The effects of natural language processing on cross-institutional portability of influenza case detection for disease surveillance.

Journal: Applied clinical informatics
Published Date: May 31, 2017

Abstract

OBJECTIVES: This study evaluates the accuracy and portability of a natural language processing (NLP) tool for extracting clinical findings of influenza from clinical notes across two large healthcare systems. Effectiveness is evaluated on how well NLP supports downstream influenza case-detection for disease surveillance.

Authors

  • Jeffrey P Ferraro
    School of Medicine, University of Utah, Salt Lake City, Utah, US.
  • Ye Ye
    Department of Biomedical Informatics, University of Pittsburgh School of Medicine, 5607 Baum Boulevard, Pittsburgh, PA, United States; Intelligent System Program, University of Pittsburgh Dietrich School of Arts and Sciences, 210 South Bouquet Street, Pittsburgh, PA, United States.
  • Per H Gesteland
  • Peter J Haug
    Department of Biomedical Informatics, University of Utah, 421 Wakara Way, Salt Lake City, UT 84108, USA; Homer Warner Research Center, Intermountain Healthcare, 5121 South Cottonwood Street, Murray, UT 84107, USA.
  • Fuchiang Rich Tsui
    Department of Biomedical Informatics, University of Pittsburgh School of Medicine, 5607 Baum Boulevard, Pittsburgh, PA, United States; Intelligent System Program, University of Pittsburgh Dietrich School of Arts and Sciences, 210 South Bouquet Street, Pittsburgh, PA, United States. Electronic address: tsui2@pitt.edu.
  • Gregory F Cooper
    University of Pittsburgh, Pittsburgh, PA, USA.
  • Rudy Van Bree
  • Thomas Ginter
  • Andrew J Nowalk
  • Michael Wagner

Keywords

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