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Improving the Quality and Utility of Electronic Health Record Data through Ontologies

Authors :
Asiyah Yu Lin
Sivaram Arabandi
Thomas Beale
William D. Duncan
Amanda Hicks
William R. Hogan
Mark Jensen
Ross Koppel
Catalina Martínez-Costa
Øystein Nytrø
Jihad S. Obeid
Jose Parente de Oliveira
Alan Ruttenberg
Selja Seppälä
Barry Smith
Dagobert Soergel
Jie Zheng
Stefan Schulz
Source :
Standards, Vol 3, Iss 3, Pp 316-340 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

The translational research community, in general, and the Clinical and Translational Science Awards (CTSA) community, in particular, share the vision of repurposing EHRs for research that will improve the quality of clinical practice. Many members of these communities are also aware that electronic health records (EHRs) suffer limitations of data becoming poorly structured, biased, and unusable out of original context. This creates obstacles to the continuity of care, utility, quality improvement, and translational research. Analogous limitations to sharing objective data in other areas of the natural sciences have been successfully overcome by developing and using common ontologies. This White Paper presents the authors’ rationale for the use of ontologies with computable semantics for the improvement of clinical data quality and EHR usability formulated for researchers with a stake in clinical and translational science and who are advocates for the use of information technology in medicine but at the same time are concerned by current major shortfalls. This White Paper outlines pitfalls, opportunities, and solutions and recommends increased investment in research and development of ontologies with computable semantics for a new generation of EHRs.

Details

Language :
English
ISSN :
23056703
Volume :
3
Issue :
3
Database :
Directory of Open Access Journals
Journal :
Standards
Publication Type :
Academic Journal
Accession number :
edsdoj.1a5920ce3d164cddbacb10ebe02abb18
Document Type :
article
Full Text :
https://doi.org/10.3390/standards3030023