Ethical and social reflections on the proposed European Health Data Space.

The COVID-19 pandemic demonstrated the benefits of international data sharing. Data sharing enabled the health care policy makers to make decisions based on real-time data, it enabled the tracking of the virus, and importantly it enabled the development of vaccines that were crucial to mitigating the impact of the virus. This data sharing is not the norm as data sharing needs to navigate complex ethical and legal rules, and in particular, the fragmented application of the General Data Protection Regulation (GDPR). The introduction of the draft regulation for a European Health Data Space (EHDS) in May 2022 seeks to address some of these legal issues. If passed, it will create an obligation to share electronic health data for certain secondary purposes. While there is a clear need to address the legal complexities involved with data sharing, it is critical that any proposed reforms are in line with ethical principles and the expectations of the data subjects. In this paper we offer a critique of the EHDS and offer some recommendations for this evolving regulatory space.

Reconciling the biomedical data commons and the GDPR: three lessons from the EUCAN ELSI collaboratory.

The coming-into-force of the EU General Data Protection Regulation (GDPR) is a watershed moment in the legal recognition of enforceable rights to informational self-determination. The rapid evolution of legal requirements applicable to data use, however, has the potential to outstrip the capabilities of networks of biomedical data users to respond to the shifting norms. It can also delegitimate established institutional bodies that are responsible for assessing and authorising the downstream use of data, including research ethics committees and institutional data custodians. These burdens are especially pronounced for clinical and research networks that are of transnational scale, because the legal compliance burden for outbound international data transfers from the EEA is especially high. Legislatures, courts, and regulators in the EU should therefore implement the following three legal changes. First, the responsibilities of particular actors in a data sharing network should be delimited through the contractual allocation of responsibilities between collaborators. Second, the use of data through secure data processing environments should not trigger the international transfer provisions of the GDPR. Third, the use of federated data analysis methodologies that do not provide analysis nodes or downstream users access to identifiable personal data as part of the outputs of those analyses should not be considered circumstances of joint controllership, nor lead to the users of non-identifiable data to be considered controllers or processors. These small clarifications of, or modifications to, the GDPR would facilitate the exchange of biomedical data amongst clinicians and researchers.

Conceptualizing fairness in the secondary use of health data for research: A scoping review.

With the introduction of the European Health Data Space (EHDS), the secondary use of health data for research purposes is attracting more attention. Secondary health data processing promises to address novel research questions, inform the design of future research and improve healthcare delivery generally. To comply with the existing data protection regulations, the secondary data use must be fair, among other things. However, there is no clear understanding of what fairness means in the context of secondary use of health data for scientific research purposes. In response, we conducted a scoping review of argument-based literature to explore how fairness in the secondary use of health data has been conceptualized. A total of 35 publications were included in the final synthesis after abstract and full-text screening. Using an inductive approach and a thematic analysis, our review has revealed that balancing individual and public interests, reducing power asymmetries, setting conditions for commercial involvement, and implementing benefit sharing are essential to guarantee fair secondary use research. The findings of this review can inform current and future research practices and policy development to adequately address concerns about fairness in the secondary use of health data.

Crowdsourcing smartphone data for biomedical research: Ethical and legal questions.

The use of smartphones has greatly increased in the last decade and has revolutionized the way that health data are being collected and shared. Mobile applications leverage the ubiquity and technological sophistication of modern smartphones to record and process a variety of metrics relevant to human health, including behavioral measures, clinical data, and disease symptoms. Information processed by mobile applications may have significant utility for increasing biomedical knowledge, both through conventional research and emerging discovery paradigms such as citizen science. However, the ways in which smartphone-collected data may be used in nontraditional modes of biomedical discovery are not well understood, such as using data to train artificially intelligent algorithms and for product development purposes. This paper argues that the use of mobile health data for algorithm training and product development is (a) likely to become a prominent fixture in medicine, (b) likely to raise significant ethical and legal challenges, and (c) warrants immediate scrutiny by policymakers and scholars. We introduce the concept of "smartphone-crowdsourced medical data," or SCMD, and set out a broad research agenda for addressing concerns associated with this new and potentially momentous practice. We conclude that SCMD for algorithm training raises a number of ethical and legal issues which require further scholarly attention to ensure that individual interests are protected and that emerging health information sources can be used in ways that maximally, and safely, promote medical innovation.

Genomic Data as a National Strategic Resource: Implications for the Genomic Commons and International Data Sharing for Biomedical Research and Innovation.

This article provides a critical review of new policies in China, the United States, and the European Union that characterize genomic data as a national strategic resource. Specifically, we review policies that regulate human genomic data for economic, national security, or other strategic purposes rather than ethical or individual rights purposes.

The European health data space: Too big to succeed?

