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Geisinger and Medial EarlySign Advance to First Stage of CMS AI Health Outcomes Challenge

DANVILLE, Pa., Nov. 19, 2019 /PRNewswire/ -- Geisinger, one of the leading integrated health services organizations in the United States, and EarlySign (, a pioneer in developing machine learning techniques for early detection of disease, have been recognized for their joint proposal being one of 25 accepted by the Centers for Medicare & Medicaid Services (CMS) to advance to Stage 1 of the AI Health Outcomes Challenge.  

The CMS AI Health Outcomes challenge provides innovators with the opportunity to demonstrate how AI tools may be implemented to predict health outcomes and keep patients healthy in hopes of more AI tools being considered for potential use in CMS Innovation Center payment and service delivery models. More than 300 entities submitted proposed AI solutions to the Challenge.

The joint Geisinger/EarlySign proposal – Reducing Adverse Events and Avoidable Hospital Readmissions by Empowering Clinicians and Patients – will seek to apply advanced AI and Machine Learning algorithms to Medicare administrative claims data. Doing so can lead to the development of models that predict unplanned hospital and skilled nursing facility (SNF) admissions within 30 days of discharge and adverse events such as respiratory failure, postoperative pulmonary embolism or deep vein thrombosis, and postoperative sepsis before they occur.

"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," said David Vawdrey, Ph.D., Chief Data Informatics Officer at Geisinger. "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."

"Geisinger's experience and substantial unified data architecture (UDA) is the perfect complement to EarlySign's proprietary data repository and suite of AI tools, enabling the rapid development and validation of effective machine learning models," said EarlySign CEO Dr. Jeremy Orr. "These models are designed to integrate seamlessly with current clinical workflows as a decision support tool that can help improve patient outcomes and decrease healthcare costs."

CMS will announce Stage 2 finalists for the AI Health Outcomes Challenge in April 2020. The final awardees and grand prize winner will be revealed in September 2020.

About Geisinger
Geisinger is committed to making better health easier for the more than 1.5 million consumers it serves. Founded more than 100 years ago by Abigail Geisinger, the system now includes 13 hospital campuses, a 600,000-member health plan, two research centers and the Geisinger Commonwealth School of Medicine. With 32,000 employees and 1,800 employed physicians, Geisinger boosts its hometown economies in Pennsylvania and New Jersey by billions of dollars annually. Learn more at or connect with us on Facebook, Instagram, LinkedIn and Twitter.

About Medial EarlySign
Medial EarlySign helps healthcare systems with early detection and prevention of high-burden diseases. Their suite of outcome-focused software solutions (AlgoMarkers™) find subtle, early signs of high-risk patient trajectories in existing lab results and ordinary EHR data already collected in the course of routine care. EarlySign's AlgoMarkers are currently helping clients identify patients at high risk for conditions such as lower GI disorders, prediabetic progression to diabetes, and downstream diabetic complications such as chronic kidney disease (CKD).  The algorithmic models developed using the company's machine learning approach are supported by peer-reviewed research published by internationally recognized health organizations and hospitals. Founded in 2013, Medial EarlySign is headquartered in Tel Aviv, Israel with US headquarters in Boston, MA. For more information, please visit
Follow Medial EarlySign on LinkedIn: Medial EarlySign and Twitter: @MedialEarlySign


Matthew Van Stone



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