Burton, J. K. , Ciminata, G., Lynch, E., Shenkin, S. D., Geue, C. and Quinn, T. J. (2022) Understanding Pathways into Care homes using Data (UnPiCD study): a retrospective cohort study using national linked health and social care data. Age and Ageing, 51(12), afac304. (doi: 10.1093/ageing/afac304) (PMID:36580557) (PMCID:PMC9799248)
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Abstract
Background: Pathways into care are poorly understood but important life events for individuals and their families. UK policy is to avoid moving-in to care homes from acute hospital settings. This assumes that moves from secondary care represent a system failure. However, those moving to care homes from community and hospital settings may be fundamentally different groups, each requiring differing care approaches. Objective: To characterise individuals who move-in to a care home from hospital and compare with those moving-in from the community. Design and setting: A retrospective cohort study using cross-sectoral data linkage of care home data. Methods: We included adults moving-in to care homes between 1/4/13 and 31/3/16, recorded in the Scottish Care Home Census. Care home data were linked to general and psychiatric hospital admissions, community prescribing and mortality records to ascertain comorbidities, significant diagnoses, hospital resource use, polypharmacy and frailty. Multivariate logistic regression identified predictors of moving-in from hospital compared to from community. Results: We included 23,892 individuals moving-in to a care home, 13,564 (56.8%) from hospital and 10,328 (43.2%) from the community. High frailty risk adjusted Odds Ratio (aOR) 5.11 (95% Confidence Interval (CI): 4.60–5.68), hospital discharge with diagnosis of fracture aOR 3.91 (95%CI: 3.41–4.47) or stroke aOR 8.42 (95%CI: 6.90–10.29) were associated with moving-in from hospital. Discharge from in-patient psychiatry was also a highly significant predictor aOR 19.12 (95%CI: 16.26–22.48). Conclusions: Individuals moving-in to care homes directly from hospital are clinically distinct from those from the community. Linkage of cross-sectoral data can allow exploration of pathways into care at scale.
| Item Type: | Articles |
|---|---|
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Quinn, Professor Terry and Ciminata, Dr Giorgio and Geue, Dr Claudia and Burton, Dr Jenni |
| Authors: | Burton, J. K., Ciminata, G., Lynch, E., Shenkin, S. D., Geue, C., and Quinn, T. J. |
| College/School: | College of Medical Veterinary and Life Sciences > School of Cardiovascular & Metabolic Health College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > Health Economics and Health Technology Assessment |
| Journal Name: | Age and Ageing |
| Publisher: | Oxford University Press |
| ISSN: | 0002-0729 |
| ISSN (Online): | 1468-2834 |
| Published Online: | 29 December 2022 |
| Copyright Holders: | Copyright © 2022 The Authors |
| First Published: | First published in Age and Ageing 51(12): afac304 |
| Publisher Policy: | Reproduced under a Creative Commons License |
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