Personalised AI Health Checks: A Game-Changer for the UK's Ageing Population

As the UK’s population ages rapidly—with nearly 11 million people over 65 and that figure projected to reach 17 million by 2040—the need for smarter, preventive, and more personalised healthcare solutions becomes ever more pressing. In response, Health Secretary Wes Streeting has announced a transformative vision for the NHS: the adoption of personalised health checks powered by artificial intelligence and genomics.

This progressive approach, already in use in Japan, could redefine the way we approach health screening and care planning. Instead of a one-size-fits-all ‘health MOT’, individuals could receive custom-built care plans based on their genetic makeup, clinical data, and AI-driven risk prediction models. In essence, this could mark an important shift from reactive treatment to proactive prevention, particularly for age-related conditions such as cardiovascular disease, osteoporosis, and cognitive decline.

What Does This Mean in Practice?

Streeting has outlined that these health MOTs will incorporate genomic data and AI-enabled insights to enable earlier diagnosis, faster treatment, and, most importantly, prevention. For example, individuals with a predisposition to high cholesterol, diabetes, or certain types of cancer could be identified through genomic screening and offered tailored interventions before symptoms appear.

This vision aligns with the upcoming ten-year NHS Plan, designed to embed innovation in clinical practice, improve population health outcomes, and tackle inequalities in access and outcomes. These ambitions are not theoretical; pilot schemes and evidence-backed AI programmes are already being trialled across the UK.

AI in A&E: Spotting the ‘Hard-to-See’ Fractures

One of the earliest and most promising applications of AI is in Accident & Emergency units, where frail patients over the age of 65 will now be offered daily checks covering mobility and heart health. Notably, NHS England is rolling out AI scanning technologies designed to catch fractures that often go undetected in busy emergency settings.

Missed fractures are one of the most common diagnostic errors in A&E. According to the National Institute for Health and Care Excellence (NICE), these errors account for over £1 million annually in compensation claims. To tackle this, the NHS has approved four AI tools—TechCare Alert, Rayvolve, BoneView, and RBfracture. These programmes use machine learning algorithms trained on thousands of X-ray and CT images to increase fracture detection accuracy by an estimated 15%.

Importantly, these technologies are not replacing radiologists but augmenting their ability to identify subtle breaks, especially in vulnerable patients, such as those with osteoporosis. Around 200,000 people are hospitalised annually due to fractures, with hip, ankle, and hand breaks being the most common.

Benefits for Patients and the NHS

The integration of AI and personalised health checks brings tangible benefits across the board:

• Faster Diagnosis: Patients can receive earlier interventions for high-risk conditions, reducing complications and hospital admissions.
• Increased Accuracy: AI tools can reduce diagnostic errors, particularly in high-pressure environments like A&E.
• Improved Outcomes: Timely care leads to better recovery rates and less long-term disability.
• Cost Efficiency: Early detection and prevention reduce the long-term costs associated with chronic illness management.
• Staff Support: Automation of routine analysis supports an overstretched workforce, especially where there are shortages of radiologists.

The Role of Digital Health Enterprises

This innovation landscape opens the door for digital health consultancies, like Innovate Health Consulting Limited, to play a central role. We believe personalised AI-driven care can be delivered effectively within community healthcare settings, not just hospitals. As we support NHS organisations with digital transformation and Clinical Safety, this is an important moment to scale up these innovations at pace.

We must ensure that ethical governance, robust safety protocols, and inclusive design remain at the forefront. Ensuring digital literacy, equitable access, and safeguarding data privacy will be key challenges. As we continue to support our partners across the NHS ecosystem, we are excited to contribute to a future where digital tools help us age not only longer—but better.

Final Thought

Personalised AI health MOTs are not just a technological upgrade—they represent a radical rethink of healthcare delivery. If implemented correctly, they will empower citizens, reduce burden on frontline services, and make the NHS more resilient for the decades ahead.

Inspired by Lord Darzi’s 2024 independent NHS review, the forthcoming ten-year health plan aims to confront the complex challenges of an ageing population with bold, digital-first thinking. By combining genomics, machine learning, and routine health screening, these AI-powered health MOTs have the potential to:

• Predict and prevent illness
• Personalise treatments
• Reduce hospital admissions
• Enhance patient experience and outcomes

In A&E, AI tools are already being trialled to detect "hard-to-spot" fractures – a move that could reduce misdiagnosis and improve recovery times for thousands. This is just the beginning of a revolution in proactive, personalised medicine.

Together, we can build a smarter, fairer, and healthier NHS for all.

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