Automated screening of natural language in electronic health records for the diagnosis septic shock is feasible and outperforms an approach based on explicit administrative codes.

Journal: Journal of critical care
Published Date: Apr 1, 2020

Abstract

PURPOSE: Identification of patients for epidemiologic research through administrative coding has important limitations. We investigated the feasibility of a search based on natural language processing (NLP) on the text sections of electronic health records for identification of patients with septic shock.

Authors

  • Joris Vermassen
    Ghent University Hospital, Department of Intensive Care Medicine, Belgium. Electronic address: Joris.vermassen@uzgent.be.
  • Kirsten Colpaert
    Department of Intensive Care Medicine, Ghent University Hospital, De Pintelaan 185, 2 K12 IC, B-9000 Ghent, Belgium.
  • Liesbet De Bus
    Ghent University Hospital, Department of Intensive Care Medicine, Belgium.
  • Pieter Depuydt
    Ghent University Hospital, Department of Intensive Care Medicine, Belgium; Ghent University, Faculty of Medicine and Health Sciences, Belgium.
  • Johan Decruyenaere
    Department of Intensive Care Medicine, Ghent University Hospital, De Pintelaan 185, 2 K12 IC, B-9000 Ghent, Belgium; Department of Internal Medicine, Ghent University, De Pintelaan 185, B-9000 Ghent, Belgium.

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