There is a growing expectation, or even requirement, for researchers to deposit a variety of research data in data repositories as a condition of funding or publication. This expectation recognizes the enormous benefits of data collected and created for research purposes being made available for secondary uses, as open science gains increasing support. This is particularly so in the context of big data, especially where health data is involved. There are, however, also challenges relating to the collection, storage, and re-use (...) of research data. This paper gives a brief overview of the landscape of data sharing via data repositories and discusses some of the key ethical issues raised by the sharing of health-related research data, including expectations of privacy and confidentiality, the transparency of repository governance structures, access restrictions, as well as data ownership and the fair attribution of credit. To consider these issues and the values that are pertinent, the paper applies the deliberative balancing approach articulated in the Ethics Framework for Big Data in Health and Research to the domain of Openness in Big Data and Data Repositories. Please refer to that article for more information on how this framework is to be used, including a full explanation of the key values involved and the balancing approach used in the case study at the end. (shrink)

To ensure that the information resulting from research is relevant to patients, the Patient‐Centered Outcomes Research Institute eschews the “traditional health research” paradigm, in which investigators drive all aspects of research, in favor of one in which patients assume the role of research partner. If we accept the premise that patient engagement can offer fresh perspectives that shape research in valuable ways, then at least two important sets of questions present themselves. First, how are patients being engaged—and how should they (...) be engaged? Second, which patients are being engaged—and which patients should be? This set has received relatively less attention, and the neglect is surprising, given that the “who” question is conceptually prior to the question of “how.”This article focuses attention on the “who” of patient engagement in research. First, we provide background on the rationale for patient engagement, underscoring the importance of ensuring the representativeness of engaged patients. Second, we present what little is known about patients engaged in PCORI‐funded research. Third, we identify and discuss the ethical implications of ways in which current practices of patient identification and recruitment may lead to a lack of representativeness. These practices include reliance on the well‐connected and well‐informed, reliance on patients who are not well trained or well‐informed, and reliance on patient advocacy organizations. Finally, we consider several strategies for addressing these pitfalls in order to maximize the positive goals of patient engagement. Patient engagement is intended to address the inability of researchers, funders, and others to fully represent patient views and priorities, but without sufficient attention, the patients selected for this role may still leave important gaps. (shrink)

A key ethical issue arising in data linkage research relates to consent requirements. Patients’ consent preferences in the context of health research have been explored but their consent preferences regarding data linkage specifically have been under-explored. In addition, the views on data linkage are often those of patient groups. As a result, little is known about lay people’s views and their preferences about consent requirements in the context of data linkage. This study explores lay people’s views and justifications regarding the (...) acceptability of conducting data linkage research without obtaining consent. (shrink)

Regulation and governance of medical research is frequently criticised by researchers. In this paper, we draw on Everett Hughes’ concepts of professional licence and professional mandate, and on contemporary sociological theory on risk regulation, to explain the emergence of research governance and the kinds of criticism it receives. We offer explanations for researcher criticism of the rules and practices of research governance, suggesting that these are perceived as interference in their mandate. We argue that, in spite of their complaints, researchers (...) benefit from the institutions of governance and regulation, in particular by the ways in which regulation secures the social licence for research. While it is difficult to answer questions such as: “Is medical research over-regulated?” and “Does the regulation of medical research successfully protect patients or promote ethical conduct?”, a close analysis of the social functions of research governance and its relationship to risk, trust, and confidence permits us to pose these questions in a more illuminating way. (shrink)

Discussion of uses of biomedical data often proceeds on the assumption that the data are generated and shared solely or largely within the health sector. However, this assumption must be challenged because increasingly large amounts of health and well-being data are being gathered and deployed in cross-sectoral contexts such as social media and through the internet of things and wearable devices. Cross-sectoral sharing of data thus refers to the generation, use and linkage of biomedical data beyond the health sector. This (...) paper considers the challenges that arise from this phenomenon. If we are to benefit fully, it is important to consider which ethical values are at stake and to reflect on ways to resolve emerging ethical issues across ecosystems where values, laws and cultures might be quite distinct. In considering such issues, this paper applies the deliberative balancing approach of the Ethics Framework for Big Data in Health and Research to the domain of cross-sectoral big data. Please refer to that article for more information on how this framework is to be used, including a full explanation of the key values involved and the balancing approach used in the case study at the end. (shrink)

It is increasingly recognised that evidence generated using “real-world data” is crucial for assessing the safety and effectiveness of health-related interventions. This, however, raises a number of issues, including those related to the quality of RWD, and of the scientific methods used to generate evidence from it, and the potential for those gathering and using RWD be driven by commercial, political, professional or personal self-interest. This article is an application of the framework presented in this issue of ABR. Please refer (...) to that article for more information on how this framework is to be used, including a full explanation of the key values involved and the balancing approach used in the case study at the end to demonstrate how those generating or using RWD can make use of values when deliberating about ethical issues. (shrink)