Journal
AGE AND AGEING
Volume 40, Issue 2, Pages 265-270Publisher
OXFORD UNIV PRESS
DOI: 10.1093/ageing/afq181
Keywords
algorithms; risk assessment; methods; risk assessment; standards; risk factors; residential facilities; elderly
Categories
Funding
- Care Services Efficiency Delivery (CSED)
- Department of Health, London
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Objectives: to determine whether predictive risk models can be built that use routine health and social care data to predict which older people will begin receiving intensive social care. Design: analysis of pseudonymous, person-level, data extracted from the administrative data systems of local health and social care organisations. Setting: five primary care trust areas in England and their associated councils with social services responsibilities. Subjects: people aged 75 or older registered continuously with a general practitioner in five selected areas of England (n = 155,905). Methods: multivariate statistical analysis using a split sample of data. Results: it was possible to construct models that predicted which people would begin receiving intensive social care in the coming 12 months. The performance of the models was improved by selecting a dependent variable based on a lower cost threshold as one of the definitions of commencing intensive social care. Conclusions: predictive models can be constructed that use linked, routine health and social care data for case finding in social care settings.
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