Maccabi Healthcare Services, Israel’s leading HMO with 2.4 million members, announces the deployment of a new AI-powered algorithm that identifies individuals estimated to be at the highest risk of severe COVID-19 complications due to pre-existing conditions and other health factors.

The new algorithm has already identified the top 2 percent of highest-risk patients (approximately 40,000 people) following the analysis of all Maccabi patients’ anonymized electronic health records (EHRs).

“The world is currently at war with COVID-19,” said Ran Sa’ar, CEO of Maccabi Healthcare Services. “The algorithm and the fast-tracked testing it enables will reduce the number of severe COVID-19 cases and help save lives.”

The algorithm was developed by Medial EarlySign and the Kahn-Sagol-Maccabi Research and Innovation Institute.

Medial EarlySign is a technology leader in machine learning-based solutions that aid in the early detection and prevention of high-burden diseases. The company is currently in advanced negotiations with medical systems in the United States that are interested in the algorithm as part of their COVID-19 health-care protocols.

When an individual flagged by the algorithm contacts a nurse or doctor to report COVID-19-like symptoms, the system will automatically notify the medical professional that the patient falls in the high-risk group. The patient will then be sent for immediate testing.

Tests are performed at designated Maccabi facilities, drive-through stations or, if necessary, in the patient’s home. This allows for medical procedures to begin as quickly as possible following a positive diagnosis, helping to limit the spread of the virus.

The algorithm identifies high-risk patients through analysis of dozens of routine medical factors, including age; respiratory disease such as pneumonia, bronchiolitis and influenza; hospital-admission history; weight and BMI; medications prescribed for respiratory illnesses or conditions, such as asthma and cough; heart disease; smoking history; diabetes; digestive disease; and immunosuppression.

“As one of the largest HMOs in the world with 2.4 million members and 27 years’ worth of electronic health records, Maccabi’s algorithm relies on big data from one of the largest and highest-quality collections of anonymized EHRs in the world,” said Professor Varda Shalev, director of the Kahn-Sagol-Maccabi Research and Innovation Institute. “Early identification of those at greatest risk is crucial to supporting health-care professionals and to flattening the curve of the pandemic.”

The new algorithm further classifies patients according to three levels of estimated risk. Medical task forces can also use risk levels as part of their decision-making on care options for each patient—home hospitalization, designated hotels or hospital admission—and the necessary frequency of follow-ups.

Dr. Jeremy Orr, CEO of Medial EarlySign, added that “the data is being continually updated, allowing us to further improve this essential new algorithm.”

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