The trading of our personal health data seems inevitable. But why? What if the market for this new economy lies not in real needs, but instead in the expedient conflation of true illness with the desire to monitor ourselves? Is there a risk that this confused appetite could detract from the real benefits digital can bring to the care of the sick?
Oscar Wilde once said “few things in life are made better by an app.” Maybe he didn’t. But I can imagine it’s the sort of dismissive, biting criticism he would waft at Telenti et al’s vision for the future of medical records and big data. Writing in the Lancet, the authors first lay open buried truths about electronic health records: they are built for business, not for people; the interface and usability is usually poor; information sharing between institutions is remarkably difficult; individuals’ data are harvested and sold for financial benefit. They then lay out the injustice: it is third parties who profit from individuals’ health related data, not those from whom it is gleaned.
Telenti’s team propose a fairer future: one where “de-identified medical data could be shared or sold by the owner.” To illustrate their vision they draw parallels with Uber drivers who can monetise their car and time: “an individual may choose to ‘rent’ their MRI imaging to a company for research, … or trade their health data for a lower insurance premium,” for instance.
The authors, thought leaders in “digital medicine,” are exceptionally placed to comment on the future form of this ballooning field. Yet something jars about the prospect of individuals monetising their health data in such a way. Why? After all, a market for biometric and medical data already exists. So when those data are placed into individuals’ hands to profit from as they so wish, where is the problem?
In the calendar of human history, it is only in the last tick of the clock that we have used the word “data” to describe the forces at work in our lives. Data was historically thought subordinate to information, knowledge, and wisdom—a relationship eloquently framed by TS Eliot—but now finds itself the main player. The hijacking of our dopaminergic systems to convert attention into data has created our newest economy, and in exchange for our input, we are richly rewarded with a more “personalised” experience of the digital world. Criticism of this exchange has only recently entered mainstream public debate, and some have warned that this economy will reduce humans to mere data generating machines. Either way, the attention economy has grown; manipulation of our innate desire for connection and reward appears to conquer individual willpower and control. And it does so at scale. For a handful, the possession of digital data in this equation now leverages remarkable wealth and, as is becoming increasingly apparent, control.
If possession and control are important, when it comes to health data would Telenti’s proposal redress the balance? If we ignore for a minute a fundamental and valid question regarding data ownership—whether a patient actually “owns” data if they are generated by a hospital’s MRI machine—does the handing over of control to the patient improve individual health outcomes? And would it rectify an injustice?
The authors’ vision would certainly make health data a currency, traded at the individual level. But if history tells us that individuals seek to accrue capital, we need to ask: what would investment look like in this economy? And who would benefit?
If measuring and monitoring makes cash, people will increasingly choose to measure and monitor. For those impoverished by the burden of chronic disease, financial compensation for their interaction with health professionals may be a welcome source of income. For those who wish to see patienthood recognised as a profession, it may be another celebrated step in that direction. But one thing is for certain: as large numbers of us sell our physiological metrics, upload our biochemistry, and share our cross sectional imaging, massive data are generated to help train algorithms. Deep learning needs deep data. But what do we know about those who are most likely to collect and trade their healthcare data? How representative a sample are they of the sick, the well, the worried? What effect does training knowledge systems on such a sample have on our understanding of illness, its prevention, and treatment?
The potential for unintended consequences is real. Unnecessary and excessive monitoring of normal physiology may be of value to a company wishing to train algorithms, but how honestly have we reflected on the value of widespread monitoring to each of us? At the individual level could it engender a more obsessive, neurotic relationship with our bodies; one where health is only defined by a supportive digital trail? Furthermore, when our interaction with healthcare professionals is not restricted to the seeking of cure, relief, or empathy, but rather becomes an opportunity for financial reward, the pasture grows ever more fertile for overinvestigation.
Conflation of “monitoring health” and “treating illness”
Concerns aside, there is an inevitability about the future that Telenti et al propose. Possibly it is already here. So, if it was the insatiable hunger of our dopaminergic system that allowed the attention economy to flourish, what is fuelling the health data economy? Because, seen from the unglamorous end of healthcare (looking after the unwell), something about the digital health revolution doesn’t quite make sense: there exists a wristwatch able to correlate our minute to minute ECG with our asparagus intake, yet a computer on an acute medical unit takes 14 minutes to switch on, and the medical regulator’s response to reporting rota gaps is to issue a flowchart. Why the disparity?
The answer may lie in the following: the act of “monitoring health” is subtly but frequently conflated with the act of “treating illness.” Look carefully, and you will spot this in much of the lay literature on “digital health.” This marketing sleight of hand inflates the scope and promise of many disruptive digital technologies. It bolsters their cause and widens their footprint. The health monitoring market is huge, but many of the myriad digital health monitoring products would struggle to demonstrate the real world benefits necessary to justify government funding. And while the treatment of true illness is seen as an endeavour worthy of support, this population represents too narrow, particular, and unpredictable a market. The solution—from an innovator’s perspective—is to conflate the two aims. But this conceptual conflation isn’t successful on its own: it requires an appetite and obsession with the monitoring of our data.
I have no doubt that digital holds huge promise in healthcare, but genuine illness is a different state from health. They are related, but not the same—just as solid is a different state from liquid. They may lie on a continuum, but the behaviour of the substance is recognisably different; the molecules have arranged themselves to take up a new form. Susan Sontag used the terms “Kingdom of the well” and “Kingdom of the sick.” The distinction is important, because while there is good reason to preserve and foster one’s health, the tools used in the one state do not necessarily translate into the other. A pair of skis is great for the powder on a glacier but not much use in a fast flowing river.
Some may challenge this binary definition of disease. And digital innovation will likely diffuse into the grisly realm of illness. But the metaphor is important: if we are to get the most out of the promise of digital medicine, it helps to be clear and honest about whether we’re looking to build skis or a life raft; whether we are collecting data, accruing capital, or treating the sick. Skis are fun, but shouldn’t be sold to those struggling to stay afloat.
There is big business to be found at the intersection of health, illness, medicine, and data. We are witnessing a scramble over who has the tightest grip on the reins. Ten years ago, the front cover of Time magazine read: “You control the information age. Welcome to your world.” The question is how much control do we each want, and at what price does it come? In a desperate rush to disrupt and redistribute a perceived injustice in the ownership of medical information, there is a risk that we walk into a more sophisticated, but equally controlling relationship with our own health.
The Theranos, Facebook, and Cambridge Analytica scandals have challenged both our faith in the promise of disruptive technologies and our trust that data are used honourably. It has called us to question what we want out of big tech, and seeded scepticism about what it wants for us. The convenience we all pursue may come at a price. While there is enormous potential for the digital revolution to aid us in the care of the sick, we should not assume that it is necessarily being directed towards the most challenging problems in healthcare.
Robin Baddeley, editorial registrar, The BMJ.
 Telenti A, Steinhubl SR, Topol EJ. Rethinking the medical record. Lancet 2018;391(10125):1013. http://www.thelancet.com/journals/lancet/article/PIIS0140-6736(18)30538-5/abstract
 TS Eliot. The Rock. 1934.
 Yuval Noah Harari. Big data, Google, and the end of free will. Financial Times. 26 August 2016. https://www.ft.com/content/50bb4830-6a4c-11e6-ae5b-a7cc5dd5a28c
 Susan Sontag. Illness as Metaphor. 1978.