One of the four Health Maintenance Organizations (HMOs) currently active in Israel, Maccabi Healthcare Services, plans to deploy a system with AI-powered algorithm that can detect individuals estimated to be at the highest risk of severe COVID-19 complications by considering pre-existing conditions and other health factors. This new system has already identified the top 2% of highest-risk patients (approximately 40,000 people), following analysis of all Maccabi patients’ anonymized electronic health records (EHRs).Here, the algorithm considered the medical factors like age,respiratory disease(pneumonia, bronchiolitis, and influenza),hospital admission history,weight,BMI,heart diseases,etc.. to identifies high-risk patients.

The work is being done in partnership with the Medial EarlySign and the Kahn-Sagol-Maccabi Research and Innovation Institute.Medial EarlySign is a pioneer in AI and machine learning-based solutions for early detection and prevention of high-burden diseases.


“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 Prof. Varda Shalev, director of the Kahn-Sagol-Maccabi Research and Innovation Institute.


When a person flagged by the algorithm as high-risk contacts a nurse or a doctor to report COVID-19-like symptoms, the system automatically notifies the medical professional of that patient’s status.From there, the potentially infected person can expect testing and priority treatment at Maccabi testing facilities 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.



According to the Dr. Jeremy Orr, CEO of Medial EarlySign, “In building the new algorithm for COVID-19, we utilized numerous aspects of our Flu Complications AlgoMarker.Based on anonymized data collected from millions of people treated by Maccabi, our models were adapted and optimized according to existing medical knowledge and known risk factors relating to COVID-19. The data from Maccabi is being continually updated, allowing us to further improve this essential new algorithm.”


When considering efforts of applying AI to COVID-19, a team led by physician Ron Li at Stanford University is evaluating whether an algorithm trained on over 130,000 patient could accurately identify which COVID-19 patients’ condition will deteriorate.University of Chicago Medical Center is testing an upgrade to its AI eCart system that will monitor oxygen to notify when a COVID-19 patient’s lungs might be failed.


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