| Predicting who will use intensive social care: case finding tools based on linked health and social care data. | |
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MedLine Citation:
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PMID: 21252036 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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BACKGROUND: the costs of delivering health and social care services are rising as the population ages and more people live with chronic diseases. 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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Authors:
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Martin Bardsley; John Billings; Jennifer Dixon; Theo Georghiou; Geraint Hywel Lewis; Adam Steventon |
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Publication Detail:
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Type: JOURNAL ARTICLE Date: 2011-1-20 |
Journal Detail:
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Title: Age and ageing Volume: - ISSN: 1468-2834 ISO Abbreviation: - Publication Date: 2011 Jan |
Date Detail:
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Created Date: 2011-1-21 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 0375655 Medline TA: Age Ageing Country: - |
Other Details:
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Languages: ENG Pagination: - Citation Subset: - |
Affiliation:
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The Nuffield Trust, 59 New Cavendish Street, London W1G 7LP, UK. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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