What is measured matters: A scoping review of analysis methods used for qualitative patient reported experience measure data.

Natural language processing Patient reported experience measures Qualitative research Routinely collected heath data

Journal

International journal of medical informatics
ISSN: 1872-8243
Titre abrégé: Int J Med Inform
Pays: Ireland
ID NLM: 9711057

Informations de publication

Date de publication:
18 Jul 2024
Historique:
received: 26 11 2023
revised: 11 07 2024
accepted: 16 07 2024
medline: 21 7 2024
pubmed: 21 7 2024
entrez: 20 7 2024
Statut: aheadofprint

Résumé

Hospitals are increasingly turning to patients for valuable feedback regarding their care experience. A common method to collect this information is patient reported experience measures (PREMs) surveys. Health care workers report qualitative PREMs as more interesting, relevant, and informative than quantitative survey responses. However, a major barrier to utilising qualitative PREMs data to drive quality improvements is a lack of resources to analyse the data. This scoping review aimed to review the methods used to analyse qualitative PREMs survey data from routine hospital care. We utilised the JBI scoping review methodology, and searched four databases for articles from 2013 to 2023 which analysed qualitative PREMs survey data from routine care in hospitals. Study characteristics were extracted, as well as the analysis method - specifically, whether the study used traditional manual analysis methods in which the researcher reads the text and categorise the data, or automated methods utilising computers and algorithms to read and categorise the data. From 960 unique articles, 123 went through full-text review and 54 were deemed eligible. 75.9 % used only manual content analysis methods to analyse the qualitative responses, 16.7 % of studies used a combination of manual and automated methods, and only 7.4 % used exclusively automated methods. Automated methods were used in 27.5 % of studies published 2019-2023, compared to 14.3 % of studies published 2013-2018. All bar one study using automated methods focused on investigating the validity of the automated methodology or used it to complement manual content analysis. The studies included in this review show a transition from traditional time-consuming manual analyses to computerised methods enabling analysis at a larger scale. As the volume of PREMs data collected grows, efficient and effective ways to analyse qualitative PREMs data at scale are required to enable health services to capture the patient voice and drive consumer-centred improvements in care.

Identifiants

pubmed: 39032453
pii: S1386-5056(24)00222-3
doi: 10.1016/j.ijmedinf.2024.105559
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

105559

Informations de copyright

Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Teyl Engstrom (T)

Queensland Digital Health Centre, Centre for Health Services Research, The University of Queensland, Herston, QLD, Australia. Electronic address: t.engstrom@uq.edu.au.

Max Shteiman (M)

The University of Queensland-Ochsner Clinical School, Brisbane, QLD, Australia.

Kim Kelly (K)

Qualitative Research Center of Excellence, IQVIA, Tucson, AZ, USA.

Clair Sullivan (C)

Queensland Digital Health Centre, Centre for Health Services Research, The University of Queensland, Herston, QLD, Australia; Royal Brisbane and Women's Hospital, Herston, QLD, Australia.

Jason D Pole (JD)

Queensland Digital Health Centre, Centre for Health Services Research, The University of Queensland, Herston, QLD, Australia; The University of Toronto, Dalla Lana School of Public Health, Toronto, ON, Canada.

Classifications MeSH