Empirical evidence suggests that while people hold the capacity to control their data in high regard, they increasingly experience a loss of control over their data in the online world. The capacity to exert control over the generation and flow of personal information is a fundamental premise to important values such as autonomy, privacy, and trust. In healthcare and clinical research this capacity is generally achieved indirectly, by agreeing to specific conditions of informational exposure. Such conditions can be openly stated (...) in informed consent documents or be implicit in the norms of confidentiality that govern the relationships of patients and healthcare professionals. However, with medicine becoming a data-intense enterprise, informed consent and medical confidentiality, as mechanisms of control, are put under pressure. In this paper we explore emerging models of informational control in data-intense healthcare and clinical research, which can compensate for the limitations of currently available instruments. More specifically, we discuss three approaches that hold promise in increasing individual control: the emergence of data portability rights as means to control data access, new mechanisms of informed consent as tools to control data use, and finally, new participatory governance schemes that allow individuals to control their data through direct involvement in data governance. We conclude by suggesting that, despite the impression that biomedical big data diminish individual control, the synergistic effect of new data management models can in fact improve it. (shrink)

The collapse of confidence in anonymization as a robust approach for preserving the privacy of personal data has incited an outpouring of new approaches that aim to fill the resulting trifecta of technical, organizational, and regulatory privacy gaps left in its wake. In the latter category, and in large part due to the growth of Big Data–driven biomedical research, falls a growing chorus of calls for criminal and penal offences to sanction wrongful re-identification of “anonymized” data. This chorus cuts across (...) the fault lines of polarized privacy law scholarship that at times seems to advocate privacy protection at the expense of Big Data research or vice versa. Focusing on Big Data in the context of biomedicine, this article surveys the approaches that criminal or penal law might take toward wrongful re-identification of health data. It contextualizes the strategies within their respective legal regimes as well as in relation to emerging privacy debates focusing on personal data use and data linkage and assesses the relative merit of criminalization. We conclude that this approach suffers from several flaws and that alternative social and legal strategies to deter wrongful re-identification may be preferable. (shrink)

Due to modern biochemistry and, in particular, recent developments in genomics, proteomics, and bioinformatics, human samples have become the most important raw materials for advancement in the health sciences. Such material has been at the center of fundamental biomedical research for a long time. What is new is its increased usefulness in research with direct clinical relevance, such as the development of drugs. Because of the larger commercial involvement in such research, this has also led to greater economic interests in (...) human biological material and in the information that can be extracted from it. (shrink)

In the biomedical field, calls for the generation of new regulations or for the amendment of existing regulations often follow the emergence of apparently new research practices (such as embryonic stem cell research), clinical practices (such as facial transplantation) and entities (such as Avian Influenza/’Bird Flu’). Calls for regulatory responses also arise as a result of controversies which bring to light longstanding practices, such as the call for increased regulation of human tissue collections that followed the discovery of unauthorised post-mortem (...) organ retention. Whilst it seems obvious that new regulations should only be generated if existing regulations are inadequate (a practice referred to in this paper as ‘regulatory syncretism’), this does not always occur in practice. This paper examines the conceptual steps involved in generating regulatory responses to emerging phenomena. Two decision points are identified. First, a stance is taken as to whether the emerging phenomenon raises unique ethical or legal issues (exceptionalism versus non-exceptionalism). Second, the decision is made as to whether new regulation should be generated only for truly unique phenomena (syncretism versus asyncretism). It is argued here that it is important to make a careful assessment of novelty, followed by a reflective and deliberate choice of regulatory syncretism or asyncretism, since each type of regulatory response has advantages which need to be harnessed and disadvantages which need to be managed—something that can only occur if regulators are attentive to the choices they are making. (shrink)

Biomedical innovation and translation are increasingly emphasizing research using “big data.” The hope is that big data methods will both speed up research and make its results more applicable to “real-world” patients and health services. While big data research has been embraced by scientists, politicians, industry, and the public, numerous ethical, organizational, and technical/methodological concerns have also been raised. With respect to technical and methodological concerns, there is a view that these will be resolved through sophisticated information technologies, predictive algorithms, (...) and data analysis techniques. While such advances will likely go some way towards resolving technical and methodological issues, we believe that the epistemological issues raised by big data research have important ethical implications and raise questions about the very possibility of big data research achieving its goals. (shrink)

Denmark is a society that has already moved towards Big Data and a Learning Health Care System. Data from routine healthcare has been registered centrally for years, there is a nationwide tissue bank, and there are numerous other available registries about education, employment, housing, pollution, etcetera. This has allowed Danish researchers to study the link between exposures, genetics and diseases in a large population. This use of public registries for scientific research has been relatively uncontroversial and has been supported by (...) facilitative regulation that allows data to be used without the consent of data subjects. However, in the future much of the data will not be held by public authorities but by private companies. What are the implications of this shift for the governance of the research use of the data? This paper will argue that increased involvement of Research Ethics Committees and better training of researchers are necessary; and that some form of consent will have to be re-introduced. Four different consent models will be discussed: Opt-Out, Broad/Blanket consent, Dynamic consent, and Meta consent. It will be argued that a governance model including a possibility for citizens to make meta-choices strikes the best balance between individual and public interests. (shrink)