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IBM, Mayo Clinic, Geisinger among 25 finalists for $1.6M CMS artificial intelligence challenge

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Out of more than 300 artificial intelligence proposals, the Centers for Medicare & Medicare Services (CMS) picked 25 organizations for the next stage of its AI challenge including IBM, Booz Allen Hamilton and Mayo Clinic. The organizations are competing for a $1 million prize to develop the best tool for predicting patient health outcomes. CMS says the AI challenge, which launched in March, will accelerate the development of AI solutions that aid clinicians in predicting health outcomes and keeping patients healthy. The central goal is to develop AI-driven predictions healthcare providers and clinicians participating in CMS Innovation Center models can use, CMS officials said. RELATED: CMS offers up to $1.6M in AI challenge for better healthcare prediction tools The challenge was created in partnership with the American Academy of Family Physicians and the Laura and John Arnold Foundation.


CMS names 25 innovators advancing in AI Health Outcomes Challenge

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The Centers for Medicare and Medicare Services this week announced the 25 participants selected to move on to the next round of its Artificial Intelligence Health Outcomes Challenge. WHY IT MATTERS Launched this past March by the CMS Innovation Center, in collaboration with the American Academy of Family Physicians and the Laura and John Arnold Foundation, the AI Health Outcomes Challenge aims to give innovators a showcase for how they're developing AI and machine learning technologies, deep learning tools and neural networks. While the focus is on helping hospitals and health systems drive cost efficiencies for value based reimbursement, prevent adverse patient safety events and boost quality outcomes, CMS put out the call innovators from all sectors of the economy – not just from healthcare. More than 300 different organizations submitted proposals. They were evaluated by a group of data science experts, clinical informaticists and care providers.


Geisinger-AI vendor aim to reduce adverse events, avoid readmissions

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Israel-based Medial EarlySign and Geisinger Health System have partnered to apply advanced artificial intelligence and machine learning algorithms to Medicare claims data to predict and improve patient outcomes. An EarlySign-Geisinger proposal has been selected as one of 25 participants to advance to Stage 1 of a technology challenge from the Centers for Medicare and Medicaid Services to accelerate the development of AI and machine learning solutions for healthcare. "Approximately 4.3 million hospital readmissions occur each year in the U.S., costing more than $60 billion, with preventable adverse patient events creating additional clinical and financial burdens for both patients and healthcare systems," says David Vawdrey, Geisinger's chief data informatics officer. "Together with our partner EarlySign, we have forged a dynamic team that is rapidly developing novel solutions to achieve the Quadruple Aim of improving the patient experience of care, improving the health of populations, reducing cost and improving clinical care provider satisfaction," adds Vawdrey. The AI vendor and Danville, Penn.-based regional healthcare provider intend to develop models that predict unplanned hospital and skilled nursing facility admissions within 30 days of discharge and adverse events such as respiratory failure, postoperative pulmonary embolism or deep vein thrombosis, as well as postoperative sepsis before they occur.


CMS competition seeks predictive AI apps for better health outcomes

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The Centers for Medicare and Medicaid Services has launched a new contest it hopes will speed the development of new artificial intelligence technologies that can better predict health outcomes and boost quality of care. WHY IT MATTERS CMS says the Artificial Intelligence Health Outcomes Challenge – announced by the agency on Wednesday, in partnership with American Academy of Family Physicians and the Laura and John Arnold Foundation – seeks to uncover and "unleash" new and innovative tools to help with the push toward value-based care. To do that, CMS is calling on developers from all industries to create new predictive AI applications to help providers participating in CMS Innovation Center models to deliver better care and make quality measures more impactful. "The Artificial Intelligence Health Outcomes Challenge is a three stage competition that will begin with the Launch Stage, in which participants will submit an application at ai.cms.gov," "Up to 20 participants will be selected to participate in Stage 1 of the Challenge. We anticipate that more information about Stage 1 and Stage 2 will be announced later this year."


UVA Artificial Intelligence Project Among 7 Finalists for $1 Million Prize

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A UVA Health data science team is one of seven finalists in a national competition to improve healthcare with the help of artificial intelligence. UVA's proposal was selected as a finalist from among more than 300 applicants in the first-ever Centers for Medicare & Medicaid Services (CMS) Artificial Intelligence Health Outcomes Challenge. UVA's project predicts which patients are at risk for adverse outcomes and then suggests a personalized plan to ensure appropriate healthcare delivery and avoid unnecessary hospitalizations. CMS selected the seven finalists after reviewing the accuracy of their artificial intelligence models and evaluating how well healthcare providers could use visual displays created by each project team to improve outcomes and patient care. Each team of finalists received $60,000 and will compete for a grand prize of up to $1 million.