Implementing a Common Data Model in Ophthalmology: Mapping Structured Electronic Health Record Ophthalmic Examination Data to Standard Vocabularies

作者：Justin C. Quon, Christopher P. Long, William Halfpenny, Amy Chuang, Cindy X. Cai, Sally L. Baxter, Vamsi Daketi, Amanda Schmitz, Neil Bahroos, Benjamin Y. Xu, Brian C. Toy · 发表于：Ophthalmology Science · 年份：2024 · DOI：10.1016/j.xops.2024.100666 · 被引用次数：4 · 研究领域：Electronic Health Records Systems、Retinal Imaging and Analysis、Genomics and Rare Diseases

Objective: To identify and characterize concept coverage gaps of ophthalmology examination data elements within the Cerner Millennium electronic health record (EHR) implementations by the Observational Health Data Sciences and Informatics Observational Medical Outcomes Partnership (OMOP) common data model (CDM). Design: Analysis of data elements in EHRs. Subjects: Not applicable. Methods: Source eye examination data elements from the default Cerner Model Experience EHR and a local implementation of the Cerner Millennium EHR were extracted, classified into one of 8 subject categories, and mapped to the semantically closest standard concept in the OMOP CDM. Mappings were categorized as exact, if the data element and OMOP concept represented equivalent information, wider, if the OMOP concept was missing conceptual granularity, narrower, if the OMOP concept introduced excess information, and unmatched, if no standard concept adequately represented the data element. Descriptive statistics and qualitative analysis were used to describe the concept coverage for each subject category. Main Outcome Measures: Concept coverage gaps in 8 ophthalmology subject categories of data elements by the OMOP CDM. Results: . The largest coverage gaps were seen in the local Cerner module under the visual acuity, sensorimotor testing, and refraction categories, with 95%, 95%, and 81% of data elements in each respective category having mappings that were not exact. Concept coverage gaps spanned all 8 ...