The popular emphasis on technology being harnessed by individuals fails to consider how it can be used to improve social determinants of health, say Richard Milne, Edo Richard, Eric B Larson, and Carol Brayne

In a speech to Public Health England earlier this year, health secretary Matt Hancock set out his vision for the future of public health—a vision based around “proactive, predictive, personalised prevention,” the “predictive power of genomics, and the data-crunching power of AI.” Hancock’s vision echoes the “futures thinking” of the chief medical officer’s (CMO) 2018 report, which scoped out the potential landscape of healthcare in 2040. Together, they represent the vision of technological innovation for public health that is being developed in UK health policy. 

We think that there are tensions within this vision, which should push us to broaden our understanding of how technology can help us to deal with health challenges—not only as responsible individuals, but as groups, communities, and societies. 

The CMO’s report sets out how the future offers the potential for better and more equitable health. The first half of the report focuses on social determinants of health and the role of social, political, and community action in securing the future health of the population. The second half discusses the potential of technology to bring about individualised health change. The futures imagined in these two halves of the report contrast in a way that usefully casts light on the problems of Hancock’s vision of personalised health and the wider impoverishment of our imagination when it comes to conceiving the future of public health. This is captured in microcosm within the CMO report in a scenario of how health may be experienced in 2040. 

The scenario presents the case of a couple, Sara and Michael, with their baby Allie. In line with Hancock’s emphasis on the implementation of genomics and AI from before birth, the family opt into a national genome sequencing project, and take part in various “precision medicine” activities. Sara orders a home gut biome test, which shows that Michael has a predisposition for type 2 diabetes, and he changes his lifestyle to counter this risk. The couple consent to donate their daughter’s genetic data to a research project, and in return they are provided with access to the latest research findings. Throughout the scenario, the NHS provides wearables, chatbots, home genome testing kits, and health coaching—all of which produce data that are collected in a single, user controlled platform. 

Hancock’s vision of a public health “fit for the future” makes a series of assumptions about that future, which are captured in this scenario. Both forecasts fail to acknowledge the complexity of biological systems and, in our view, downplay the risks of oversimplification that come with new ways of measuring biological systems, such as microbiome sequencing. Furthermore, his vision demarcates the anticipated role of detection and prediction; how and where we see responsibility for action in future healthcare; and the future relationship between citizens, health services, and the private sector. 

The data generated by and about Michael, Sara, and Allie in this scenario maps out both their current and predicted health, and are used to inform lifestyle changes and discussions with doctors. However, as commentators have pointed out, the growing volume of data generated through the continuous monitoring of the body will inevitably detect many abnormalities without necessarily having the ability to discern which will have clinical consequences. Such technologies thus come with a high likelihood of overdiagnosis and overtreatment.

Michael is clearly responsible for acting on the basis of his gut biome result; as an empowered individual, he is expected to “optimise” his health and reduce his innate biological risks. Yet to date, the accumulated evidence suggests that knowledge of genetic profiles alone is insufficient to change people’s behaviour.

For Hancock, emphasising people’s role as “active participants in their own health” reflects the wishes of a public who have been found to “believe the responsibility for their health lies with them—the individual, not the state.” If we want to improve public health, however, there are compelling reasons to move beyond “the wisdom of the crowd” and this increasing emphasis on individual responsibility. The evidence we have on the importance of social determinants—including poverty, education, and geography—in shaping health is overwhelming. Yet in the push for personalised prevention, these social determinants are being sidelined. 

The popular emphasis on technology being harnessed by individuals is unlikely to affect social determinants of health, and risks increasing the divide between the haves and have nots. Yet technological and social change over the next few decades could also open up new possibilities for public health that shift attention away from the individual. We’d like to see more focus on how a future health service can use technology to affect and improve the social factors which support or impede Michael, Sara, and Allie in “optimising” their health. Examples include supporting innovative “citizen science” efforts to monitor local air and noise pollution or to improve mobility. Other ideas might involve using technologies to support access to education across the lifecourse or building social networks for the chronically ill or socially excluded. 

Genomic medicine and the potential of AI driven healthcare have captured the attention and imagination of clinicians and politicians. Yet we need to consider how we shape this vision of the future, what financial and scientific commitments it drives, and how these limit our ability to change direction. The current visions being proffered for health technology neglect innovation’s potential to impact on social determinants of health; redistribute responsibility; and affect social, economic, and cultural inequalities. As we think about the future of public health, we should remember that there is an alternative. 

Richard Milne is a sociologist based at the Wellcome Genome Campus and University of Cambridge. His work examines the social and ethical implications associated with new medical technologies in the areas of dementia and genomics. Twitter @rjmilne

Competing interests: I have read and understood BMJ policy on declaration of interests and declare the following interests: None. 

Edo Richard is a neurologist in the Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, the Netherlands. He combines his work as a neurologist with research into the prevention of dementia, mainly from a public health perspective.

Competing interests: I have read and understood BMJ policy on declaration of interests and declare the following interests: None. 

Eric B Larson is a senior investigator, formerly vice president for research and healthcare innovation, and executive director of the Kaiser Permanente Washington Health Research Institute. He is also a professor of medicine and health services at the University of Washington.

Competing interests: I have read and understood BMJ policy on declaration of interests and declare the following interests: Royalties from UpToDate.

Carol Brayne is director of the Cambridge Institute of Public Health, and lead investigator for the Cognitive Function and Ageing Studies.

Competing interests: I have read and understood BMJ policy on declaration of interests and declare the following interests: None.