IntroductionMichael Morrison reflects on healthcare and the high-tech revolution
In an op-ed piece in the New York Times, former director of the M.I.T. media lab Frank Moss offered the following scenario for consideration:
“Over the past few years, innovations like electronic health records and the use of mobile computing devices in hospitals have begun to improve medical care delivery. Consumer health information websites and online disease support groups have made millions of people active participants in their own health care.
“But imagine a far more extreme transformation, in which advances in information technology, biology and engineering allow us to move much of health care out of hospitals, clinics and doctors’ offices, and into our everyday lives.”
Moss is not alone in lauding a high-tech revolution in medicine, as evidenced by two recent high-profile publications on the future of healthcare in the United States. In November 2011 the US National Academies Board on Life Sciences announced details of the forthcoming report Towards Precision Medicine: Building a knowledge network for biomedical research and a new taxonomy of disease. This was followed in early December by the release, in e-book form of The Creative Destruction of Medicine: How the digital revolution will create better health care, by Dr Eric Topol, professor of genomics at the Scripps Research Institute. Although the focus of both of these is explicitly on the US healthcare system, trends in thinking about medicine and technology that attract attention in the US often become influential in the UK as well, making it worthwhile to pay attention to these new developments.
While each of these documents has its own distinct agenda, they and Moss’s op-ed piece, are united by two common themes; an argument that processing ever-greater volumes of data through information communication technologies (ICT) is the key to improving healthcare and reducing costs, and an emphasis on the provision of ‘personalised’ medicine through individuals’ continuous engagement with this web of information.
The Precision Medicine report argues that advances in medical and scientific research have led to “an explosion of data” which requires the development of new and integrated ICT systems to harness this diverse information for patient benefit. It proposes “an 'Information Commons', a data repository that links layers of molecular data, medical histories, including information on social and physical environments, and health outcomes to individual patients. Data would be continuously contributed to the Information Commons by the research community and from the medical records of participating patients.”
Dr Topol also envisages ICT systems linking hospital, laboratory and clinical sites combined with “wearable sensors, smart-phone apps, social networks, and whole-genome sequencing” that will ultimately “create a complete and continuously updated picture of every patient”. The common rationale for these strategies is that they will make healthcare provision more targeted, more efficient and thus reduce costs. These discussions take place primarily in the context of the US healthcare system, where health expenditure is often presented as unsustainable and ‘out of control’. In the current global economic climate proposals to make healthcare more affordable have a unilateral appeal.
It is important to realise that these accounts are not descriptions of what is currently happening in medicine, but promises about what medical technology might achieve in the future. As such, they are not only visions of future medical technology, but also of the kind of future societies in which this technology will be available and even of the types of people that will be using it. While few people would argue against ‘better healthcare’ as a desirable aim, it is worth taking a closer look at the particular claims these visions contain and the types of future worlds they imagine.
How, for example, is the development of complex, high-tech systems for collecting, collating and presenting information presented as a route to reducing healthcare costs? In part this is due to the way in which existing causes of ‘unnecessary’ healthcare costs are framed. The Precision Medicine report argues that more data, shared and collated in better ways will produce ‘more informed’ healthcare decisions and avoid “wasteful health care expenditures … incurred for treatments that are only effective in specific subgroups”. Leaving aside the question of the validity of this claim – and Daniel Callahan of the Hastings Centre, for example, has made a strong alternative case that the most pressing financial issue in US healthcare is actually the overuse of ‘high-tech’ medical procedures1 - the answer relies on the particular political-economic model of innovation embedded in these accounts.
The notion of ‘personalised medicine’ is closely allied to a concept of health and wellbeing as a matter of individual responsibility rather than a communal or social matter. Adele Clarke and colleagues at the University of California in Berkley recently observed that the deployment of medical and bio-technologies in contemporary life is increasingly associated with narratives of individual moral responsibility; projecting an individual duty to gain as much information about oneself as possible in order to ‘secure the best possible future’.2 Future patient-consumers of ‘big-data’-driven personalised medicine will be engaged in a lifelong project of self-monitoring and constant interaction with reams of information about genetic, epigenetic, physical, molecular, environmental, and social factors potentially influencing their health status. As Moss envisages it, “wireless sensors worn on your body and placed in your home would continuously monitor your vital signs and track the daily activities that affect your health, counting the number of steps you take and the quantity and quality of food you eat. Wristbands would measure your levels of arousal, attention and anxiety. Bandages would monitor cuts for infection. Your bathroom mirror would calculate your heart rate, blood pressure and oxygen level.”
