Early identification of patients with acute gastrointestinal bleeding using natural language processing and decision rules.

Journal: Journal of gastroenterology and hepatology
Published Date: Jun 1, 2021

Abstract

BACKGROUND AND AIM: Guidelines recommend risk stratification scores in patients presenting with gastrointestinal bleeding (GIB), but such scores are uncommonly employed in practice. Automation and deployment of risk stratification scores in real time within electronic health records (EHRs) would overcome a major impediment. This requires an automated mechanism to accurately identify ("phenotype") patients with GIB at the time of presentation. The goal is to identify patients with acute GIB by developing and evaluating EHR-based phenotyping algorithms for emergency department (ED) patients.

Authors

  • Dennis Shung
    Yale School of Medicine Section of Digestive Diseases, P.O. Box 208019, New Haven, CT, 06520-8019, USA. dennis.shung@yale.edu.
  • Cynthia Tsay
    Yale School of Medicine, New Haven, Connecticut, USA.
  • Loren Laine
    Section of Digestive Diseases, Department of Medicine, Yale School of Medicine, New Haven, USA.
  • David Chang
    Yale Center for Medical Informatics, Yale University.
  • Fan Li
    Department of Instrument Science and Engineering, School of SEIEE, Shanghai Jiao Tong University, Shanghai 200240, China.
  • Prem Thomas
    Yale School of Medicine, New Haven, Connecticut, USA.
  • Caitlin Partridge
    Clinical Informatics, Yale-New Haven Health System, New Haven, Connecticut, USA.
  • Michael Simonov
    Yale School of Medicine Section of Digestive Diseases, P.O. Box 208019, New Haven, CT, 06520-8019, USA.
  • Allen Hsiao
    Yale School of Medicine, New Haven, Connecticut, USA.
  • J Kenneth Tay
    Stanford University, Palo Alto, California.
  • Andrew Taylor
    From the Departments of Urology (T.C., M.U., H.C.C., M.S.) and Radiology and Biomedical Imaging (J.M., M.P.K., A.T., P.J., R.G., S.W.), University of California, San Francisco. 505 Parnassus Ave, M-391, San Francisco, CA 94143; and Division of Urology, Faculty of Medicine, King Chulalongkorn Memorial Hospital, Chulalongkorn University, The Thai Red Cross Society, Bangkok, Thailand (M.U.).

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