Health AI Leader Medial EarlySign Launches New Suite of Clinical Data Solutions to Optimize Patient Care

TEL AVIV, Israel, June 24, 2020 /PRNewswire/ -- Medial EarlySign (earlysign.com), a leader in AI-based clinical data solutions to aid in the early detection and prevention of high-burden diseases, today announced the launch of its new Back2Care platform. With four new bundles focused on clinical domains, prioritization, and readmissions, this suite of integrated AI-powered solutions uses routine data to identify and prioritize patients who will benefit from accelerated attention. The result is actionable insights into patient and population health, allowing healthcare organizations to expedite care for high-risk patients, deliver proactive interventions, and address organizational needs in getting patients back to care.

"As the healthcare community begins to emerge from the disruption caused by the coronavirus pandemic, the market is demanding solutions that help get patients 'back to care' as quickly and seamlessly as possible," said Jeremy Orr MD, CEO of Medial EarlySign. "Confidence in safe visits must be restored and addressing the backlog of patients in need of screenings and ongoing care must be accelerated. The ability to leverage and deploy ML/AI to identify and prioritize patients for care is critical. As we move to the next normal, we are expanding the scope of our proven digital solutions to help healthcare organizations—and their front-line workers—successfully navigate the transition back to care."

The Back2Care suite of bundled solutions enable prioritization of high-risk patients and re-engagement of populations into the clinical system. Healthcare organizations can benefit from a broad range of solutions:

• Infectious Disease Bundle – Prepares healthcare organizations for a potential surge of COVID-19 patients, in addition to flagging patients at risk of flu complications in the coming season.
• Admissions Bundle – Stratifies patients at the greatest risk of re-admission and hospital acquired conditions, maximizing savings and avoiding unnecessary expenses.
• Early Detection Bundle – Prioritizes and targets interventions for patients at risk for high burden diseases such as lower GI disorders, colorectal cancer, lung cancer, and diabetes.
• Diabetes + Complications Bundle – Identifies patients at risk for diabetes and complications with precision analytics, flags progression from diabetes to CKD or CAD.

"The COVID complication high risk identification tool has been used to enable our physicians to identify and direct patients who are most likely to suffer complications from COVID for appropriate testing and treatment," said Micah Thorpe, DO, Vice President Business Strategy for Northwest Permanente Medicine. "It has been a valued resource in our fight against COVID and we see this as a helpful strategy to support the ongoing health of our population."

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 and AI-based solutions can help clients identify and prioritize patients at high risk for a broad range of conditions. 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 Colorado. For more information, please visit: https://earlysign.com/.

Follow Medial EarlySign on LinkedIn: Medial EarlySign and Twitter: @MedialEarlySign

Media Relations Contact:
Ellie Hanson
[email protected]
+1-929-222-8006

SOURCE Medial EarlySign

WANT YOUR COMPANY'S NEWS FEATURED ON PRNEWSWIRE.COM?

440k+
Newsrooms &
Influencers

9k+
Digital Media
Outlets

270k+
Journalists
Opted In

GET STARTED