Predicting who will use intensive social care: case finding tools based on linked health and social care data
Predicting who will use intensive social care: case finding tools based on linked health and social care data
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DOI：
10.1093/ageing/afq181
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发表时间：
2011-03-01
期刊：
影响因子：
6.7
通讯作者：
Steventon, Adam
中科院分区：
文献类型：
--
作者：
Bardsley, Martin;Billings, John;Steventon, Adam
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.
