Clinical research staff perceptions on a natural language processing-driven tool for eligibility prescreening: An iterative usability assessment.

Journal: International journal of medical informatics
PMID: 36638583

Abstract

BACKGROUND: Participant recruitment is a barrier to successful clinical research. One strategy to improve recruitment is to conduct eligibility prescreening, a resource-intensive process where clinical research staff manually reviews electronic health records data to identify potentially eligible patients. Criteria2Query (C2Q) was developed to address this problem by capitalizing on natural language processing to generate queries to identify eligible participants from clinical databases semi-autonomously.

Authors

  • Betina Idnay
    School of Nursing, Columbia University, New York, New York, USA.
  • Yilu Fang
    Department of Biomedical Informatics.
  • Caitlin Dreisbach
    University of Virginia, School of Nursing, Charlottesville, VA, USA; University of Virginia, Data Science Institute, Charlottesville, VA, USA.
  • Karen Marder
    Columbia University, Department of Neurology, New York, NY, USA.
  • Chunhua Weng
    Department of Biomedical Informatics, Columbia University.
  • Rebecca Schnall
    School of Nursing, Columbia University, New York, New York, USA.

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