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Predictive validity of tools used to assess the risk of unplanned admissions: a rapid review of the evidence

Published: June 1, 2014
Category: Reports
Authors: Paton F, Wilson P, Wright K
Country: United Kingdom
Language: null
Type: Care Management
Settings: Academic, Hospital

York, UK: University of York.

University of York, York, UK

CRD has developed an evidence briefing and support service tailored to the needs of commissioners and NHS managers (as part of the NIHR CLAHRC for Leeds York and Bradford). The service identifies, appraises and contextualises existing research evidence to inform the real world issues brought to us by local decision makers. Feedback on this service from NHS partners has been positive and we have helped some achieve major cost savings through evidence informed service reconfiguration. The context for this particular briefing emerged from informal discussions between the evidence briefing team and John Young, the National Clinical Director for Integration and Frail & Elderly Care about evidence relating to methods and services that might be used to reduce the need for hospital admission for older people. From these discussions, a synthesis of the available evidence relating to the predictive validity of tools used to assess the risk of unplanned admissions emerged. In 2011, the Department of Health moved from a policy of recommendation to one that embraced the plethora of prediction tools available. There are now a number of predictive tools available from commercial or academic providers and as such it was felt that a summary of their comparative performance would be of benefit. Our aim therefore was to conduct a rapid synthesis of evidence assessing the predictive ability of tools used to identify frail elderly and people living with multiple long-term chronic health conditions who are at risk of future unplanned hospital admissions. It should be noted that predicting the risk of future hospital readmissions are not the focus of this work. The performance of such models has already been subject to systematic review (see for example Kansagara, 2011).

United Kingdom,Predictive Risk Modeling,Cost Burden Evaluation,Practice Patterns Comparison,Age

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