International scope of biomedical research ethics review.

Many countries consider long-term implications for society.

Psychiatric Illness and Clinical Negligence: When Can "Secondary Victims" Successfully Claim for Damages? Recent Developments from the United Kingdom.

On January 11, 2024, the United Kingdom (U.K.) Supreme Court rendered its judgment in Paul v Royal Wolverhampton NHS Trust, restricting the circumstances in which "secondary victims" can successfully claim for damages in clinical negligence cases. This ruling has provided welcome clarity regarding the scope of negligently caused "pure" psychiatric illness claims, but the judgment may well prove controversial. In this article, I trace the facts and opinion from the majority and also discuss an important dissenting opinion. I then reflect on what the ruling means for psychiatric illness claims by secondary victims, and more broadly on the implications for clinical negligence law. I suggest that while much-needed clarity has been injected in this area of the law, it is difficult, reading the majority of the Supreme Court's emphasis on the restricted scope of a medical practitioner's duty, to envision a scenario in which secondary victim could ever succeed in a clinical negligence context.

A qualitative interview study to determine barriers and facilitators of implementing automated decision support tools for genomic data access.

Data access committees (DAC) gatekeep access to secured genomic and related health datasets yet are challenged to keep pace with the rising volume and complexity of data generation. Automated decision support (ADS) systems have been shown to support consistency, compliance, and coordination of data access review decisions. However, we lack understanding of how DAC members perceive the value add of ADS, if any, on the quality and effectiveness of their reviews. In this qualitative study, we report findings from 13 semi-structured interviews with DAC members from around the world to identify relevant barriers and facilitators to implementing ADS for genomic data access management. Participants generally supported pilot studies that test ADS performance, for example in cataloging data types, verifying user credentials and tagging datasets for use terms. Concerns related to over-automation, lack of human oversight, low prioritization, and misalignment with institutional missions tempered enthusiasm for ADS among the DAC members we engaged. Tensions for change in institutional settings within which DACs operated was a powerful motivator for why DAC members considered the implementation of ADS into their access workflows, as well as perceptions of the relative advantage of ADS over the status quo. Future research is needed to build the evidence base around the comparative effectiveness and decisional outcomes of institutions that do/not use ADS into their workflows.

Purpose definition as a crucial step for determining the legal basis under the GDPR: implications for scientific research.

The General Data Protection Regulation (GDPR) of the European Union, which became applicable in 2018, contains a new accountability principle. Under this principle, controllers (ie parties determining the purposes and the means of the processing of personal data) are responsible for ensuring and demonstrating the overall compliance with the GDPR. However, interpretive uncertainties of the GDPR mean that controllers must exercise considerable judgement in designing and implementing an appropriate compliance strategy, making GDPR compliance both complex and resource-intensive. In this article, we provide conceptual clarity around GDPR compliance with respect to one core aspect of the law: the determination and relevance of the purpose of personal data processing. We derive from the GDPR's text concrete requirements for purpose specification, which we subsequently apply to the area of secondary use of personal data for scientific research. We offer guidance for correctly specifying purposes of data processing under different research scenarios. To illustrate the practical necessity of purpose specification for GDPR compliance, we then show how our proposed approach can enable controllers to meet their compliance obligations, using the example of the overarching GDPR principle of lawfulness to highlight the relevance of purpose specification for the identification of a suitable legal basis.

Achieving Procedural Parity in Managing Access to Genomic and Related Health Data: A Global Survey of Data Access Committee Members.

Data access committees (DACs) are critical players in the data sharing ecosystem. DACs review requests for access to data held in one or more repositories and where specific constraints determine how the data may be used and by whom. Our team surveyed DAC members affiliated with genomic data repositories worldwide to understand standard processes and procedures, operational metrics, bottlenecks, and efficiencies, as well as their perspectives on possible improvements to quality review. We found that DAC operations and systemic issues were common across repositories globally. In general, DAC members endeavored to achieve an appropriate balance of review efficiency, quality, and compliance. Our results suggest a similarly proportionate path forward that helps DACs pursue mutual improvements to efficiency and compliance without sacrificing review quality.

Confidentiality, public interest, and the human right to science: when can confidential information be used for the benefit of the wider community?

This article explores whether the human right to science can support the public interest as a legal basis to use and disclose confidential information. The contextual focus is scientific research; the jurisdictional focus is England. The human right to science, as reflected in the Universal Declaration of Human Rights (Article 27) and the International Covenant on Economic, Social and Cultural Rights (Article 15), hitherto has not been invoked in support of a public interest basis for lawful disclosure, but the argument is made herein that there may be scope to develop this jurisprudentially. On grounds of both law and policy, and in line with the underlying rationale of recent UK Government deployment of 'COPI Notices' for lawful use of confidential patient information in the course of the COVID-19 pandemic, I contend that the human right to science may well serve as a valuable juridical buttress to an overriding public interest justification to lawfully share confidential information. However, this could occur only in restricted circumstances where the public interest is clearly manifest, namely studies researching serious, imminent health threats to the general population that rely on confidential information accessed outside of existing statutory gateways, and not more routine scientific endeavors.

