Development of a Coronavirus Disease 2019 (COVID-19) Application Ontology for the Accrual to Clinical Trials (ACT) network

Shyam Visweswaran, Malarkodi J. Samayamuthu, Michele Morris, Griffin M. Weber, Douglas Macfadden, Philip Trevvett, Jeffrey G. Klann, Vivian S. Gainer, Barbara Benoit, Shawn N. Murphy, Lav Patel, Nebojsa Mirkovic, Yuliya Borovskiy, Robert D. Johnson, Matthew C. Wyatt, Amy Y. Wang, Robert W. Follett, Ngan Chau, Mark Abajian, Wenhong ZhuAmy Chuang, Neil Bahroos, Phillip Reeder, Donglu Xie, Jennifer Cai, Elaina R. Sendro, Robert D. Toto, Gary S. Firestein, Lee M. Nadler, Steven E. Reis

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Clinical data networks that leverage large volumes of data in electronic health records (EHRs) are significant resources for research on coronavirus disease 2019 (COVID-19). Data harmonization is a key challenge in seamless use of multisite EHRs for COVID-19 research. We developed a COVID-19 application ontology in the national Accrual to Clinical Trials (ACT) network that enables harmonization of data elements that are critical to COVID-19 research. The ontology contains over 50 000 concepts in the domains of diagnosis, procedures, medications, and laboratory tests. In particular, it has computational phenotypes to characterize the course of illness and outcomes, derived terms, and harmonized value sets for severe acute respiratory syndrome coronavirus 2 laboratory tests. The ontology was deployed and validated on the ACT COVID-19 network that consists of 9 academic health centers with data on 14.5M patients. This ontology, which is freely available to the entire research community on GitHub at https://github.com/shyamvis/ACT-COVID-Ontology, will be useful for harmonizing EHRs for COVID-19 research beyond the ACT network.

Original languageEnglish (US)
Article numberooab036
JournalJAMIA Open
Volume4
Issue number2
DOIs
StatePublished - Apr 1 2021
Externally publishedYes

Keywords

  • clinical data network
  • COVID-19
  • electronic health records
  • ontology

ASJC Scopus subject areas

  • Health Informatics

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