Case Study: Large Hospital Group achieves 6,000 fewer readmissions and $76M in savings with Cloudera

Intel and Cloudera Use Predictive Analytics to Help a Large Hospital Group Reduce Readmission Rates

A large Hospital Group faced pressure from federal readmission penalties and rising healthcare costs to cut readmission rates (targeting a 3% annual reduction) while improving patient outcomes and operational efficiency. The challenge was to identify, at admission, which patients were most likely to be readmitted so the hospital could provide targeted follow-up care and avoid costly Medicare penalties.

Working with Intel and Cloudera, the hospital built an enterprise data hub that links EMR and socioeconomic data and uses Random Forests to assign a readmission risk score at admission, flagging the top 5% as high risk. By targeting extra care to those patients, the program correctly identifies high‑risk cases with 50–65% accuracy (versus <20% for random sampling) and yields annual benefits: ~6,000 fewer readmissions, ~$4M in avoided Medicare penalties, about $72M saved in medical costs, better resource utilization, and improved hospital ratings.