ArticleBMJ health & care informatics2026
Traversing the data landscape: insights and recommendations from a case study using novel linkage of care home and health data.
Article in BMJ health & care informatics, 2026. 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.
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Who cites it
1 citing paper in PubMed.
- Adopting and embedding home sensors in social care: findings from a mixed methods, rapid evaluation.NIHR open 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
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The insights available from linking routine health data have transformative potential for understanding and improving population health and well-being. However, cross-sectoral data linkage in the UK remains challenging, with persistent barriers around governance, interoperability and data quality.This Perspective paper draws on the experiences of the Developing research resources And minimum data set for Care Homes Adoption and use (DACHA) study which linked administrative health and social care records with records from care home software providers for over 700 older adult care home residents, an underserved population in research, in England to build a proof-of-concept minimum dataset.From our learning, we make eight recommendations for researchers, research funders, data owners, data controllers and policymakers to strengthen future data linkage across health and social care. We recommend: (1) sharing metadata to support transparency and efficient reuse; (2) clarifying purposes for data sharing; (3) streamlining information governance processes; (4) recognising the health and social care system as a research partner; (5) resourcing data quality at the point of collection; (6) acknowledging the work needed to adapt routine data for research; (7) standardising core variables for interoperability; and (8) designing linkage for wider public benefit and safe data reuse.Implementing these recommendations would help create a more coherent, efficient and equitable data landscape, realising the potential of existing data to improve care quality, research capacity and population health.
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Registered trials
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