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Published June 21, 2020 | Version v0.0.0
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OMOP2OBO

  • 1. Computational Bioscience Program, University of Colorado Anschutz Medical Campus
  • 2. Oregon Clinical and Translational Research Institute, Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University
  • 3. Department of Pediatrics, Section of Pediatric Critical Care, School of Medicine, University of Colorado Anschutz Medical Campus
  • 1. Department of Research Informatics, Children's Hospital Colorado
  • 2. Computational Bioscience Program, University of Colorado Anschutz Medical Campus
  • 3. Department, Purdue University of Pharmacy Practice,
  • 4. The Jackson Laboratory for Genomic Medicine

Description

Precision medicine requires timely synthesis of clinical and genomic data. Despite large-scale biobanking efforts, most electronic health records (EHRs) do not systematically integrate nor have the infrastructure to incorporate genomic data. Common data models (CDMs) have solved many of the challenges of utilizing EHR data, yet they do not include resources needed to integrate or interpret clinical and genomic data. Biomedical ontologies provide accurate and semantically computable representations of biological knowledge. Aligning patient data to open biomedical ontologies (OBO) requires manual and/or semi-automated curation and domain expertise, limiting existing efforts to specific diseases and clinical data. We introduce OMOP2OBO - the first health system-wide, disease-agnostic mappings between standardized clinical terminologies in the Observational Medical Outcomes Partnership (OMOP) CDM and several OBO foundry ontologies. These mappings were validated by domain experts and their coverage was examined in several health systems. The mappings are openly available at  https://github.com/callahantiff/OMOP2OBO/wiki.

Notes

Mappings are in progress and will be updated here shortly

Files

UCDenver_AMC_LOINC2HPO Mapping.pdf

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