The largest ever healthcare-focused AI challenge has been won by the healthcare data science platform,

The $1.6m ‘Centers for Medicare & Medicaid Services (CMS) Artificial Intelligence Health Outcomes Challenge’ prioritized creating “explainable artificial intelligence solutions to help front-line clinicians understand and trust AI-driven data feedback” to demonstrate how AI solutions could predict unplanned hospital admissions and adverse events – a $200 billion problem that impacts nearly 32% of Medicare beneficiaries.

The Austin-based company beat more than 300 of the world’s leading technology, healthcare, and pharmaceutical organizations, including IBM, Mayo Clinic and Deloitte to the $1m prize. With ClosedLoop’s explainable predictive models already positively impacting more than three million patients a day, the competition win reinforces ClosedLoop’s position as industry leader in delivering explainable AI solutions that clinicians trust to predict health outcomes, target scarce resources, and keep their patients healthy.

‍“Our Patient Health Forecasts (PHF) were key to winning the Challenge,” said ClosedLoop CTO and Co-founder Dave DeCaprio. “We re-imagined the entire concept into a comprehensive and personalized risk forecast that could be delivered directly into a clinical workflow. Each forecast surfaces key variables and explains precisely how they contribute to a patient’s specific risk.” The forecasts integrate relevant clinical information and link to specific interventions that clinical teams use to prevent adverse events, improve outcomes, and reduce unnecessary costs.

‍The multi-stage competition is operated by CMS’s Center for Medicare and Medicaid Innovation (CMS Innovation Center) in collaboration with the American Academy of Family Physicians (AAFP) and Arnold Ventures. It began in 2019 with the aim of accelerating development of AI solutions for predicting patient health outcomes for Medicare beneficiaries for potential use by the Innovation Center.

To select the winner, CMS conducted a rigorous evaluation process, supported by a team of AI scientists. Clinicians from the AAFP reviewed and scored the explainability element. Submissions were reviewed and the winners selected by a panel of CMS senior leadership.

“Clinicians are eager to use the latest innovations to better help identify patients at risk, provide higher quality care, and improve health outcomes,” said CMS Acting Administrator Liz Richter. “CMS’s AI Health Outcomes Challenge has brought this exciting future one step closer to reality by engaging with some of the country’s brightest AI innovators. We congratulate and runner-up Geisinger on their achievements, and all the Challenge finalists and participants for helping increase the information available to clinicians to improve patient care.”

‍‍While the ClosedLoop platform is already widely trusted by healthcare organizations across the country, the CMS Challenge accelerated the creation of additional explainable interfaces. The latest version of the Patient Health Forecast is available in private beta for existing customers and select strategic partners.

‍“Finding effective ways to improve outcomes and reduce the cost of care is a national imperative. The CMS Challenge demonstrated how AI solutions can be a powerful tool to help achieve that,” said ClosedLoop CEO Andrew Eye. “As the leading provider of AI solutions in healthcare, the Challenge drove us to improve our capabilities across the board – scalability, accuracy, deep explainability, and ways to address algorithmic bias and fairness. In the end, we didn’t stop at ‘AI that clinicians trust.’ We built a product that clinicians love.”