ArticleHealth expectations : an international journal of public participation in health care and health policy2025
Public Involvement to Enhance Care Home Research; Collaboration on a Minimum Data Set for Care Homes.
Article in Health expectations : an international journal of public participation in health care and health policy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Nursing Minimum Datasets in Long-Term Care Settings: Scoping Review.Journal of medical Internet research · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
19 authors.
Funding
Abstract
introductionInformation on care home residents in England is captured in numerous data sets (care home records, General Practitioner records, community nursing, etc.) but little of this information is currently analysed in a way that is useful for care providers, current or future residents and families or that realises the potential of data to enhance care provision. The DACHA study aimed to develop and test a minimum data set (MDS) which would bring together data that is useful to support and improve care and facilitate research. It is that utility that underscores the importance of meaningful public involvement (PI) with the range of groups of people affected. This paper analyses the involvement of family members of care home residents and care home staff through a PI Panel.
objectivesThe objective for the PI activities was to consistently bring the knowledge and perspectives of family members and care home staff to influence the ongoing design and conduct of the DACHA study.
methodsThe bespoke methods of PI included a dedicated PI team and a PI Panel of public contributors. Meetings were recorded and minutes agreed, resulting actions were tracked and reflections on the PI recorded. A democratic, social relations approach was used to frame the analysis.
resultsA PI panel met 17 times. All meetings included both family members and care home staff. Analysis of the records and reflections developed the following themes about the operation of the PI: deepened understanding of the data environment in care homes; Influence on the pilot MDS; aiming for best research practices with care homes; personal/professional development for PI members; expectations of the project. Learning points for future research projects are developed.
conclusionsPI shaped the design and conduct of the DACHA study, grounding it in the needs and perspectives of people using and providing social care. Data research has a huge responsibility to accurately incorporate relevant public perspectives. There is an implicit assumption that records and data are objective and 'speak for themselves' however there can be unintended consequences from introduction of new data requirements in practice. PATIENT OR PUBLIC CONTRIBUTION: Public contributors to this manuscript include family members of older people living in care homes and staff of care homes. The wider study also involved as the public, older people living in care homes. Public contributors helped develop the project, contributed throughout the conduct of the study and some chose to be involved in preparing this manuscript.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.