Ontologizing Health Systems Data at Scale: Making Translational Discovery a Reality
Abstract
Background: Common data models solve many challenges of standardizing electronic health record (EHR) data, but are unable to semantically integrate all 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. Objective: We introduce OMOP2OBO, an algorithm for mapping Observational Medical Outcomes Partnership (OMOP) vocabularies to OBO ontologies. Results: 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. Conclusions: By aligning OMOP vocabularies to OBO ontologies our algorithm presents new opportunities to advance EHR-based deep phenotyping.
Keywords
Cite
@article{arxiv.2209.04732,
title = {Ontologizing Health Systems Data at Scale: Making Translational Discovery a Reality},
author = {Tiffany J. Callahan and Adrianne L. Stefanski and Jordan M. Wyrwa and Chenjie Zeng and Anna Ostropolets and Juan M. Banda and William A. Baumgartner and Richard D. Boyce and Elena Casiraghi and Ben D. Coleman and Janine H. Collins and Sara J. Deakyne-Davies and James A. Feinstein and Melissa A. Haendel and Asiyah Y. Lin and Blake Martin and Nicolas A. Matentzoglu and Daniella Meeker and Justin Reese and Jessica Sinclair and Sanya B. Taneja and Katy E. Trinkley and Nicole A. Vasilevsky and Andrew Williams and Xingman A. Zhang and Joshua C. Denny and Peter N. Robinson and Patrick Ryan and George Hripcsak and Tellen D. Bennett and Lawrence E. Hunter and Michael G. Kahn},
journal= {arXiv preprint arXiv:2209.04732},
year = {2023}
}
Comments
Supplementary Material is included at the end of the manuscript