Improving documentation of presenting problems in the emergency department using a domain-specific ontology and machine learning-driven user interfaces.

Journal: International journal of medical informatics
PMID: 31605881

Abstract

OBJECTIVES: To determine the effect of a domain-specific ontology and machine learning-driven user interfaces on the efficiency and quality of documentation of presenting problems (chief complaints) in the emergency department (ED).

Authors

  • Nathaniel R Greenbaum
    Division of Clinical Informatics, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, United States.
  • Yacine Jernite
    Department of Computer Science, Courant Institute of Mathematical Sciences, New York University, New York, New York, United States of America.
  • Yoni Halpern
    Department of Computer Science, New York University, New York, NY, USA dsontag@cs.nyu.edu.
  • Shelley Calder
    Department of Emergency Medicine, Beth Israel Deaconess Medical Center, Boston, MA, United States.
  • Larry A Nathanson
    Department of Emergency Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, United States of America.
  • David A Sontag
    Department of Electrical Engineering and Computer Science, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.
  • Steven Horng
    Department of Emergency Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA dsontag@cs.nyu.edu.

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