Predicting who will use intensive social care: case finding tools based on linked health and social care data

This paper considers 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.

Journal article

Published: 20/01/2011

Journal article information

Abstract

Background

The costs of delivering health and social care services are rising as the population ages and more people live with chronic diseases.

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.