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WHO names Israeli healthcare AI model among the world’s leading approaches
Clalit Health Services' framework for assessing AI before it reaches patients has been highlighted in a new World Health Organisation report
Israel’s largest healthcare provider has been recognised by the World Health Organisation (WHO) for its approach to safely introducing artificial intelligence into clinical care.
Clalit Health Services’ OPTICA framework has been selected as one of four leading approaches highlighted in a new WHO report examining how AI is being deployed in real-world healthcare settings across Europe.
The model was developed to assess AI technologies before they are introduced into clinical practice, addressing a growing challenge for health systems as the use of artificial intelligence accelerates.
Rather than simply assessing whether an AI product works, OPTICA uses a 77-point checklist covering areas including patient safety, privacy, accuracy, clinical suitability and how the technology will be monitored after it has been introduced.
The framework requires input from different specialists across the organisation, including clinicians and those responsible for AI infrastructure, with systems continuing to be monitored after deployment rather than receiving a one-off approval.
Prof Ran Balicer, chief innovation officer and head of the Innovation Division at Clalit, said: “We created an organisational process called OPTICA, in which every AI product intended for implementation at Clalit goes through a checklist of up to 77 items.
“These items address every aspect of the product, including safety, privacy protection, accuracy, and continuous monitoring over the years, because the product itself may change.”
The WHO report examined 11 case studies from different countries, including three from Israel and two involving Clalit.
One highlighted an AI model developed by researchers at the Clalit Research Institute using 25 years of patient records to identify people at greater risk of having undiagnosed hepatitis C.
When used to target screening, the model identified 38 carriers among around 500 people considered at risk. Clalit said this represented a 100-fold improvement in detection efficiency compared with mass screening.
Another Israeli case examined technology developed by Israeli medical AI company Aidoc, whose platform enables Clalit to run multiple AI algorithms from different providers for medical imaging.
The report found that successful adoption of healthcare AI depended not only on the performance of the technology, but also on its integration into clinical workflows, the involvement of medical professionals and continued monitoring after deployment.
The findings come as health systems around the world increasingly grapple with how to harness the potential of AI while protecting patient safety and maintaining the trust of doctors and other healthcare professionals.
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