Using natural language processing to understand, facilitate and maintain continuity in patient experience across transitions of care.

Journal: International journal of medical informatics
Published Date: Nov 11, 2021

Abstract

BACKGROUND: Patient centred care necessitates that healthcare experiences and perceived outcomes be considered across all transitions of care. Information encoded within free-text patient experience comments relating to transitions of care are not captured in a systematic way due to the manual resource required. We demonstrate the use of natural language processing (NLP) to extract meaningful information from the Friends and Family Test (FFT).

Authors

  • Mustafa Khanbhai
    Patient Safety Translational Research Centre, Imperial College of Science Technology and Medicine, London, UK m.khanbhai@imperial.ac.uk.
  • Leigh Warren
    Patient Safety Translational Research Centre, Institute of Global Health Innovation, Imperial College London, London, UK.
  • Joshua Symons
    Big Data and Analytical Unit, Imperial College of Science Technology and Medicine, London, UK.
  • Kelsey Flott
    Patient Safety Translational Research Centre, Imperial College of Science Technology and Medicine, London, UK.
  • Stephanie Harrison-White
    Patient Experience and Improvement, Imperial College NHS Healthcare Trust, London, UK.
  • Dave Manton
    Patient Safety Translational Research Centre, Institute of Global Health Innovation, Imperial College London, London, UK.
  • Ara Darzi
    Imperial College London London UK.
  • Erik Mayer
    Patient Safety Translational Research Centre, Imperial College of Science Technology and Medicine, London, UK.

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