Identifying Patient-Reported Care Experiences in Free-Text Survey Comments: Topic Modeling Study.

Journal: JMIR medical informatics
Published Date: Feb 24, 2025

Abstract

BACKGROUND: Patient-reported experience surveys allow administrators, clinicians, and researchers to quantify and improve health care by receiving feedback directly from patients. Existing research has focused primarily on quantitative analysis of survey items, but these measures may collect optional free-text comments. These comments can provide insights for health systems but may not be analyzed due to limited resources and the complexity of traditional textual analysis. However, advances in machine learning-based natural language processing provide opportunities to learn from this traditionally underused data source.

Authors

  • Brian Steele
    Centre for Health Informatics, Cumming School of Medicine, University of Calgary, Cal Wenzel Precision Health Building, 3280 Hospital Dr NW, Calgary, AB, T2N 4Z6, Canada, 1 403-220-5110.
  • Paul Fairie
    Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.
  • Kyle Kemp
    Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
  • Adam G D'Souza
    Centre for Health Informatics, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.
  • Matthias Wilms
    Department of Radiology, University of Calgary, Calgary, AB, Canada.
  • Maria Jose Santana
    Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.

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