"Data makes the story come to life:" understanding the ethical and legal implications of Big Data research involving ethnic minority healthcare workers in the United Kingdom-a qualitative study.

The aim of UK-REACH ("The United Kingdom Research study into Ethnicity And COVID-19 outcomes in Healthcare workers") is to understand if, how, and why healthcare workers (HCWs) in the United Kingdom (UK) from ethnic minority groups are at increased risk of poor outcomes from COVID-19. In this article, we present findings from the ethical and legal stream of the study, which undertook qualitative research seeking to understand and address legal, ethical, and social acceptability issues around data protection, privacy, and information governance associated with the linkage of HCWs' registration data and healthcare data. We interviewed 22 key opinion leaders in healthcare and health research from across the UK in two-to-one semi-structured interviews. Transcripts were coded using qualitative thematic analysis. Participants told us that a significant aspect of Big Data research in public health is varying drivers of mistrust-of the research itself, research staff and funders, and broader concerns of mistrust within participant communities, particularly in the context of COVID-19 and those situated in more marginalised community settings. However, despite the challenges, participants also identified ways in which legally compliant and ethically informed approaches to research can be crafted to mitigate or overcome mistrust and establish greater confidence in Big Data public health research. Overall, our research indicates that a "Big Data Ethics by Design" approach to research in this area can help assure (1) that meaningful community and participant engagement is taking place and that extant challenges are addressed, and (2) that any new challenges or hitherto unknown unknowns can be rapidly and properly considered to ensure potential (but material) harms are identified and minimised where necessary. Our findings indicate such an approach, in turn, will help drive better scientific breakthroughs that translate into medical innovations and effective public health interventions, which benefit the publics studied, including those who are often marginalised in research.

Leveraging Algorithms to Improve Decision-Making Workflows for Genomic Data Access and Management.

Studies on the ethics of automating clinical or research decision making using artificial intelligence and other algorithmic tools abound. Less attention has been paid, however, to the scope for, and ethics of, automating decision making within regulatory apparatuses governing the access, use, and exchange of data involving humans for research. In this article, we map how the binary logic flows and real-time capabilities of automated decision support (ADS) systems may be leveraged to accelerate one rate-limiting step in scientific discovery: data access management. We contend that improved auditability, consistency, and efficiency of the data access request process using ADS systems have the potential to yield fairer outcomes in requests for data largely sourced from biospecimens and biobanked samples. This procedural justice rationale reinforces a broader set of participant and data subject rights that data access committees (DACs) indirectly protect. DACs protect the rights of citizens to benefit from science by bringing researchers closer to the data they need to advance that science. DACs also protect the informational dignities of individuals and communities by ensuring the data being accessed are used in ways consistent with participant values. We discuss the development of the Global Alliance for Genomics and Health Data Use Ontology standard as a test case of ADS for genomic data access management specifically, and we synthesize relevant ethical, legal, and social challenges to its implementation in practice. We conclude with an agenda of future research needed to thoughtfully advance strategies for computational governance that endeavor to instill public trust in, and maximize the scientific value of, health-related human data across data types, environments, and user communities.

The Ethical Implications of Big Data Research in Public Health: "Big Data Ethics by Design" in the UK-REACH Study.

In this article, we analyze legal and ethical issues raised in Big Data health research projects in the Covid-19 era and consider how these issues might be addressed in ways that advance positive values (e.g., furtherance of respect for persons and accordance with relevant legal frameworks) while mitigating or eliminating any negative aspects (e.g., exacerbation of social inequality and injustice). We apply this analysis specifically to UK-REACH (The United Kingdom Research Study into Ethnicity and Covid-19 Outcomes in Healthcare Workers), a project with which we are involved. We argue that Big Data projects like UK-REACH can be conducted in an ethically robust manner and that funders and sponsors ought to encourage similar projects to drive better evidence-based public policy in public health. As part of this, we advocate that a Big Data ethics-by-design approach be undertaken when such projects are constructed. This principle extends the work of those who advocate ethics by design by addressing prominent issues in Big Data health research projects; it holds that ethical values and principles in Big Data health research projects are best adhered to when they are already integrated into the project aims and methods at the design stage. In advocating this principle, we present a unique perspective regarding pressing ethical problems around large-scale, data-driven Covid-19 research, as well as legal issues associated with processing ostensibly anonymized health data.

The Genetic Discrimination Observatory: confronting novel issues in genetic discrimination.

