biostudies-literatureWyatt BNIOSH CDC HHSGilead Sciences2974-2987https://www.ebi.ac.uk/biostudies/studies/S-EPMC9299620biostudies-literatureUnknown74(6)<h4>Background and aims</h4>Although chronic HCV infection increases mortality, thousands of patients remain diagnosed-but-untreated (DBU). We aimed to (1) develop a DBU phenotyping algorithm, (2) use it to facilitate case finding and linkage to care, and (3) identify barriers to successful treatment.<h4>Approach and results</h4>We developed a phenotyping algorithm using Java and SQL and applied it to ~2.5 million EPIC electronic medical records (EMRs; data entered January 2003 to December 2017). Approximately 72,000 EMRs contained an HCV International Classification of Diseases code and/or diagnostic test. The algorithm classified 10,614 cases as DBU (HCV-RNA positive and alive). Its positive and negative predictive values were 88% and 97%, respectively, as determined by manual review of Hepatology (Baltimore, Md.)A Digital Case-Finding Algorithm for Diagnosed but Untreated Hepatitis C: A Tool for Increasing Linkage to Treatment and Cure.PMC9299620U01 OH011489U01 OH012263Miller MWyatt BMageras AMa NDinani ADieterich DJeon JLi LBowman CAPaulino LCollado FPerumalswami PVHarty AVandromme MBranch ADfalseA Digital Case-Finding Algorithm for Diagnosed but Untreated Hepatitis C: A Tool for Increasing Linkage to Treatment and Cure.<h4>Background and aims</h4>Although chronic HCV infection increases mortality, thousands of patients remain diagnosed-but-untreated (DBU). We aimed to (1) develop a DBU phenotyping algorithm, (2) use it to facilitate case finding and linkage to care, and (3) identify barriers to successful treatment.<h4>Approach and results</h4>We developed a phenotyping algorithm using Java and SQL and applied it to ~2.5 million EPIC electronic medical records (EMRs; data entered January 2003 to December 2017). Approximately 72,000 EMRs contained an HCV International Classification of Diseases code and/or diagnostic test. The algorithm classified 10,614 cases as DBU (HCV-RNA positive and alive). Its positive and negative predictive values were 88% and 97%, respectively, as determined by manual review of 2021-01-01T00:00:00Z2021 Dec2025-04-05T15:04:20.584Z2022-08-06T14:48:04.209ZS-EPMC92996203433377710.1002/hep.32086