On this episode of The Race to Value Podcast, Andrew Eye, founder and CEO of ClosedLoop, explains why the company is an exemplar in the race to value. He discusses how ClosedLoop.ai was founded, how the team beat out the world’s leading technology and healthcare organizations to win the CMS AI Health Outcomes Challenge, the importance of explainable AI in healthcare, and much more.
In healthcare, we are overdue for a “Moneyball” revolution. The shift towards value-based payment has made it clear that our system needs to do a better job generating outcomes that matter to patients — a positive health-care experience, improved health, and good quality of life. The machine learning techniques that were used to algorithmically determine a player’s value were light-years ahead of the archaic methods that had been used in baseball up to that point. Similarly, many of our conventions in delivering care come from an era when healthcare was delivered primarily by doctors and nurses with elite training whose success depended mostly on content expertise. A key component to value-based transformation in healthcare will be artificial intelligence. Without AI, medicine will never advance to a state where the totality of a patient’s data can be used to find predictive signals that will lead to enhanced treatment and population health interventions that improve outcomes.
Predict the comprehensive chronic and preventive care needs of individual patients with unparalleled precision.
Predict and prioritize high-risk members and use Contributing Factors insights to personalize outreach and interventions.
Strengthen commercial success, gain precision insights into key cohorts, and power digital therapeutics and value-based contracts.