What could 'personalised prevention' mean for our health?

‘Personalised prevention’ is not new, but the term is becoming increasingly widespread in political, clinical and public discourse in England as growth in technology, data collection and AI create more opportunities for personalisation in health care. As we head towards a general election, both Labour and Conservatives have called for personalised approaches within the NHS that engage people in their health and predict, detect and treat conditions better and earlier. But what exactly is personalised prevention? And what is its potential to improve health and help a struggling NHS?

The first reference to personalised prevention in health policy in England was in 2013. Since then, there have been 30 Department of Health and Social Care publications with an ambition to improve health care or patient outcomes by introducing personalised approaches. However, the specifics of these ambitions have not always been clear, with the use of varying terms such as ‘precision medicine’ and ‘personalised health care’.

We reviewed government publications between 2010 and 2023 alongside academic definitions. We found that ‘precision’ and ‘personalised’ are being used interchangeably to refer to targeted or stratified clinical care based on individual factors such as socio-demographic, clinical, behavioural and genetic information.

What does this mean for health in England?

Personalised prevention brings promising opportunities

As gains in life expectancy stall and inequalities and multimorbidity grow, there is an increasing need to target already limited resources to better prevent illness and improve health. Though not without risks, personalised prevention could be part of the solution.

Incorporating genetic information into decisions about disease risk, diagnosis and treatment has shown potential in areas such as breast cancer, weight gain and coronary artery disease. For example, genetic-based risk prediction using polygenic risk scores (which estimate someone’s increased risk of a disease based on multiple small genetic variants) has been found to identify individuals at twofold or higher risk of cancer from biobank databases (although the benefit to existing screening programmes remains small, with significant risk of false negative results when applied across populations). 

Personalisation could also help increase patient engagement, with small-scale examples of people using wearables to manage type 2 diabetes or improve physical activity and diet. Based on this potential, the private sector is heavily investing in personalised health – from smartwatch tracking to direct-to-consumer genetic tests – benefitting from relatively loose regulation and high uptake from younger and more affluent populations. The NHS could be well placed to democratise these approaches by making them available to everyone and leveraging its vast data assets.

Current ambitions will not work equally for everyone

Many of the government’s ambitions for personalised prevention are dependent on genomics, technology and patient data. However, the significant variation in the predictive power of genomics calls into question its introduction into routine care just yet. Polygenic risk scores are based on data derived disproportionately from people of white European ancestry, meaning they are less accurate in non-white populations. Similar biases plague AI, as recently echoed in an independent report to government. 

Engagement with health technology generally tends to be greater among populations who are white, younger or living on a higher income – groups who already experience better health outcomes – suggesting any benefits may actually widen inequalities.

Industry interests must be balanced against clinical value-add

The technology to deliver personalised prevention is currently a long way from being implemented nationally. 

According to NHS Digital’s own roadmap for AI, nearly all technologies identified to support population health will not be deployable for at least 3 years, and only a third of products to improve service efficiency will be ready within 12 months. 

While the private sector has launched several health technologies – from health ‘MOTs’ to disease and genetic screening – these worryingly sit well outside our NHS- and government-approved screening programmes and clinical systems. They can therefore cause more harm than good, either through over-diagnosis or revealing results of unknown clinical significance or with no clear care pathway. Concerns and follow-ups are likely to fall on the NHS, generating additional pressure rather than relieving it.

Alongside targeting consumers, the commercial sector is playing a more subtle role in shaping personalised prevention. For example, the current collaborative rather than legislative approach to regulating AI and the industry buy-in to government-sponsored initiatives (such as Our Future Health) mean that commercial interests may be placed ahead of national priorities. As a result, industry is driving the development agenda as opposed to government setting out core problems for the commercial sector to solve. 

A dual focus on individuals and populations is needed

Finally, an overemphasis on personalised prevention risks shifting the focus of research, funding and policy towards individuals and away from the wider determinants of health, such as education and housing, which drive population health and inequalities.

While personalised prevention may lead to improved health outcomes for some people, this won’t be sufficient to realise wholesale improvements to public health.

Looking ahead

If the next government is serious about realising the promise of personalised prevention, a proactive, strategic approach is needed that clearly connects NHS ambitions for condition management, use of data and AI. 

Over the coming months, the Health Foundation will be exploring personalised prevention in more detail to better understand how government can leverage available opportunities while mitigating the risks.