Ontologizing health systems data at scale: making translational discovery a reality
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Published:2023-05-19
Issue:1
Volume:6
Page:
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ISSN:2398-6352
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Container-title:npj Digital Medicine
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language:en
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Short-container-title:npj Digit. Med.
Author:
Callahan Tiffany J.ORCID, Stefanski Adrianne L., Wyrwa Jordan M.ORCID, Zeng Chenjie, Ostropolets Anna, Banda Juan M., Baumgartner William A., Boyce Richard D., Casiraghi ElenaORCID, Coleman Ben D., Collins Janine H.ORCID, Deakyne Davies Sara J.ORCID, Feinstein James A., Lin Asiyah Y., Martin BlakeORCID, Matentzoglu Nicolas A., Meeker Daniella, Reese Justin, Sinclair Jessica, Taneja Sanya B.ORCID, Trinkley Katy E., Vasilevsky Nicole A., Williams Andrew E.ORCID, Zhang Xingmin A., Denny Joshua C., Ryan Patrick B., Hripcsak George, Bennett Tellen D., Haendel Melissa A., Robinson Peter N.ORCID, Hunter Lawrence E., Kahn Michael G.ORCID
Abstract
AbstractCommon data models solve many challenges of standardizing electronic health record (EHR) data but are unable to semantically integrate all of the resources needed for deep phenotyping. Open Biological and Biomedical Ontology (OBO) Foundry ontologies provide computable representations of biological knowledge and enable the integration of heterogeneous data. However, mapping EHR data to OBO ontologies requires significant manual curation and domain expertise. We introduce OMOP2OBO, an algorithm for mapping Observational Medical Outcomes Partnership (OMOP) vocabularies to OBO ontologies. Using OMOP2OBO, we produced mappings for 92,367 conditions, 8611 drug ingredients, and 10,673 measurement results, which covered 68–99% of concepts used in clinical practice when examined across 24 hospitals. When used to phenotype rare disease patients, the mappings helped systematically identify undiagnosed patients who might benefit from genetic testing. By aligning OMOP vocabularies to OBO ontologies our algorithm presents new opportunities to advance EHR-based deep phenotyping.
Funder
U.S. Department of Health & Human Services | NIH | U.S. National Library of Medicine U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute RCUK | Medical Research Council U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute U.S. Department of Health & Human Services | NIH | National Center for Advancing Translational Sciences
Publisher
Springer Science and Business Media LLC
Subject
Health Information Management,Health Informatics,Computer Science Applications,Medicine (miscellaneous)
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