#Big data, biomedicine and participation: from NSA to NIH?

In the previous post, we have seen how some scientists envision a future where technological developments in computing capacities and networks will interact with citizens’ activism and desire to participate to promote biomedical innovation and construct ‘learning health systems’. This is not the only vision regarding how we shall exploit new networking technologies to foster medical innovation. Yet in other such visions of the future of our health systems, citizen participation plays an altogether different role. Harvard med school researchers Weber, Mandl and Kohane — the last of whom co-authored the paper on data donation quoted in the previous post – argued that ‘social media, credit card purchases, census records, and numerous other types of data, despite varying degrees of quality, can help assemble a holistic view of a patient, and, in particular, shed light on social and environmental factors that may be influencing health’ (Ref.1). This is a new form of epidemiology, which is based on the capability of recording large quantities of information and – crucially – going beyond aggregate data by linking information to individual people.

Weber et al. start from the observation that other industries outside of healthcare are already using this approach very effectively. The Obama electoral campaign in 2012, for example, targeted swing voters by linking personal data from social media, census, and voter lists. This method allowed the staff of the campaign to reach swing voters personally with great precisions, i.e. delivering tailored messages, leaflets, etc. Google personalises search results with localisation data as well as chronologies of web browsing. Strikingly, Weber and colleagues also quote how the National Security Agency (NSA) in the US employs data from phone and internet companies to ‘identify terrorists’. The latter example is rather unfortunate, given the huge controversies – and indeed diplomatic crises in the case of NSA targeting of foreign citizens, including top politicians – that followed the revelation of the NSA surveillance program by Edward Snowden to The Guardian and other such venues.

The authors do recognise that the public might object to governments — in this case, health departments — collecting identifiable health related data, some of which are very sensitive indeed. Thus Weber and co-authors ruminate on how public skepticism toward health oriented surveillance programs could be addressed:

<<One constructive response [to citizens’ concerns] would be to regulate what is legal and ethical, to ensure that benefits outweigh risks, and to include patients in the decision-making process. An alternative approach would simply be to put the onus entirely on the patients and give them control over their data. However, as has been seen for far less private data, individuals are likely to share their data publicly only to regret it later when those data were used in unanticipated circumstances. To avoid paternalism, is there an effective and affordable mechanism, analogous to consent for participation in a trial, to enable patients to decide how and when their data can be shared with or “mashed up” against other databases? It may therefore be timely to convene a public forum whereby the relevant stakeholders, including citizens, the health care community, and commercial data vendors could meet to frame the policy from which legislation and ultimately technical protections for big biomedical data linkage will devolve>>

The oversight of bioethicists on the regulation of big data health programs, patient participation and the summoning of stakeholders fora are standard tools for addressing socially sensitive topics – and we should make sure that these instruments won’t be used to merely sanction decisions that are taken elsewhere.

There is however one further limitation of Weber and colleagues’ approach. They do not address how citizens’ attitudes towards their health data are being affected by the proliferation of communities of sharing, and patient-empowered networks. People are sharing data — even re-identifiable genomic data — out of solidaristic motivations, or because they are desperately trying to find a cure for their disease. So doing, citizens reveal their willingness to participate to scientific research – provided that its aims are fully disclosed and not vulnerable to exploitative extraction of value. Yet Weber and colleagues construct the agency of citizens in the big-data technological scenario in a overly passive manner, trying to protect them from risks with concepts and legal tools, such as consent, that might have been obsoleted by citizens’ practices (ref.2). There is probably little risk that health and research systems will turn into NSA-like surveillance agencies – yet citizens’ stakes in their own data must be well in sight when designing possible futures. They may well be very different from how they are commonly depicted.


1. G.M. Weber, K.D Mandl & I.S. Kohane. 2014 Finding the Missing Link for Big Biomedical Data. JAMA. doi:10.1001/jama.2013.393.

2. D. O’Connor. 2013. The Apomediated World: Regulating Research When Social Media Has Changed Research. Journal of Law, Medicine & Ethics. doi: 10.1111/jlme.12056


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