To understand the rationale of these accounts it is necessary to recognise that they position health as a ‘super value’ – an obligation and a goal that trumps almost all other considerations. Continuous monitoring, combined with an increasingly prevalent focus on biological markers of potential future illness, threatens to collapse the distinction between health and disease, patient and healthy individual, bringing everyone into the realm of the ‘at risk’. Simultaneously, advances in pre-natal screening, genomic profiling and epigenetics raise the possibility of extending medical surveillance beyond the lifetime, and even beyond the body, of any given individual, locating further health risks in the behaviours, genomes, and medical histories of parents, siblings, partners, and children. Health becomes not an intermittent responsibility, to be addressed in the face of illness, but a totalising project encompassing every aspect of life where every action, from a bite of food to a decision about how travel to work in the morning becomes a source of health data to be processed and added to an ever-updating digital repository.
In turn, the model of medical innovation in these accounts is a highly commercialised one. Each new ICT interface, smart-phone app, mobile heart-rate biosensor, and self-diagnosis or self-reporting device is a new consumable product. Ultimately, by framing healthcare as a consumer product whose consumption is morally mandated, these visions enrol healthcare payers – whether states or private insurance providers – in financing this new round of technological development. The promise of reduced healthcare expenditure in the future is used as means to elicit higher levels of investment in healthcare technologies in the present, and while this may well generate a period of economic growth for the healthcare and ICT industries, the long-term benefit to those who are paying, and ultimately to patients, remains uncertain.
A further aspect of these visions is worth examining in closer detail - the particular form(s) of technology being associated with this promise. Put simply, what makes ‘big data’ a big deal? At least in part, these proposals echo a prevailing trend in the contemporary life-sciences that might be characterised as an ‘information fetish’. This approach is typified by the belief that core medical-scientific problems, perhaps even the issue of uncertainty itself, can be addressed by collecting as much information as possible; and processing it in vast, searchable databases. ‘If only enough information is available’ the argument runs ‘ all problems become technical queries to which rational, informed answers can and will ultimately be found’. However, this approach underplays the complexity of working with such large amounts of data. In the case of diagnosing disease there is a considerable amount of analytic work involved in aligning multiple signs and symptoms to produce a coherent disease concept. Collating information is not the same as interpreting it – which must necessarily involve dealing with uncertain and even conflicting outcomes.
Moreover, to be useful a diagnosis must be meaningful to the patient as well as the physician and must have utility in aiding clinical management of the patient’s symptoms. None of these aspects are automatic outcomes of data collection alone. Indeed, more data can actually make action more difficult, complex and fraught for physicians and patients. This is especially pertinent in a situation where consumerist, individualist perspectives mean that a prospective patient is not only compelled to make choices, but is held solely accountable for the consequences of those choices.
Perhaps the clearest example of how more information does not necessarily resolve difficult choices is found when no therapeutic interventions are possible, for example in prenatal genetic screening for non-fatal but untreatable conditions. Visions of ‘big data’-driven medicine also take the large-scale sharing of large amounts of individual health information as an inherently desirable outcome. The serious concerns about privacy and informed consent to sharing of personal information associated with existing genetic databases and healthcare records are either overlooked or, perhaps more worryingly, seen as ‘irrational’ social barriers to be overcome. All told, ‘big data’ may promise more than it can deliver and the costs of these plans to reduce healthcare costs may be more than we are willing to pay.
1 Callahan, D., Taming the Beloved Beast: Why Medical Technology Costs are Destroying Our Health Care System. Princeton, NJ: Princeton University Press, 2009.
2 Adams, V., Murphy, M. and Clarke, A.E., Anticipation: Technoscience, life, affect and temporality. Subjectivity 28, 2009: 246–265.