIOpen Access PDF

Abstract

Electronic health records (EHRs) are a rich source of data for researchers, but extracting meaningful information out of this highly complex data source is challenging. Phecodes represent one strategy for defining phenotypes for research using EHR data. They are a high-throughput phenotyping tool based on ICD (International Classification of Diseases) codes that can be used to rapidly define the case/control status of thousands of clinically meaningful diseases and conditions. Phecodes were originally developed to conduct phenome-wide association studies to scan for phenotypic associations with common genetic variants. Since then, phecodes have been used to support a wide range of EHR-based phenotyping methods, including the phenotype risk score. This review aims to comprehensively describe the development, validation, and applications of phecodes and suggest some future directions for phecodes and high-throughput phenotyping.

Topics & Concepts

PhenomeHealth recordsData scienceComputer scienceElectronic health recordData miningComputational biologyPhenotypeBiologyGeneticsHealth carePolitical scienceGeneLawBiomedical Text Mining and OntologiesGenetic Associations and EpidemiologyGenomics and Rare Diseases
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