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

  • Asiah Yu Lin
  • , Sivaram Arabandi
  • , Thomas Beale
  • , William D. Duncan
  • , Amanda Hicks
  • , William R. Horgan
  • , Mark Jensen
  • , Ross Koppel
  • , Catalina Martinez-Costa
  • , Øystein Nytrø
  • , Jihad S. Obeid
  • , Jose Parente de Oliveira
  • , Alan Ruttenberg
  • , Selja Seppälä
  • , Barry Smith
  • , Dagobert Soergel
  • , Jie Zheng
  • , Stefan Schulz
  • National Institutes of Health
  • ONTOPRO
  • Ars Semantica Ltd.
  • University of Florida
  • Johns Hopkins University Applied Physics Laboratory
  • Medical College of Wisconsin
  • CUBRC
  • University at Buff alo
  • University of Pennsylvania
  • University of Murcia
  • University of Tromsø – The Arctic University of Norway
  • Norwegian University of Science and Technology
  • Medical University of South Carolina
  • Instituto Tecnológico de Aeronautica, Instituto de Estudos Avançados
  • SUNY Buffalo
  • University of Michigan Medical School
  • Medical University of Graz
  • Averbis GmbH

Research output: Contribution to journalArticlepeer-review

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.
Original languageEnglish
JournalStandards
DOIs
Publication statusPublished - 15 Sept 2023

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 12 - Responsible Consumption and Production
    SDG 12 Responsible Consumption and Production

Keywords

  • Repurposing
  • Quality (philosophy)
  • Data science
  • Context (archaeology)
  • Computer science
  • Usability
  • Translational research
  • Data quality
  • Knowledge management
  • White paper
  • Medicine
  • Engineering
  • Political science
  • Paleontology
  • Metric (unit)
  • Philosophy
  • Operations management
  • Epistemology
  • Pathology
  • Humancomputer interaction
  • Biology
  • Waste management
  • Law

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