Background The rise of Big Data-driven health research challenges the assumed contribution of medical research to the public good, raising questions about whether the status of such research as a common good should be taken for granted, and how public trust can be preserved. Scandals arising out of sharing data during medical research have pointed out that going beyond the requirements of law may be necessary for sustaining trust in data-intensive health research. We propose building upon the use of a social licence for achieving such ethical governance. Main text We performed a narrative review of the social licence as presented in the biomedical literature. We used a systematic search and selection process, followed by a critical conceptual analysis. The systematic search resulted in nine publications. Our conceptual analysis aims to clarify how societal permission can be granted to health research projects which rely upon the reuse and/or linkage of health data. These activities may be morally demanding. For these types of activities, a moral legitimation, beyond the limits of law, may need to be sought in order to preserve trust. Our analysis indicates that a social licence encourages us to recognise a broad range of stakeholder interests and perspectives in data-intensive health research. This is especially true for patients contributing data. Incorporating such a practice paves the way towards an ethical governance, based upon trust. Public engagement that involves patients from the start is called for to strengthen this social licence. Conclusions There are several merits to using the concept of social licence as a guideline for ethical governance. Firstly, it fits the novel scale of data-related risks; secondly, it focuses attention on trustworthiness; and finally, it offers co-creation as a way forward. Greater trust can be achieved in the governance of data-intensive health research by highlighting strategic dialogue with both patients contributing the data, and the public in general. This should ultimately contribute to a more ethical practice of governance.

Background Patients and publics are generally positive about data-intensive health research. However, conditions need to be fulfilled for their support. Ensuring confidentiality, security, and privacy of patients’ health data is pivotal. Patients and publics have concerns about secondary use of data by commercial parties and the risk of data misuse, reasons for which they favor personal control of their data. Yet, the potential of public benefit highlights the potential of building trust to attenuate these perceptions of harm and risk. Nevertheless, empirical evidence on how conditions for support of data-intensive health research can be operationalized to that end remains scant. Objective This study aims to inform efforts to design governance frameworks for data-intensive health research, by gaining insight into the preferences of patients and publics for governance policies and measures. Methods We distributed a digital questionnaire among a purposive sample of patients and publics. Data were analyzed using descriptive statistics and nonparametric inferential statistics to compare group differences and explore associations between policy preferences. Results Study participants (N=987) strongly favored sharing their health data for scientific health research. Personal decision-making about which research projects health data are shared with (346/980, 35.3%), which researchers/organizations can have access (380/978, 38.9%), and the provision of information (458/981, 46.7%) were found highly important. Health data–sharing policies strengthening direct personal control, like being able to decide under which conditions health data are shared (538/969, 55.5%), were found highly important. Policies strengthening collective governance, like reliability checks (805/967, 83.2%) and security safeguards (787/976, 80.6%), were also found highly important. Further analysis revealed that participants willing to share health data, to a lesser extent, demanded policies strengthening direct personal control than participants who were reluctant to share health data. This was the case for the option to have health data deleted at any time (P<.001) and the ability to decide the conditions under which health data can be shared (P<.001). Overall, policies and measures enforcing conditions for support at the collective level of governance, like having an independent committee to evaluate requests for access to health data (P=.02), were most strongly favored. This also applied to participants who explicitly stressed that it was important to be able to decide the conditions under which health data can be shared, for instance, whether sanctions on data misuse are in place (P=.03). Conclusions This study revealed that both a positive attitude toward health data sharing and demand for personal decision-making abilities were associated with policies and measures strengthening control at the collective level of governance. We recommend pursuing the development of this type of governance policy. More importantly, further study is required to understand how governance policies and measures can contribute to the trustworthiness of data-intensive health research.

Current challenges to sustaining public support for health data research have directed attention to the governance of data-intensive health research networks. Accountability is hailed as an important element of trustworthy governance frameworks for data-intensive health research networks. Yet the extent to which adequate accountability regimes in data-intensive health research networks are currently realized is questionable. Current governance of data-intensive health research networks is dominated by the limitations of a drawing board approach. As a way forward, we propose a stronger focus on accountability as learning to achieve accountable governance. As an important step in that direction, we provide two pathways: (1) developing an integrated structure for decision-making and (2) establishing a dialogue in ongoing deliberative processes. Suitable places for learning accountability to thrive are dedicated governing bodies as well as specialized committees, panels or boards which bear and guide the development of governance in data-intensive health research networks. A continuous accountability process which comprises learning and interaction accommodates the diversity of expectations, responsibilities and tasks in data-intensive health research networks to achieve responsible and effective governance.

Dynamic consent forms a comprehensive, tailored approach for interacting with research participants. We conducted a survey study to inquire how research participants evaluate the elements of consent, information provision, communication and return of results within dynamic consent in a hypothetical health data reuse scenario. We distributed a digital questionnaire among a purposive sample of patient panel members. Data were analysed using descriptive and nonparametric inferential statistics. Respondents favoured the potential to manage changing consent preferences over time. There was much agreement between people favouring closer and more specific control over data reuse approval and those in favour of broader approval, facilitated by an opt-out system or an independent data reuse committee. People want to receive more information about reuse, outcomes and return of results. Respondents supported an interactive model of research participation, welcoming regular, diverse and interactive forms of communication, like a digital communication platform. Approval for reuse and providing meaningful information, including meaningful return of results, are intricately related to facilitating better communication. Respondents favoured return of actionable research results. These findings emphasize the potential of dynamic consent for enabling participants to maintain control over how their data are being used for which purposes by whom. Allowing different options to shape a dynamic consent interface in health data reuse in a personalized manner is pivotal to accommodate plurality in a flexible though robust manner. Interaction via dynamic consent enables participants to tailor the elements of participation they deem relevant to their own preferences, engaging diverse perspectives, interests and preferences.