A Computable Phenotype for HSV Anterior Uveitis: Operationalizing the SUN Classification Criteria employing the OMOP Common Data Model
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Purpose
Data models can enhance observational research for rare diseases like uveitis. This study operationalized the Standardization of Uveitis Nomenclature (SUN) classification criteria for herpes simplex virus (HSV) anterior uveitis into the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM).
Methods
Using the Observational Health Data Sciences and Informatics (OHDSI) ATLAS tool, we constructed a computable phenotype, applied it to two electronic health records (EHR) systems for internal validation, and to Optum’s Clinformatics® claims database for external validation.
Results
In EHR manual chart reviews, we identified 5,404 and 38 patients at two sites, achieving 70% and 90% accuracy, respectively, in a randomized validation sample. From the claims database, 10,858 (2.7%) patients met all criteria, consistent with previous literature. The most discriminatory inclusion criterion was a history of HSV keratitis.
Conclusion
Our results indicate that OMOP can accurately identify HSV anterior uveitis, suggesting potential utility for operationalizing other uveitis subtypes in observational research.
Conflict of interest
No
1
Last name
TOY
Initials of first name(s)
B
Department
USC Roski Eye Institute
City
Los Angeles
Country
United States
2
Last name
Armbrust
Initials of first name(s)
K
Department
Minneapolis VA Health Care System, University of Minnesota
City
Minneapolis
Country
United States
3
Last name
Kim
Initials of first name(s)
A
Department
USC Roski Eye Institute
City
Los Angeles
Country
United States
4
Last name
Lee
Initials of first name(s)
E
Department
USC Roski Eye Institute
City
Los Angeles
Country
United States
5
Last name
Huang
Initials of first name(s)
L
Department
UCSD Shiley Eye Institute
City
San Diego
Country
United States
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