“It’s not trying to hunt for a needle in a haystack anymore,” said Carol McCall, Chief Health Analytics Officer at ClosedLoop.ai. “There are too many haystacks. What I need is a magnet, and AI is this magnet that can pull out all these needles.”
In this interview, Carol McCall, Chief Health Analytics Officer at ClosedLoop, sits down with Lone Star Health News to discuss her company's innovative platform, winning the CMS AI challenge, and the future of healthcare.
Andrew Eye, CEO of ClosedLoop, shares insights into how AI is changing the healthcare landscape. In addition to discussing the $1.6 million CMS Challenge won by Closedloop, Andrew offers his thoughts on how AI stands to revolutionize the healthcare landscape by using predictive analytics to reduce social and racial disparities in healthcare, surface insights to reduce unplanned hospital readmissions and adverse events, and solve the biggest and most costly problems facing healthcare today.
In this Q&A, Carol McCall, Chief Analytics Officer, tells Healthcare Global what sets ClosedLoop apart from other data science platforms. She delves into explainability in AI, avoiding bias in healthcare data science, the level of data science maturity needed to effectively use the platform, and plans for the future.
Watch the segment to learn how ClosedLoop won the CMS AI Health Outcomes Challenge, and how Genesis Physicians Group is using ClosedLoop to identify and tackle the healthcare challenges facing nearly 30,000 Medicaid patients in Dallas.
The winner of Medicare's AI Health Outcomes Challenge is a lesser-known startup from Austin, Texas, called ClosedLoop.ai. The company, whose victory was announced late Friday, bested 300 rivals with a system capable of forecasting adverse health events...
ClosedLoop.ai, healthcare’s data science platform, today announced a new relationship with Palm Beach Accountable Care Organization (PBACO), one of the nation’s leading and most successful physician-led ACOs in the Medicare Shared Savings Program (MSSP).
ClosedLoop makes it easy and affordable for healthcare organizations to use data science to improve outcomes and reduce costs by combining an intuitive end-to-end machine learning platform for data scientists with a catalog of healthcare specific predictive models and features.
KLAS examines the recent AI purchase decisions of 47 organizations to determine which vendors are being considered and chosen, which are being replaced, and why provider and payer organizations choose the AI solutions they do (technology? service? healthcare expertise?).