Learn more about Brian Crick, MBA

Author Bio

Brian Crick, MBA

Brian Crick became the Pulse Heart Institute's Heart Failure and Arrhythmia Manager in May 2016. He moved to Washington state and started working at MultiCare in January 2014 managing their four Sleep Center sites across the system with locations in Tacoma, Puyallup, Auburn, and South Hill before taking the Heart Failure and Arrhythmia Manager position. Brian is responsible for the system-wide leadership of the Heart Failure and Arrhythmia programs as well as our Tacoma and Good Samaritan EP/Device Clinics. Brian will work with his Cardiology partners to develop and promote these programs in our communities through Pulse. He is a graduate of Louisiana State University where he earned his MBA degree. He earned his undergraduate degree in Health Sciences at Northern Arizona University. Prior to moving to Washington Brian's career in healthcare began as a Respiratory Therapist at Oro Valley Hospital in Tucson, Arizona before he began managing physician practices and sleep centers for Oro Valley Hospital, Northwest Allied Physicians, Desert Cardiology, and MD-Sleep in the Tucson area. During that time, he also worked as an adjunct faculty instructor for Pima Community College's Respiratory Therapy program. In his time off he enjoys spending time with his wife and three daughters as well as running, hiking, and biking.

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Brian Crick, MBA
Holly Burke
Needham Ward, MD

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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