ACG-modell kan förutsäga vilka som blir högkonsumenter av sjukvård. Vårdresurser kan användas klokare, individer i riskzon kan få
bättre vård
Sammanfattning
We describe a method, which uses already existent administrative data to identify individuals with a high risk of a large need of
healthcare in the coming year. The model is based on the ACG (Adjusted Clinical Groups) system to identify the high-risk patients. We have
set up a model where we combine the ACG system stratification analysis tool RUB (Resource Utilization Band) and Probability High Total
Cost >0.5. We tested the method with historical data, using 2 endpoints, either >19 physical visits anywhere in the healthcare system in the
coming 12 months or more than 2 hospital admissions in the coming 12 months. In the region of Västra Götaland with 1.6 million
inhabitants, 5.6% of the population had >19 physical visits during a 12 month period and 1.2% more than 2 hospital admissions. Our model
identified approximately 24 000 individuals of whom 25.7% had >19 physical visits and 11.6% had more than 2 hospital admissions in the
coming 12 months. We now plan a small test in ten primary care centers to evaluate if the model should be introduced in the entire Västra
Götaland region.