In May 2022, the European Commission issued the Proposal for a Regulation on the European Health Data Space (EHDS), with the aims of granting citizens increased access to and control of their (electronic) health data across the EU, and facilitating health data re-use for research, innovation, and policymaking. As the first in a series of European domain-specific "data spaces", the EHDS is a high-stakes development that will transform health data governance in the EU region. As an international consortium of experts from health policy, law, ethics and the social sciences, we are concerned that the EHDS Proposal will detract from, rather than lead to the achievement of, its stated aims. We are in no doubt on the benefits of using health data for secondary purposes, and we appreciate attempts to facilitate such uses across borders in a carefully curated manner. Based on the current draft Regulation, however, the EHDS risks undermining rather than enhancing patient control over data; hindering rather than facilitating the work of health professionals and researchers; and eroding rather than increasing the public value generated through health data sharing. Therefore, significant adjustments are needed if the EHDS is to realize its promised benefits. Besides analyzing the implications for key groups and European societies at large who will be affected by the implementation of the EHDS, this contribution advances targeted policy recommendations to address the identified shortcomings of the EHDS Proposal.

Reward systems for cohort data sharing: An interview study with funding agencies.

Data infrastructures are being constructed to facilitate cohort data sharing. These infrastructures are anticipated to increase the rate of data sharing. However, the lack of data sharing has also been framed as being the consequence of the lack of reputational or financial incentives for sharing. Some initiatives try to confer value onto data sharing by making researchers' individual contributions to research visible (i.e., contributorship) or by quantifying the degree to which research data has been shared (e.g., data indicators). So far, the role of downstream evaluation and funding distribution systems for reputational incentives remains underexplored. This interview study documents the perspectives of members of funding agencies on, amongst other elements, incentives for data sharing. Funding agencies are adopting narrative CVs to encourage evaluation of diverse research outputs and display diversity in researchers' profiles. This was argued to diminish the focus on quantitative indicators of scientific productivity. Indicators related to open science dimensions may be reintroduced if they are fully developed. Shifts towards contributorship models for research outputs are seen as complementary to narrative review.

From collected stamps to hair locks: ethical and legal implications of testing DNA found on privately owned family artifacts.

Biological samples containing DNA that is attributed to deceased relatives, can now undergo genetic testing at a reasonable cost due to revolutionary improvements in sampling, sequencing, and analytical techniques. This artifact DNA testing, or 'artDNA', includes genetic analysis of hair locks, stamps, envelopes with saliva traces or teeth. ArtDNA can reveal valuable information about a deceased relative or one's genetic background, but it also presents novel ethical dilemmas and legal uncertainties for genetic researchers and commercial testing services. In this paper, we provide an analysis of some of the unique ethical and legal risks of such testing and provide needed recommendations for practitioners of private family artDNA testing. ArtDNA testing generates ethical and legal risks regarding the privacy and autonomy of deceased individuals, the rights of living relatives over their ancestor's genetic information, and the rights of living persons to control their own genetic information. To mitigate these risks, practitioners can conduct certain preliminary testing to ascertain the identity of a DNA donor and estimate the time that has elapsed postmortem. Generally, the ethical and legal concerns will be higher when a shorter period has passed between the death of the DNA donor and the time of artifact DNA testing. Regardless, all artDNA testing present some risks, and practitioners should exercise professional judgement as necessary.

Policies to regulate data sharing of cohorts via data infrastructures: An interview study with funding agencies.

BACKGROUND: Platforms are being constructed to stimulate cohort data sharing. Nevertheless, many policy barriers impede data sharing. Various interventions have been proposed to address these barriers, including incentive creation and data sharing mandates for researchers. AIM: To understand funding agencies' perspectives on policy interventions to encourage data sharing. METHODS: Members of funding agencies were recruited to participate in semi-structured interviews. Nearly all funding agencies are situated in European countries. Interview transcripts were analyzed through inductive content analysis. RESULTS: Mandates for cohort data sharing are not supported by agencies due to data protection regulations and the preconditions for issuing mandates. Recommendation of platforms may be based on certification schemes, such as repository accreditation. Monitoring mechanisms for cohort data sharing are currently absent, which complicates assessing compliance of researchers with funding agencies' policies and evidence production. Funding agencies are not imposing conditions on data access committees. CONCLUSIONS: Policy measures that, in some ways, restrict the decision-making authority of researchers in terms of data sharing are not generally supported. Concrete steps are proposed to enable evidence-based policy making. Incentive design is paramount if funding agencies do not wish to impose restrictions on the decision-making authority of researchers.

Will the European Health Data Space change data sharing rules?

Questions of consent and public interest research loom large.

Credit and Recognition for Contributions to Data-Sharing Platforms Among Cohort Holders and Platform Developers in Europe: Interview Study.

BACKGROUND: The European Commission is funding projects that aim to establish data-sharing platforms. These platforms are envisioned to enhance and facilitate the international sharing of cohort data. Nevertheless, broad data sharing may be restricted by the lack of adequate recognition for those who share data. OBJECTIVE: The aim of this study is to describe in depth the concerns about acquiring credit for data sharing within epidemiological research. METHODS: A total of 17 participants linked to European Union-funded data-sharing platforms were recruited for a semistructured interview. Transcripts were analyzed using inductive content analysis. RESULTS: Interviewees argued that data sharing within international projects could challenge authorship guidelines in multiple ways. Some respondents considered that the acquisition of credit for articles with extensive author lists could be problematic in some instances, such as for junior researchers. In addition, universities may be critical of researchers who share data more often than leading research. Some considered that the evaluation system undervalues data generators and specialists. Respondents generally looked favorably upon alternatives to the current evaluation system to potentially ameliorate these issues. CONCLUSIONS: The evaluation system might impede data sharing because it mainly focuses on first and last authorship and undervalues the contributor's work. Further movement of crediting models toward contributorship could potentially address this issue. Appropriate crediting mechanisms that are better aligned with the way science ought to be conducted in the future need to be developed.

