Share, but respectfully and with conditions. That's one conclusion from 'Patients’ and public views and attitudes towards the sharing of health data for research: a narrative review of the empirical evidence' by Shona Kalkman, Johannes van Delden, Amitava Banerjee, Benoît Tyl, Menno Mostert and Ghislaine van Thiel in (2021) 48(1) Journal of Medical Ethics, abstracted as
Introduction International sharing of health data opens the door to the study of the so-called ‘Big Data’, which holds great promise for improving patient-centred care. Failure of recent data sharing initiatives indicates an urgent need to invest in societal trust in researchers and institutions. Key to an informed understanding of such a ‘social license’ is identifying the views patients and the public may hold with regard to data sharing for health research. We performed a narrative review of the empirical evidence addressing patients’ and public views and attitudes towards the use of health data for research purposes. The literature databases PubMed (MEDLINE), Embase, Scopus and Google Scholar were searched in April 2019 to identify relevant publications. Patients’ and public attitudes were extracted from selected references and thematically categorised. Twenty-seven papers were included for review, including both qualitative and quantitative studies and systematic reviews. Results suggest widespread—though conditional—support among patients and the public for data sharing for health research. Despite the fact that participants recognise actual or potential benefits of data research, they expressed concerns about breaches of confidentiality and potential abuses of the data. Studies showed agreement on the following conditions: value, privacy, risk minimisation, data security, transparency, control, information, trust, responsibility and accountability. Our results indicate that a social license for data-intensive health research cannot simply be presumed. To strengthen the social license, identified conditions ought to be operationalised in a governance framework that incorporates the diverse patient and public values, needs and interests.
The authors argue
Large-scale, international data sharing opens the door to the study of so-called ‘Big Data’, which holds great promise for improving patient-centred care. Big Data health research is envisioned to take precision medicine to the next level through increased understanding of disease aetiology and phenotypes, treatment effects, disease management and healthcare expenditure. However, lack of public trust is proven to be detrimental to the goals of data sharing. The case of care.data in the UK offers a blatant example of a data sharing initiative gone awry. Criticism predominantly focused on limited public awareness and lack of clarity on the goals of the programme and ways to opt out. Citizens are becoming increasingly aware and critical of data privacy issues, and this warrants renewed investments to maintain public trust in data-intensive health research. Here, we use the term data-intensive health research to refer to a practice of grand-scale capture, (re)use and/or linkage of a wide variety of health-related data on individuals.
Within the European Union (EU), the recently adopted General Data Protection Regulation (GDPR) (EU 2016/679) addresses some of the concerns the public may have with respect to privacy and data protection. One of the primary goals of the GDPR is to give individuals control over their personal data, most notably through consent. Other lawful grounds for the processing of personal data are listed, but it is unclear how these would exactly apply to scientific research. Legal norms remain open to interpretation and thus offer limited guidance to researchers. In Recital 33, the GDPR actually mentions that additional ethical standards are necessary for the processing of personal data for scientific research. This indicates a recognised need for entities undertaking activities likely to incite public unease to go beyond compliance with legal requirements. Complementary ethical governance then becomes a prerequisite for securing public trust in data-intensive health research.
A concept that could be of use in developing ethical governance is that of a ‘social license to operate’. The social license captures the notion of a mandate granted by society to certain occupational groups to determine for themselves what constitutes proper conduct, under the condition that such conduct is in line with society’s expectations. The term ‘social license’ was first used in the 1950s by American sociologist Everett Hughes to address relations between professional occupations and society. The concept has been used since to frame, for example, corporate social responsibility in the mining industry, governance of medical research in general and of data-intensive health research more specifically. As such, adequate ethical governance then becomes a precondition for obtaining a social license for data sharing activities.
Key to an informed understanding of the social license is identifying the expectations society may hold with regard to sharing of and access to health data. Here, relevant societal actors are the subjects of Big Data health research, constituting both patients and the general public. Identification of patients’ and public views and attitudes allows for a better understanding of the elements of a socially sanctioned governance framework. We know of the existence of research papers that have captured these views using quantitative or qualitative methods or a combination of both. So far, systematic reviews of the literature have limited their scope to citizens of specific countries, qualitative studies only or the sharing of genomic data. Therefore, we performed an up-to-date narrative review of both quantitative and qualitative studies to explore predominant patient and public views and attitudes towards data sharing for health research.
In discussing Conditions for sharing the authors comment
Widespread willingness to share data for health research very rarely led to participants’ unconditional support. Studies showed agreement on the following conditions for responsible data sharing: value, privacy, minimising risks, data security, transparency, control, information, trust, responsibility and accountability.
Value
One systematic review found that participants found it important that the research as a result of data sharing should be in the public’s interest and should reflect participants’ values. The NICE Citizens Council advocated for appropriate systems and good working practices to ensure a consistent approach to research planning, data capture and analysis.
Privacy, risks and data security
The need to protect individuals’ privacy was considered paramount and participants often viewed deidentification of personal data as a top privacy measure. One survey among US patients with cancer found that only 20% (n=228) of participants found linkage of individuals with their deidentified data acceptable for return of individual health results and to support further research. Secured access to databases was considered an important measure to ensure data security in data sharing activities. A systematic review of participants’ attitudes towards data sharing showed that people established risk minimisation as another condition for data sharing. Findings by Mazor et al suggest that patients only support studies that offer value and minimise security risks.
