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Machine Learning for Population Health
By Eric Bricker MD
Healthcare Machine Learning Company ClosedLoop.ai is One of the Best at Applying Machine Learning to Population Health Data.
ClosedLoop.ai is So Good, They Won the CMS AI Challenge … Beating Out 300 Other Organizations Including IBM, the Mayo Clinic and Deloitte.
The Promise of Machine Learning in Population Health is to Better Predict Which People Will Benefit From an Intervention Because They Are at Greater Risk of a Complication of a Disease or an ER Visit or a Hospitalization.
ClosedLoop.ai Beautifully Applied Their Machine Learning Abilities to Create a Pandemic Risk Model That Helped a New York City Health Insurance Plan Identify Which Members Would Be Most Likely to Have Severe Complications of COVID-19.
As a Result, the Insurance Company Helped These Individuals Have Groceries and Prescription Medication Delivered to Them So They Could Stay at Home and Avoid Exposure to COVID.
There You Have It! A Practical, Real-World Example of Machine Learning in Population Health That Literally Saved Some People’s Lives.
Disclaimer: Dr. Bricker is the Chief Medical Officer of Virtual Care Company First Stop Health.
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Filed under: Experts Invited, Health Economics, Health Insurance, Healthcare Finance, Information Technology | Tagged: AI, artificial intelligence, ClosedLoop.ai, CMS AI Challenge, Covid-19, Dictionary of Health Information Technology and Security, Eric Bricker MD, Machine Learning, Population Health |
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