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Author Bio

Holly Burke

Holly Burke is the Director Clinical Innovation and Quality at MultiCare Health System. She has been with MultiCare since 2012 with previous roles as Heart Failure Program Manager, Project Manager, and Administrative Fellow for Strategy & Business Development. Holly has a master's degree in health policy administration from Washington State University and a bachelor's degree in healthcare administration from Idaho State University.

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Brian Crick, MBA
Holly Burke
Dr. Needham Ward

How to Apply Machine Learning in Healthcare to Reduce Heart Failure Readmissions

One large healthcare system in the Pacific Northwest is moving machine learning technology from theory to practice. MultiCare Health System is using machine learning to develop a predictive model for reducing heart failure readmissions. Starting with 88 predictive variables applied to data from 69,000 heart failure patient encounters, the machine learning team has been able to quickly develop and refine a predictive model.
The output from the model has guided resource allocation efforts and pre-discharge decision making to significantly improve patient care management activities. And the data has engendered trust among clinicians who rely on it the most for clinical decision making.
This inside look at the application of advanced technology offers lessons for any healthcare system planning to ramp up its machine learning and predictive analytics efforts.

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