Transparency and control
Conditions regarding transparency were information about how data will be shared and with whom, the type of research that is to be performed, by whom the research will be performed, information on data sharing and monitoring policies and database governance, conditions framing access to data and data access agreements, and any partnerships with the pharmaceutical industry. More generally, participants expressed the desire to be involved in the data sharing process, to be notified when their data are (re)used and to be informed of the results of studies using their data. Spencer et al identified use of an electronic interface as a highly valued means to enable greater control over consent choices. When asked about the use of personal data for health research by the NHS, UK citizens were typically willing to accept models of consent other than the ones they would prefer. Acceptance of consent models with lower levels of individual control was found to be dependent on a number of factors, including adequate transparency, control over detrimental use and commercialisation, and the ability to object, particularly to any processing considered to be inappropriate or particularly sensitive.
Information and trust
One systematic review identified trust in the ability of the original institution to carry out the oversight tasks as a major condition for responsible data sharing. Appropriate education and information about data sharing was thought to include public campaigns to inform stakeholders about Big Data and information communicated at open days of research institutions (such as NICE) to ensure people understand what their data are being used for and to reassure them that personal data will not be passed on or sold to other organisations. The informed consent process for study participation was believed to include information about the fact that individuals’ data could potentially be shared, the objectives of data sharing and (biobank) research, the study’s data sharing plans, governance structure, logistics and accountability.
Responsibility and accountability
Participants often placed the responsibility for data sharing practices on the shoulders of researchers. Secondary use of data collected earlier for scientific research was viewed to require a data access committee that involves a researcher from the original research project, a clinician, patient representative and a participant in the original study. Researchers of the original study were required to monitor data used by other researchers. In terms of accountability, patient and public groups in Italy (n=280) placed high value on sanctions for misuse of data. Information on penalties or other consequences of a breach of protection or misuse was considered important by many. Discussion In this study, we narratively reviewed 27 papers on patients’ and public views on and attitudes towards the use of health data for scientific research. Studies reported a widespread—though conditional—support for the linkage and sharing of data for health research. The only outlier seems to be the finding that just over half (n=25) of the NICE Citizens Council answered ‘no’ to the question whether they had any concerns if NICE used anonymised data to fill in the gaps if NICE was not getting enough evidence in ‘the usual ways’. However, we hasten to point out that the question about willingness to share is different from the question whether people have concerns or not. In addition, after a 2-day discussion meeting Council members were perhaps more sensitised to the potential concerns regarding data sharing. Therefore, we suggest that the way and context within which questions are phrased may influence the answers people give.
Overall, people expressed similar motivations to share their data, perceived similar benefits (despite some variation between patients and citizens), yet at the same time displayed a range of concerns, predominantly relating to confidentiality and data security, awareness about access and control, and potential harms resulting from these risks. Both patient and public participants conveyed that certain factors would increase or reduce their willingness to have their data shared. For example, the presence of privacy-protecting measures (eg, data deidentification and the use of secured databases) seemed to increase willingness to share, as well as transparency and information about data sharing processes and responsibilities. The identified views and attitudes appeared to come together in the conditions stipulated by participants: value, privacy and confidentiality, minimising risks, data security, transparency, control, information, trust, responsibility and accountability.
In our Introduction, we mentioned that identifying patients’ and public views and attitudes allows for a better understanding of the elements of a socially sanctioned governance framework. In other words, what work should our governance framework be doing in order to obtain a social license? This review urges researchers and institutions to address people’s diverse concerns and to make an effort to meet the conditions identified. Without these conditions, institutions lack trustworthiness, which is vital for the proceedings of medicine and biomedical science. As such, a social license is not a ‘nice to have’ but a ‘need to have’. Our results also confirm that patients and the public indeed care about more than legal compliance alone, and wish to be engaged through information, transparency and control. This work supports the findings of a recent systematic review into ethical principles of data sharing as specified in various international ethical guidelines and literature. What this body of research implies is considerable diversity of values and beliefs both between and within countries.
The goal of this narrative review was to identify the most internationally dominant, aggregated patient and public views about the broad topic of data sharing for health research. We deliberately opted for the methodology of a narrative review rather than a systematic review. Most narrative reviews deal with a broad range of issues to a given topic rather than addressing a particular topic in depth. This means narrative reviews may be most useful for obtaining a broad perspective on a topic, and that they often are less useful in generating quantitative answers to specific clinical questions. However, because narrative reviews do not require specification of the search and selection strategy and the way of critically appraising literature can be variable, the connection between evidence generated by narrative reviews and (clinical) recommendations is less rigorous and risk of bias exists. This is something to take into account in this study. A risk of bias assessment was not possible due to the heterogeneity of the findings. We acknowledge that our methodological choices may have affected the discriminative power or granularity of our findings. For example, there is a difference between sharing of routinely collected health data versus secondary use of health data collected for research purposes. And we can only make loose assumptions about potential differences between patient and public views.
In addition, we should mention that this work is centred around studies conducted in Western countries as the whole Big Data space and literature is dominated by Western countries, higher socioeconomic status and Caucasians. However, most of the disease burden globally and within countries is most probably not represented in the ‘Big Data’ and so we have to stress the lack of generalisability to large parts of the world.
Nevertheless, we believe our findings point towards essential elements of a governance framework for data sharing for health research purposes. If we are to conclude that the identified conditions ought to act as the pillars of a governance framework, the next step is to identify how these conditions could be practically operationalised. For example, if people value information, transparency and control, what type of consent is most likely to valorise these conditions? And what policy for returning research results would be desirable? Once we know what to value, we can start thinking about the ways to acknowledge that value. A new challenge arising here, however, is what to do when people hold different or even conflicting values or preferences. Discrete choice experiments could help to test people’s preferences regarding specific topics, such as preferred modes of informed consent. Apart from empirical work, conceptual analysis is needed to clarify how public trust, trustworthiness of institutions and accountability are interconnected.
