Patient participation impacts outcome domain selection in core outcome sets for research: an updated systematic review.

COMET Comparative effectiveness research Core outcome sets Outcomes Patient participation Randomized controlled trials Taxonomy

Journal

Journal of clinical epidemiology
ISSN: 1878-5921
Titre abrégé: J Clin Epidemiol
Pays: United States
ID NLM: 8801383

Informations de publication

Date de publication:
Jun 2023
Historique:
received: 06 12 2022
revised: 17 03 2023
accepted: 25 03 2023
medline: 17 7 2023
pubmed: 14 4 2023
entrez: 13 4 2023
Statut: ppublish

Résumé

The importance of including patients, carers, and the public in health research is well recognized, including the need to consider outcomes in health care research that reflect the priorities of patients. Core outcome sets (COS) define the minimum set of outcomes that should be measured and reported in research of a given condition, determined through consensus among key stakeholders. The Core Outcome Measures in Effectiveness Trials Initiative undertakes an annual systematic review (SR) to identify newly published COS to update its online database of COS for research. The objective of this study was to assess the impact of patient participation on COS. SR methods used in previous updates were applied to identify research studies published or indexed in 2020 and 2021 (conducted as separate reviews) that report development of a COS, regardless of any specifications relating to condition, population, intervention, or setting. Studies were assessed according to published standards for COS development, and core outcomes extracted from study publications were categorized according to an outcome taxonomy and added to an existing database of core outcome classifications of all previously published COS. The effect of patient participation on core domains was examined. Searches identified 56 new studies published in 2020 and 54 in 2021. All studies met all four minimum standards for scope, and 42 (75%) of the 2020 studies and 45 (83%) of the 2021 studies met all three standards for stakeholders involved. However, only 19 (34%) of the 2020 studies and 18 (33%) of the 2021 studies met all four standards for the consensus process. COS that involved patients or their representatives are more likely to include life impact outcomes (239, 86%) than COS without patient participation (193, 62%). Physiological/clinical outcomes are almost always specified at a granular level, whereas life impact outcomes are often described at a higher level. This study adds to the body of evidence demonstrating the importance and impact of including patients, carers, and the public in COS development, in particular by demonstrating that the impact of interventions on patients' lives is more likely to be represented in COS that involve patients or their representatives. COS developers are encouraged to pay increased attention to methods and reporting relating to the consensus process. Further work is required to understand the appropriateness and rationale for the discrepancy in granularity levels between outcome domains.

Identifiants

pubmed: 37054902
pii: S0895-4356(23)00073-2
doi: 10.1016/j.jclinepi.2023.03.022
pii:
doi:

Types de publication

Systematic Review Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

127-133

Informations de copyright

Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.

Auteurs

Susanna Dodd (S)

Department of Health Data Science, University of Liverpool, Liverpool L63 3GL, UK. Electronic address: s.r.dodd@liv.ac.uk.

Sarah L Gorst (SL)

Department of Health Data Science, University of Liverpool, Liverpool L63 3GL, UK.

Amber Young (A)

Bristol Centre for Surgical Research, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; Children's Burns Research Centre Bristol, University Hospitals Bristol and Weston NHS Foundation Trust, Bristol, UK.

Samuel W Lucas (SW)

Department of Health Data Science, University of Liverpool, Liverpool L63 3GL, UK.

Paula R Williamson (PR)

Department of Health Data Science, University of Liverpool, Liverpool L63 3GL, UK.

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