Identification of unmet palliative care needs of nursing home residents: A scoping review protocol.


Journal

PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081

Informations de publication

Date de publication:
2024
Historique:
received: 03 04 2024
accepted: 26 06 2024
medline: 8 8 2024
pubmed: 8 8 2024
entrez: 8 8 2024
Statut: epublish

Résumé

Nursing home residents often have life limiting illnesses in combination with multiple comorbidities, cognitive deficits, and frailty. Due to these complex characteristics, a high proportion of nursing home residents require palliative care. However, many do not receive palliative care relative to this need resulting in unmet care needs. To the best of our knowledge, there have been no literature reviews to synthesise the evidence on how nursing home staff identify unmet palliative care needs and to determine what guidelines, policies, and frameworks on identifying unmet palliative care needs of nursing home residents are available. The aim of this scoping review is to map and summarise the evidence on identifying unmet palliative care needs of residents in nursing homes. This scoping review will be guided by the JBI Manual for Evidence Synthesis. The search will be conducted in CINAHL, MEDLINE, Embase, Web of Science, APA PsycINFO, and APA PsycArticles. A search of grey literature will also be conducted in databases such as CareSearch, Trip, GuidelineCentral, ClinicalTrials.gov, and the National Institute for Health and Care and Excellence website. The search strategy will be developed in conjunction with an academic librarian. Piloting of the screening process will be conducted to ensure agreement among the team on the eligibility criteria. Covidence software will be used to facilitate deduplication, screening, and blind reviewing. Four reviewers will conduct title and abstract screening. Six reviewers will conduct full text screening. Any conflicts will be resolved by a reviewer not involved in the conflict. One reviewer will conduct data extraction using pre-established data extraction tables. Results will be synthesised, and a narrative synthesis will be used to illustrate the findings of this review. Data will be presented visually using tables, figures, and word clouds, as appropriate.

Identifiants

pubmed: 39116114
doi: 10.1371/journal.pone.0306980
pii: PONE-D-24-11649
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0306980

Informations de copyright

Copyright: © 2024 Crowley et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

Auteurs

Patrice Crowley (P)

Catherine McAuley School of Nursing and Midwifery, University College Cork, Cork, Ireland.

Mohamad M Saab (MM)

Catherine McAuley School of Nursing and Midwifery, University College Cork, Cork, Ireland.

Nicola Cornally (N)

Catherine McAuley School of Nursing and Midwifery, University College Cork, Cork, Ireland.

Isabel Ronan (I)

School of Computer Science and Information Technology, University College Cork, Cork, Ireland.

Sabin Tabirca (S)

School of Computer Science and Information Technology, University College Cork, Cork, Ireland.

David Murphy (D)

School of Computer Science and Information Technology, University College Cork, Cork, Ireland.

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Classifications MeSH