Categorising patient concerns using natural language processing techniques.

Journal: BMJ health & care informatics
PMID: 34193519

Abstract

OBJECTIVES: Patient feedback is critical to identify and resolve patient safety and experience issues in healthcare systems. However, large volumes of unstructured text data can pose problems for manual (human) analysis. This study reports the results of using a semiautomated, computational topic-modelling approach to analyse a corpus of patient feedback.

Authors

  • Paul Fairie
    Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.
  • Zilong Zhang
    School of Computer Science and Technology, Hainan University, Haikou 570228, China.
  • Adam G D'Souza
    Centre for Health Informatics, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.
  • Tara Walsh
    Alberta Health Services, Calgary, Alberta, Canada.
  • Hude Quan
    Department of Community Health Sciences, University of Calgary, Calgary, Canada.
  • Maria J Santana
    Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada mjsantan@ucalgary.ca.

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