Factors that influence data sharing through data sharing platforms: A qualitative study on the views and experiences of cohort holders and platform developers.

BACKGROUND: Infrastructures are being developed to enhance and facilitate the sharing of cohort data internationally. However, empirical studies show that many barriers impede sharing data broadly. PURPOSE: Therefore, our aim is to describe the barriers and concerns for the sharing of cohort data, and the implications for data sharing platforms. METHODS: Seventeen participants involved in developing data sharing platforms or tied to cohorts that are to be submitted to platforms were recruited for semi-structured interviews to share views and experiences regarding data sharing. RESULTS: Credit and recognition, the potential misuse of data, loss of control, lack of resources, socio-cultural factors and ethical and legal barriers are elements that influence decisions on data sharing. Core values underlying these reasons are equality, reciprocity, trust, transparency, gratification and beneficence. CONCLUSIONS: Data generators might use data sharing platforms primarily for collaborative modes of working and network building. Data generators might be unwilling to contribute and share for non-collaborative work, or if no financial resources are provided for sharing data.

Ethics review of big data research: What should stay and what should be reformed?

BACKGROUND: Ethics review is the process of assessing the ethics of research involving humans. The Ethics Review Committee (ERC) is the key oversight mechanism designated to ensure ethics review. Whether or not this governance mechanism is still fit for purpose in the data-driven research context remains a debated issue among research ethics experts. MAIN TEXT: In this article, we seek to address this issue in a twofold manner. First, we review the strengths and weaknesses of ERCs in ensuring ethical oversight. Second, we map these strengths and weaknesses onto specific challenges raised by big data research. We distinguish two categories of potential weakness. The first category concerns persistent weaknesses, i.e., those which are not specific to big data research, but may be exacerbated by it. The second category concerns novel weaknesses, i.e., those which are created by and inherent to big data projects. Within this second category, we further distinguish between purview weaknesses related to the ERC's scope (e.g., how big data projects may evade ERC review) and functional weaknesses, related to the ERC's way of operating. Based on this analysis, we propose reforms aimed at improving the oversight capacity of ERCs in the era of big data science. CONCLUSIONS: We believe the oversight mechanism could benefit from these reforms because they will help to overcome data-intensive research challenges and consequently benefit research at large.

Data Sharing in Biomedical Sciences: A Systematic Review of Incentives.

Background: The lack of incentives has been described as the rate-limiting step for data sharing. Currently, the evaluation of scientific productivity by academic institutions and funders has been heavily reliant upon the number of publications and citations, raising questions about the adequacy of such mechanisms to reward data generation and sharing. This article provides a systematic review of the current and proposed incentive mechanisms for researchers in biomedical sciences and discusses their strengths and weaknesses. Methods: PubMed, Web of Science, and Google Scholar were queried for original research articles, editorials, and opinion articles on incentives for data sharing. Articles were included if they discussed incentive mechanisms for data sharing, were applicable to biomedical sciences, and were written in English. Results: Although coauthorship in return for the sharing of data is common, this might be incompatible with authorship guidelines and raise concerns over the ability of secondary analysts to contest the proposed research methods or conclusions that are drawn. Data publication, citation, and altmetrics have been proposed as alternative routes to credit data generators, which could address these disadvantages. Their primary downsides are that they are not well-established, it is difficult to acquire evidence to support their implementation, and that they could be gamed or give rise to novel forms of research misconduct. Conclusions: Alternative recognition mechanisms need to be more commonly used to generate evidence on their power to stimulate data sharing, and to assess where they fall short. There is ample discussion in policy documents on alternative crediting systems to work toward Open Science, which indicates that that there is an interest in working out more elaborate metascience programs.

The Data Governance Act and the EU's move towards facilitating data sharing.

The implementation of the EU General Data Protection Regulation (GDPR) has had significant impacts on biomedical research, often complicating data sharing among researchers. The recently announced proposal for a new EU Data Governance Act is a promising step towards facilitating data sharing, if it can interplay well with the GDPR.

An agenda-setting paper on data sharing platforms: euCanSHare workshop.

Various data sharing platforms are being developed to enhance the sharing of cohort data by addressing the fragmented state of data storage and access systems. However, policy challenges in several domains remain unresolved. The euCanSHare workshop was organized to identify and discuss these challenges and to set the future research agenda. Concerns over the multiplicity and long-term sustainability of platforms, lack of resources, access of commercial parties to medical data, credit and recognition mechanisms in academia and the organization of data access committees are outlined. Within these areas, solutions need to be devised to ensure an optimal functioning of platforms.