CMS selects participants for predictive health AI challenge

The Centers for Medicare and Medicare Services named 25 participants to compete in the first stage of its Artificial Intelligence Health Outcomes Challenge.

The 25 teams, competing for a pot of $1.6 million, are being asked to use AI and deep learning to predict unplanned hospital visits within a 30-day window for Medicare beneficiaries and create innovative ways to explain their results to front-line clinicians and patients.

“Artificial Intelligence is a vehicle that can help drive our system to value – proven to reduce out-of-pocket costs and improve quality. It holds the potential to revolutionize healthcare: imagine a doctor being able to predict health outcomes – such as a hospital admission – and to intervene before an illness strikes,” CMS Administrator Seema Verma said in a statement. “The participants in our AI Challenge demonstrate that such possibilities will soon be within reach.”

Many of the participating teams are top technology companies and universities, but most others are health-related organizations. See the complete list below. Just seven will be selected to move on to phase two, in which they can receive awards up to $60,000. In the second phase, they’ll compete for a $1 million grand prize and $230,000 for second place.

More than 300 entities submitted proposals, CMS said.

The agency launched the challenge in March to support President Trump’s recent executive order on AI.

Phase Two Participants

• Accenture Federal Services
• Ann Arbor Algorithms Inc.
• Booz Allen Hamilton
• ClosedLoop.ai
• Columbia University Department of Biomedical Informatics
• CORMAC
• Deloitte Consulting LLP
• Geisinger
• Health Data Analytics Institute
• HealthEC, LLC
• Hospital of the University of Pennsylvania
• IBM Corp.
• Innovative Decisions Inc.
• Jefferson Health
• KenSci Inc.
• Lightbeam Health Solutions, LLC
• Mathematica Policy Research, Inc.
• Mayo Clinic
• Mederrata
• Merck & Co., Inc.
• North Carolina State University
• Northrop Grumman Systems Corporation
• Northwestern Medicine
• Observational Health Data Sciences and Informatics
• University of Virginia Health System