Case Study

Artificial Intelligence Improves Accuracy of Heart Failure Readmission Risk Predictions

Artificial Intelligence Improves Accuracy of Heart Failure Readmission Risk Predictions

Pages 8 Pages

Copyright © 2018 Health Catalyst 1 Artificial Intelligence Improves Accuracy of Heart Failure Readmission Risk Predictions Success Story EXECUTIVE SUMMARY A global pandemic, heart failure (HF) affects at least 26 million people worldwide, and its prevalence only continues to increase. Within the U.S. alone, 5.7 million adults live with HF, carrying a cost of nearly $30.7 billion each year. At 55 percent, HF represents the most common cause of Medicare readmissions, and HF accounts for 42 percent of total admissions for Medicare patients. Readmissions for HF carry a heavy cost for patients and health systems, in addition to reimbursement penalties from CMS. This makes properly assessing the risk for readmission for patients with HF a top priority. MultiCare Health System leveraged

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