AI-System Flags the Under-Vaccinated in Israel
An Israeli-based provider of machine learning-based solutions announced its flu complications algorithm has been selected as part of the Israeli healthcare organization’s integrated strategy to enhance its vaccination campaign.
This innovative machine-learning (AI) program from Medial EarlySign is designed to facilitate more effective and targeted outreach to people in need of disease protection.
EarlySign’s software applies advanced algorithms to ordinary patient data, collected over the course of routine care.
In a press release on January 14, 2020, EarlySign said its’ algorithm can flag individuals at high risk for developing flu-related complications and is being used as part of a clinical study undertaken by Maccabi Healthcare Services and EarlySign.
Varda Shalev, M.D., MPH, director of KSM Kahn-Sagol-Maccabi Research and Innovation Institute, founded by Maccabi Healthcare Services, said in this press release, “Due to the late arrival of influenza vaccines in Israel this year, the time we have to vaccinate patients this flu season ─ especially those at high risk for developing flu-related complications ─ is much shorter than usual.’
The influenza identification algorithm uses EMR generated data to identify and stratify unvaccinated individuals at high risk of developing flu-related complications, often requiring hospitalization.
This is good news since many areas in the Northern Hemisphere have reported increasing rates of influenza infections, according to the Global Flu Update #359, published by the World Health Organization (WHO).
On January 20, 2020, the WHO reported seasonal influenza A(H3N2) viruses have accounted for the majority of detections around the Northern Hemisphere this flu season.
Maccabi’s clinical study using EarlySign’s flu complications algorithm supports the Israeli HMO’s commitment to investigating and implementing machine learning-based solutions to improve the health of populations.
The program follows EarlySign collaboration with Geisinger Health System in December 2019, to apply advanced artificial intelligence and machine learning algorithms to Medicare claims data to predict and improve patient outcomes.
“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, Geisinger’s chief data informatics officer, in a related press release.
The AI vendor and Danville, Pennsylvania based 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.
Maccabi Healthcare Services is Israel’s 2nd-largest HMO, covering approximately 2.3 million patients, operating 5 regional centers, including hundreds of branches and clinics throughout Israel.
Medial EarlySign ‘enables healthcare providers to identify risks for critical threats, leading to potentially life-changing diagnoses for millions of patients every single day.’
Machine-learning (AI) program news published by Precision Vaccinations.
- Medial EarlySign Enables Leading Israeli HMO to Identify Pre-Symptomatic Patients at High Risk for Cancer
- Geisinger-AI vendor aim to reduce adverse events, avoid readmissions
- EarlySign, Maccabi Healthcare Launches AI-Powered Flu Vaccination Campaign
- WHO: 20 January 2020 - Update number 359, based on data up to 05 January 2020