Personalised digital health: A tool, not a silver bullet

Digital health tech has the potential to help us all live longer, healthier lives – but it isn’t a population health silver bullet, it’s just one tool in the sector’s wide and diverse armoury.

When the government published its prevention green paper earlier this year, it placed a heavy emphasis on emerging technologies such as genetic sequencing, machine learning and artificial intelligence (AI).

Advancing our Health: Prevention in the 2020s said we are about to enter a decade of “proactive, predictive, personalised prevention” which would provide targeted support, tailored lifestyle advice and greater protection against future threats.

Painting a picture of the digital health future, it said: “New technologies such as genomics and AI will help us create a new prevention model that means the NHS will be there for people even before they are born.

“Using data held by the NHS, and generated by smart devices worn by individuals, we will be able to usher in a new wave of intelligent public health where everyone has access to their health information and many more health interventions are personalised.”

In the 2020s, the green paper envisions, digital health will enable people to convert from “passive recipients of care”, rather “co-creators of their own health”.

It’s a laudable and in many ways feasible aim. We are, after all, in the midst of a technological revolution that is transforming everything from diagnostics to follow-up care.

But tacking embedded public health issues such as obesity and diabetes, health inequalities and the stall in life expectancy will require more than a reliance on the potential of technology. We need a whole-system approach that moves beyond the personal.

Technological aide

Last week, the Health Foundation published a report setting out the main challenges that health leaders will need to overcome if the government’s vision of a healthy future can become a reality.

“The hope… is that new, ‘smarter’ approaches to prevention will help address entrenched problems, such as health inequalities, and worrying trends, such as the stalled improvements in life expectancy,” said the authors.

“However, if real progress is going to be made in improving the public’s health, history tells us that some fundamental tensions in public health policy and practice need to be addressed.”

In short, technology and its potential needs to be seen in the round, as an adjunct to, not replacement for, the expertise and evidence we already have.

Challenging health inequalities 

Firstly, the foundation claims that there needs to be a greater balance between interventions that reduce individual susceptibility and those that address the society-wide underlying causes of ill health.

“There are good reasons – both theoretical and empirical – to believe that, while both approaches are needed, those that address the underlying causes have the biggest impact on population health.

“By focusing on ‘personalisation', the green paper’s vision for data and technology falls into the former category, limiting its potential impact,” it said, highlighting that some of the most successful initiatives in history have focused on improving conditions at population level.

Clean water and improved housing and sanitation, for example, played a crucial role in eliminating infectious diseases such as cholera through tackling the structural issues that contributed to health inequalities.

Said the foundation: “There is abundant evidence that the strongest drivers of population health and health inequalities are not individual-level factors but structural issues such as income, education, housing and clean air: the wider determinants of health.

“These influence the health of populations powerfully – not only because they affect whole population groups but because they are ‘the causes of the causes’: that is, they strongly influence individual-level risk factors.”

Societal bias

Another thing to consider in the med tech advance is that interventions are only as good as the data they are based on – and that bias, unconscious and otherwise, is just as alive in datasets as it is in society.

Data-driven technology, the Health Foundation agrees, could potentially identify and target hard to reach groups, but they can also inadvertently reflect the structural inequalities in our society.

“For example, many risk-prediction innovations are based on genetic datasets that have historically excluded many populations.

“People of European ancestry make up 79% of all participants of genetic studies,” said the report, adding that basing AI or machine learning initiatives on biased data could result in algorithms that perpetuate or reinforce those biases.

“There is a real risk that the people who are least able to access appropriate healthcare are the most likely to be under-represented in data sources. So, balancing the benefits of data and technology solutions against the risk that they will exclude some populations is a major challenge.”

Digital exclusion

There is much evidence to show that moving services to digital channels has the potential to expand access, but it’s important to remember that it’s not the right answer for everyone.

According to the Good Things Foundation, around 7.8 million people in the UK never use the internet and another 7.4 million only use it “infrequently”.

As the Health Foundation points out, older people, those living with disability or chronic illness, with lower levels of education or on a low income are more likely to be non- or limited users

It means that technological solutions that depend on users having sufficient skills to access them may exclude many of those who are most in need, it said.

Knowing what we know

Another key challenge, the Health Foundation report said, was ensuring untested novel technological interventions were not rolled out at the expense of existing “tried and tested” ones.

The authors wrote: “The green paper emphasises the potential of new technology to improve prevention. But it is important to balance this against the many existing interventions that have a proven track record.

“There is strong evidence for the effectiveness and cost-effectiveness of a wide range of preventative interventions that are currently under-funded, ranging from smoking cessation to Sure Start Centres.”

Decisions about investing in new technologies, then, must be made in the context of what we already know about non-digital interventions with strong evidence bases and are ready to be rolled out.

Seizing opportunity

Digital health presents huge opportunities, but it is not a silver bullet – is just one tool in the armoury of healthcare.

Addressing the challenges set out in the Health Foundation’s report will take a system-wide approach that considers how technology will work with existing programmes and expertise to address the wider determinants of health.

As the Health Foundation concluded: “If we are to make the most of the opportunities, the government’s vision of new data and technology for public health must move beyond personalisation and consider the wider potential to improve the public’s health.”

Read the full report here.