Our client wanted to integrate care for patients and fund it through a capitated budget. This type of budget is used to pay for all the care required by a group of patients, rather than individuals. We were engaged to identify those patients who would benefit most from this approach. The data available was often of poor quality, and in some cases missing, so it was essential that any assumptions used were agreed with stakeholders.

We tested two approaches to selecting patients: risk banding and Quality and Outcomes Framework condition groups. We tracked individual patients’ data through all available patient level datasets. The data was validated and reconciled, then then costed, using agreed assumptions where unit costs were not available. Where patient level data was not available, agreed assumptions were applied to aggregate data.

This bespoke analysis gave us a way of selecting patients who would most benefit from integrated care and a way of predicting the effect of different models. This will enable CCGs to improve care for patients who need this most and understand the impact on commissioner and provider income and spend.