Research summary & report
24 Feb 2011
Project:
Predicting future costs of social care
Nuffield Trust Data Lab: exploiting existing information in new ways
Uses of predictive risk adjustment in the NHS
Area of work:
Commissioning, Predictive risk, Research methods & information tools

With the costs of caring for people with complex social care and health care needs set to rise in the UK in the coming years, it is becoming increasingly important to find ways of helping local councils and health services to take earlier action to support people to remain independent and stay in their own homes. This report presents the findings of research into whether predictive risk models could be used in social care to predict an individual person’s future need for intensive social care.

Summary

Being able to identify those people most at risk of beginning high-cost care so that they might be offered intensive ‘upstream’ preventive care and support could potentially promote independent living and be more cost-effective. One way of identifying people who are at high risk is with predictive risk models.

Predictive models are increasingly being used in health care to identify people at high risk of unplanned hospital admission, so that preventive care can be effectively targeted.

In addition to the predictive models we developed, this work generated important lessons about the potential of linked health and social care data to support policy analysis and to guide the planning and commissioning of services. This report, by Dr Martin Bardsley, Professor John Billings, Ludovic Jean Chassin, Dr Jennifer Dixon, Elizabeth Eastmure, Theo Georghiou, Dr Geraint Lewis, Adam Steventon, will be of interest to health and social care policy-makers, senior managers and practitioners, and others involved in commissioning, as well as academics and students in the fields of health care and social policy.

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