With the pressure of commissioning for value comes the need to understand the current and future health needs of your local populations. Risk adjustment and case-mix are tools that can help CCGs set budgets or capitation rates and evaluate provider performance.
The traditional approach to benchmarking something like emergency admission rates would compare GP practices to the CCG average. However, this takes no account of differences in case-mix between different GP practices, and so doesn’t reflect the impact of morbidity and multimorbidity on service demand. By using case-mix you get a much more insightful picture of practice performance. This is based not just on comparison of actual activity across the CCG but on what the patient data expects from each practice, based on the morbidity of their populations.
This graph shows the emergency admission rate for each GP practice and the orange line shows the CCG average. Because the population sizes are going to differ for each practice, the report shows the number of admissions per 1,000 patients.
If we only compare practice rates with the CCG average, it appears that practices 2, 3, 4, 6, 7 and 10 are performing worse than the others.
But when you compare the actual practice rates with their expected rates when their case-mix is taken into account a different picture emerges. Some practices with high emergency admission rates are actually performing as well as or even better than some of those with lower rates. And some practices with seemingly low rates are actually performing worse than you would expect for the morbidity burden of their patient population.
Case-mix adjustment provides a fairer method of analysing variation in activity, and shows that opportunities for reducing activity are not necessarily among the GP practices with the highest activity levels.
Let’s now look at the opportunity for cost savings when actual activity is compared with the expected activity that has been case-mix adjusted.
This table uses primary and secondary care data processed by the Johns Hopkins ACG System to show actual and expected activity and expenditure for a 12 month period for a practice’s diabetic patients.
Where actual activity and costs exceed the case-mix adjusted expected amounts there may be potential to reduce activity counts and expenditure. Where significant opportunities appear you can use this intelligence to investigate how practices are commissioning secondary care or prescribing drugs.
A Whole System View
Different ways of visually representing case-mix adjusted activity data can give you insights as to potential areas that could benefit from further investigation, while year-on-year data can highlight the effects of service changes. In this example, fewer than expected GP visits and prescribing activity might well have contributed to higher than expected A&E attendances and emergency admissions.
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