Computerized Adjudication of Coronary Heart Disease Events Using the Electronic Medical Record in HIV Clinical Research: Possibilities and Challenges Ahead.
HIV
computer phenotype
computerized event adjudication
coronary heart disease
electronic medical record
Journal
AIDS research and human retroviruses
ISSN: 1931-8405
Titre abrégé: AIDS Res Hum Retroviruses
Pays: United States
ID NLM: 8709376
Informations de publication
Date de publication:
04 2020
04 2020
Historique:
pubmed:
14
8
2019
medline:
7
4
2021
entrez:
14
8
2019
Statut:
ppublish
Résumé
This pilot study assessed feasibility of computer-assisted electronic medical record (EMR) abstraction to ascertain coronary heart disease (CHD) event hospitalizations. We included a sample of 87 hospitalization records from participants the University of North Carolina (UNC) site of the Women's Interagency HIV Study (WIHS) and UNC Center for AIDS Research (CFAR) HIV Clinical Cohort who were hospitalized within UNC Healthcare System from July 2004 to July 2015. We compared a computer algorithm utilizing diagnosis/procedure codes, medications, and cardiac enzyme levels to adjudicate CHD events [myocardial infarction (MI)/coronary revascularization] from the EMR to standardized manual chart adjudication. Of 87 hospitalizations, 42 were classified as definite, 25 probable, and 20 non-CHD events by manual chart adjudication. A computer algorithm requiring presence of ≥1 CHD-related International Classification of Diseases, 9th Revision (ICD-9)/Current Procedural Terminology (CPT) code correctly identified 24 of 42 definite (57%), 29 of 67 probable/definite CHD (43%), and 95% of non-CHD events; additionally requiring clinically defined cardiac enzyme levels or administration of MI-related medications correctly identified 55%, 42%, and 95% of such events, respectively. Requiring any one of the ICD-9/CPT or cardiac enzyme criteria correctly identified 98% of definite, 97% of probable/definite CHD, and 85% of non-CHD events. Challenges included difficulty matching hospitalization dates, incomplete diagnosis code data, and multiple field names/locations of laboratory/medication data. Computer algorithms comprising only ICD-9/CPT codes failed to identify a sizable proportion of CHD events. Using a less restrictive algorithm yielded fewer missed events but increased the false-positive rate. Despite potential benefits of EMR-based research, there remain several challenges to fully computerized adjudication of CHD events.
Identifiants
pubmed: 31407587
doi: 10.1089/AID.2019.0036
pmc: PMC7185364
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
306-313Subventions
Organisme : NIAID NIH HHS
ID : U01 AI103397
Pays : United States
Organisme : NIAID NIH HHS
ID : U01 AI031834
Pays : United States
Organisme : NIAID NIH HHS
ID : U01 AI035004
Pays : United States
Organisme : NIAID NIH HHS
ID : U01 AI034989
Pays : United States
Organisme : NIAID NIH HHS
ID : U01 AI034994
Pays : United States
Organisme : NIAID NIH HHS
ID : U01 AI103401
Pays : United States
Organisme : NIAID NIH HHS
ID : U01 AI103408
Pays : United States
Organisme : NHLBI NIH HHS
ID : U01 HL146194
Pays : United States
Organisme : NIAID NIH HHS
ID : U01 AI103390
Pays : United States
Organisme : NIAID NIH HHS
ID : U01 AI034993
Pays : United States
Organisme : NIAID NIH HHS
ID : P30 AI050410
Pays : United States
Organisme : NICHD NIH HHS
ID : U01 HD032632
Pays : United States
Organisme : NIAID NIH HHS
ID : U01 AI042590
Pays : United States
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