Case Study: Västra Götalandsregionen improves discharge decisions with Capgemini AI analytics

Västra Götalandsregionen uses AI to make better discharge decisions

Vastra Gotalandsregionen, a public healthcare provider in Sweden, faced the challenge of managing limited ward capacity. Doctors needed to prioritize patient discharges without increasing the risk of readmission, a complex task requiring the manual analysis of vast amounts of patient data. They collaborated with Capgemini subsidiary Advectas on an Analytics Jumpstart pilot project to explore a potential solution.

Capgemini developed a machine learning model that analyzed patient medical data, demographics, and prescriptions to predict the likelihood of a patient being readmitted within 14 days of discharge. The solution achieved a 40% precision rate in predicting relapse and successfully identified half of all relapse patients. This provided doctors with more effective guidance for discharge decisions, enabling better resource management and patient care.

Vastra Gotalandsregionen