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Predictive Risk Modelling for Integrated Care: A Structured Review

Profile image of Thierry ChaussaletThierry Chaussalet

2016, 2016 IEEE 29th International Symposium on Computer-Based Medical Systems (CBMS)

https://doi.org/10.1109/CBMS.2016.34
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Abstract

If patients at risk of admission or readmission to hospital or other forms of care could be identified and offered suitable early interventions then their lives and longterm health may be improved by reducing the chances of future admission or readmission to care, and hopefully, their cost of care reduced. Considerable work has been carried out in this subject area especially in the USA and the UK. This has led for instance to the development of tools such as PARR, PARR-30, and the Combined Predictive Model for prediction of emergency readmission or admission to acute care. Here we perform a structured review the academic and grey literature on predictive risk tools for social care utilisation, as well as admission and readmission to general hospitals and psychiatric hospitals. This is the first phase of a project in partnership with Docobo Ltd and funded by Innovate UK, in which we seek to develop novel predictive risk tools and dashboards to assist commissioners in Clinical Commissioning Groups with the triangulation of the intelligence available from routinely collected data to optimise integrated care and better understand the complex needs of individuals.

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