Advancing Toward a Common Data Model in Ophthalmology

Cindy X. Cai, MD, MS; William Halfpenny, MB, BChir, MEng; Michael V. Boland, MD, PhD; Harold P. Lehmann, MD, PhD; Michelle Hribar, PhD; Kerry E. Goetz, MS; Sally L. Baxter, MD, MSc

Ophthalmology Science (Dec 2023)

Advancing Toward a Common Data Model in Ophthalmology

Cindy X. Cai, MD, MS,
William Halfpenny, MB, BChir, MEng,
Michael V. Boland, MD, PhD,
Harold P. Lehmann, MD, PhD,
Michelle Hribar, PhD,
Kerry E. Goetz, MS,
Sally L. Baxter, MD, MSc

Affiliations

Cindy X. Cai, MD, MS: Wilmer Eye Institute, Johns Hopkins School of Medicine, Baltimore, Maryland; Correspondence: Cindy X. Cai, MD, MS, Wilmer Eye Institute, 1800 Orleans Street, Maumenee Building, Room 711, Baltimore, MD 21287.
William Halfpenny, MB, BChir, MEng: Division of Biomedical Informatics, Department of Medicine, University of California San Diego, La Jolla, California
Michael V. Boland, MD, PhD: Massachusetts Eye and Ear, Harvard Medical School, Boston, Massachusetts
Harold P. Lehmann, MD, PhD: Division of Health Sciences Informatics, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland; Biomedical Informatics and Data Science, Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
Michelle Hribar, PhD: Office of Data Science and Health Informatics, National Eye Institute, National Institute of Health, Bethesda, Maryland; Department of Ophthalmology, Casey Eye Institute, Portland, Oregon; Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, Oregon
Kerry E. Goetz, MS: Office of Data Science and Health Informatics, National Eye Institute, National Institute of Health, Bethesda, Maryland
Sally L. Baxter, MD, MSc: Division of Biomedical Informatics, Department of Medicine, University of California San Diego, La Jolla, California; Division of Ophthalmology Informatics and Data Science, Viterbi Family Department of Ophthalmology and Shiley Eye Institute, University of California San Diego, La Jolla, California

Journal volume & issue: Vol. 3, no. 4
p. 100391

Abstract

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Purpose: Evaluate the degree of concept coverage of the general eye examination in one widely used electronic health record (EHR) system using the Observational Health Data Sciences and Informatics Observational Medical Outcomes Partnership (OMOP) common data model (CDM). Design: Study of data elements. Participants: Not applicable. Methods: Data elements (field names and predefined entry values) from the general eye examination in the Epic foundation system were mapped to OMOP concepts and analyzed. Each mapping was given a Health Level 7 equivalence designation–equal when the OMOP concept had the same meaning as the source EHR concept, wider when it was missing information, narrower when it was overly specific, and unmatched when there was no match. Initial mappings were reviewed by 2 graders. Intergrader agreement for equivalence designation was calculated using Cohen’s kappa. Agreement on the mapped OMOP concept was calculated as a percentage of total mappable concepts. Discrepancies were discussed and a final consensus created. Quantitative analysis was performed on wider and unmatched concepts. Main Outcome Measures: Gaps in OMOP concept coverage of EHR elements and intergrader agreement of mapped OMOP concepts. Results: A total of 698 data elements (210 fields, 488 values) from the EHR were analyzed. The intergrader kappa on the equivalence designation was 0.88 (standard error 0.03, P < 0.001). There was a 96% agreement on the mapped OMOP concept. In the final consensus mapping, 25% (1% fields, 31% values) of the EHR to OMOP concept mappings were considered equal, 50% (27% fields, 60% values) wider, 4% (8% fields, 2% values) narrower, and 21% (52% fields, 8% values) unmatched. Of the wider mapped elements, 46% were missing the laterality specification, 24% had other missing attributes, and 30% had both issues. Wider and unmatched EHR elements could be found in all areas of the general eye examination. Conclusions: Most data elements in the general eye examination could not be represented precisely using the OMOP CDM. Our work suggests multiple ways to improve the incorporation of important ophthalmology concepts in OMOP, including adding laterality to existing concepts. There exists a strong need to improve the coverage of ophthalmic concepts in source vocabularies so that the OMOP CDM can better accommodate vision research. Financial Disclosure(s): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Published in Ophthalmology Science

ISSN: 2666-9145 (Online)
Publisher: Elsevier
Country of publisher: United States
LCC subjects: Medicine: Ophthalmology
Website: https://www.journals.elsevier.com/ophthalmology-science/

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