UK Plans to Introduce Personalized Health MOTs Using Genomics & AI

The proposed approach would combine genomic analysis with AI-driven technologies to develop customized health assessments and preventative strategies tailored to individual patients.

UK Health Secretary Wes Streeting has suggested that personalized health MOTs (Measurements, Observations, and Tests) could play a transformative role in addressing the challenges of the country's aging population. 

The proposed approach would combine genomic analysis with AI-driven technologies to develop customized health assessments and preventative strategies tailored to individual patients.

Speaking to The Daily Telegraph, Streeting described the concept as a "game changer" for UK healthcare. 

"If we can start to think about that sort of health MOT approach, but combining it with things like genomics and AI machine learning... not only diagnose earlier and treat faster but predict and prevent illness, that is a game-changer," he said. 

The plan is inspired by models currently in use in Japan and forms part of a broader ten-year strategy for the NHS, which is expected to be released later this year.

As part of this vision, NHS England has announced that frail individuals aged 65 and older will be offered dedicated health checks in Accident & Emergency departments. 

These assessments, running ten hours a day and seven days a week, will monitor key indicators such as heart health and mobility to provide timely support and intervention.

AI to Support Early Fracture Detection in Emergency Settings

Meanwhile, new AI-based technologies are being introduced to help clinicians identify fractures that are often missed during initial assessments in A&E. 

The National Institute for Health and Care Excellence (NICE) has approved four AI tools—TechCare Alert, Rayvolve, BoneView, and RBfracture—designed to help recognize subtle or hard-to-spot bone breaks.

These tools work by analyzing thousands of bone-scan images to identify patterns consistent with fractures. While doctors will continue to interpret the scans, AI will serve as an additional layer of scrutiny, aiming to increase diagnostic accuracy by 15%. This is particularly significant in light of chronic shortages of radiologists and radiographers.

Missed fractures are among the most frequent errors in emergency departments, with the NHS spending over £1 million annually on compensation related to such cases. 

Early detection through AI could help prevent complications, accelerate recovery times, and reduce costs. The most commonly affected areas include the hip, ankle, and hand, especially among individuals with osteoporosis.

AI-driven diagnostics are also being explored for early cancer detection, pointing to a broader shift towards data-enhanced preventative care across the NHS.

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