Predicting and Reducing Re-admission to Hospital

Long-term conditions are a significant part of the NHS's work. Previous work by The King's Fund shows that many emergency admissions are of patients with conditions such as asthma, diabetes, chronic obstructive pulmonary disease, epilepsy, cellulitis and sickle cell disease. More effective primary care can reduce the risk of such patients being admitted.

PCTs face the ongoing challenge of allocating patients to appropriate 'at risk' groups – as set out by Department of Health guidelines – and specifically to identify the patients who would benefit most from intensive case management.

PARR is a software tool that can be used to identify high-risk individuals, whereas the Combined Predictive Model identifies the whole PCT population according to their risk of admission. These two products can help PCTs to intervene and reduce future hospital admissions.

Literature review

During the early stages of this project, we conducted a literature review which used international studies to summarise and assess the principal approaches to predicting risk within the health arena.

• Predictive risk project literature review: summary (98 kb)
• Predictive risk project literature review (186 kb)