How to automatically turn patient experience free-text responses into actionable insights: a natural language programming (NLP) approach.

Journal: BMC medical informatics and decision making
Published Date: May 27, 2020

Abstract

BACKGROUND: Patient experience surveys often include free-text responses. Analysis of these responses is time-consuming and often underutilized. This study examined whether Natural Language Processing (NLP) techniques could provide a data-driven, hospital-independent solution to indicate points for quality improvement.

Authors

  • Simone A Cammel
    IT Department, Leiden University Medical Center, Albinusdreef 2, Postbus 9600, Postzone D-01-P, 2300 RC, Leiden, The Netherlands. s.cammel@lumc.nl.
  • Marit S De Vos
    Department of Surgery, Leiden University Medical Center, Leiden, The Netherlands.
  • Daphne van Soest
    Department of Quality and Patient Safety, Leiden University Medical Center, Leiden, The Netherlands.
  • Kristina M Hettne
    Department of Human Genetics, Leiden University Medical Center, PO Box 9600, 2300 RC Leiden, The Netherlands.
  • Fred Boer
    Department of Quality and Patient Safety, Leiden University Medical Center, Leiden, The Netherlands.
  • Ewout W Steyerberg
    Department of Biomedical Data Sciences, Leiden University Medical Centre, Albinusdreef 2, Leiden, 2333 ZA The Netherlands.
  • Hileen Boosman
    Department of Quality and Patient Safety, Leiden University Medical Center, Leiden, The Netherlands.

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