Development and Evaluation of a Rules-based Algorithm for Primary Open-Angle Glaucoma in the VA Million Veteran Program.

Autor: Nealon CL; Eye Clinic, VA Northeast Ohio Healthcare System, Cleveland, OH, USA., Halladay CW; Center of Innovation in Long Term Services and Supports, Providence VAMC, Providence, RI, USA., Kinzy TG; Research Service, Veterans AffairsNortheast Ohio Healthcare System, Cleveland, OH, USA.; Cleveland Institute for Computational Biology, Case Western Reserve University School of Medicine, Cleveland, OH, USA.; Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA., Simpson P; Eye Clinic, VA Northeast Ohio Healthcare System, Cleveland, OH, USA., Canania RL; Eye Clinic, VA Northeast Ohio Healthcare System, Cleveland, OH, USA., Anthony SA; Eye Clinic, VA Northeast Ohio Healthcare System, Cleveland, OH, USA., Roncone DP; Eye Clinic, VA Northeast Ohio Healthcare System, Cleveland, OH, USA., Sawicki Rogers LR; Ophthalmology Section, VA Western NY Health Care System, Buffalo NY, RI., Leber JN; Ophthalmology Section, VA Western NY Health Care System, Buffalo NY, RI., Dougherty JM; Ophthalmology Section, VA Western NY Health Care System, Buffalo NY, RI., Sullivan JM; Ophthalmology Section, VA Western NY Health Care System, Buffalo NY, RI., Wu WC; Cardiology Section, Medical Service, Providence VA Medical Center, Providence, RI, USA., Greenberg PB; Ophthalmology Section, Providence VA Medical Center, Providence, RI, USA.; Division of Ophthalmology, Alpert Medical School, Brown University, Providence, RI, USA., Iyengar SK; Research Service, Veterans AffairsNortheast Ohio Healthcare System, Cleveland, OH, USA.; Cleveland Institute for Computational Biology, Case Western Reserve University School of Medicine, Cleveland, OH, USA.; Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA., Crawford DC; Research Service, Veterans AffairsNortheast Ohio Healthcare System, Cleveland, OH, USA.; Cleveland Institute for Computational Biology, Case Western Reserve University School of Medicine, Cleveland, OH, USA.; Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA., Peachey NS; Research Service, Veterans AffairsNortheast Ohio Healthcare System, Cleveland, OH, USA.; Cole Eye Institute, Cleveland Clinic Foundation, Cleveland, OH.; Department of Ophthalmology, Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, OH., Cooke Bailey JN; Research Service, Veterans AffairsNortheast Ohio Healthcare System, Cleveland, OH, USA.; Cleveland Institute for Computational Biology, Case Western Reserve University School of Medicine, Cleveland, OH, USA.; Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA.
Jazyk: angličtina
Zdroj: Ophthalmic epidemiology [Ophthalmic Epidemiol] 2022 Dec; Vol. 29 (6), pp. 640-648. Date of Electronic Publication: 2021 Nov 25.
DOI: 10.1080/09286586.2021.1992784
Abstrakt: The availability of electronic health record (EHR)-linked biobank data for research presents opportunities to better understand complex ocular diseases. Developing accurate computable phenotypes for ocular diseases for which gold standard diagnosis includes imaging remains inaccessible in most biobank-linked EHRs. The objective of this study was to develop and validate a computable phenotype to identify primary open-angle glaucoma (POAG) through accessing the Department of Veterans Affairs (VA) Computerized Patient Record System (CPRS) and Million Veteran Program (MVP) biobank. Accessing CPRS clinical ophthalmology data from VA Medical Center Eye Clinic (VAMCEC) patients, we developed and iteratively refined POAG case and control algorithms based on clinical, prescription, and structured diagnosis data (ICD-CM codes). Refinement was performed via detailed chart review, initially at a single VAMCEC (n = 200) and validated at two additional VAMCECs (n = 100 each). Positive and negative predictive values (PPV, NPV) were computed as the proportion of CPRS patients correctly classified with POAG or without POAG, respectively, by the algorithms, validated by ophthalmologists and optometrists with access to gold-standard clinical diagnosis data. The final algorithms performed better than previously reported approaches in assuring the accuracy and reproducibility of POAG classification (PPV >83% and NPV >97%) with consistent performance in Black or African American and in White Veterans. Applied to the MVP to identify cases and controls, genetic analysis of a known POAG-associated locus further validated the algorithms. We conclude that ours is a viable approach to use combined EHR-genetic data to study patients with complex diseases that require imaging confirmation.
Databáze: MEDLINE
Externí odkaz:
Nepřihlášeným uživatelům se plný text nezobrazuje