Genetic discrimination (GD) is the differential or unfair profiling of an individual on the basis of genetic data. This article summarizes the actions of the Genetic Discrimination Observatory (GDO) in addressing GD and recent developments in GD since late 2020. It shows how GD can take many forms in today's rapidly evolving society.

Beyond categorisation: refining the relationship between subjects and objects in health research regulation.

In this article, we argue that the relationship between 'subject' and 'object' is poorly understood in health research regulation (HRR), and that it is a fallacy to suppose that they can operate in separate, fixed silos. By seeking to perpetuate this fallacy, HRR risks, among other things, objectifying persons by paying insufficient attention to human subjectivity, and the experiences and interests related to being involved in research. We deploy the anthropological concept of liminality - concerned with processes of transformation and change over time - to emphasise the enduring connectedness between subject and object in these contexts. By these means, we posit that regulatory frameworks based on processual regulation can better recognise and encompass the fluidity and significance of these relationships, and so ground more securely the moral legitimacy and social licence for human health research.

Signalling Standards for Progress: Bridging the Divide Between a Valid Consent to Use Patient Data Under Data Protection Law and the Common Law Duty of Confidentiality.

In this article, we analyse the legal components of disclosing confidential patient information under the UK's common law duty of confidentiality (CLDoC) and processing personal (health) data under the UK's General Data Protection Regulation (GDPR) and Data Protection Act 2018. We describe the ostensible divide between the CLDoC and data protection law when it comes to the requirements of a valid signal of consent by a patient to use and disclose patient information, obtained by a health professional in the context of direct care, for health care and health research purposes. Ultimately, our analysis suggests that we are saddled, at least in the medium term, with two regimes operating with different standards of a valid consent-while putatively protecting similar interests. There is, however, opportunity for progress. It is possible to improve professional guidance on the interaction between the regimes and to achieve significant normative alignment without aligning the signalling standard for consent; this would promote consistent protection of reasonable expectations of patients across both regimes. Further coherence would require aligning not only the standard, but also the role played by consent under each regime. Here we argue that, in relation to direct care, any such shift should be away from consent as the normal justification. In relation to health research, on the contrary, it should be toward consent as the normal justification for use and disclosure of patient information under both the CLDoC and data protection law.

Ethnicity and COVID-19 outcomes among healthcare workers in the UK: UK-REACH ethico-legal research, qualitative research on healthcare workers' experiences and stakeholder engagement protocol.

INTRODUCTION: As the world continues to grapple with the COVID-19 pandemic, emerging evidence suggests that individuals from ethnic minority backgrounds may be disproportionately affected. The United Kingdom Research study into Ethnicity And COVID-19 outcomes in Healthcare workers (UK-REACH) project has been initiated to generate rapid evidence on whether and why ethnicity affects COVID-19 diagnosis and clinical outcomes in healthcare workers (HCWs) in the UK, through five interlinked work packages/work streams, three of which form the basis of this protocol. The ethico-legal work (Work Package 3) aims to understand and address legal, ethical and acceptability issues around big data research; the HCWs' experiences study (Work Package 4) explores their work and personal experiences, perceptions of risk, support and coping mechanisms; the stakeholder engagement work (Work Package 5) aims to provide feedback and support with the formulation and dissemination of the project recommendations. METHODS AND ANALYSIS: Work Package 3 has two different research strands: (A) desk-based doctrinal research; and (B) empirical qualitative research with key opinion leaders. For the empirical research, in-depth interviews will be conducted digitally and recorded with participants' permission. Recordings will be transcribed, coded and analysed using thematic analysis. In Work Package 4, online in-depth interviews and focus groups will be conducted with approximately 150 HCWs, from across the UK, and these will be recorded with participants' consent. The recordings will be transcribed and coded and data will be analysed using thematic analysis. Work Package 5 will achieve its objectives through regular group meetings and in-group discussions. ETHICS AND DISSEMINATION: Ethical approval has been received from the London-Brighton & Sussex Research Ethics Committee of the Health Research Authority (Ref No 20/HRA/4718). Results of the study will be published in open-access journals, and disseminated through conference presentations, project website, stakeholder organisations, media and scientific advisory groups. TRIAL REGISTRATION NUMBER: ISRCTN11811602.

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.

Engaged genomic science produces better and fairer outcomes: an engagement framework for engaging and involving participants, patients and publics in genomics research and healthcare implementation.

Genomic science is increasingly central to the provision of health care. Producing and applying robust genomics knowledge is a complex endeavour in which no single individual, profession, discipline or community holds all the answers.  Engagement and involvement of diverse stakeholders can support alignment of societal and scientific interests, understandings and perspectives and promises better science and fairer outcomes. In this context we argue for F.A.I.R.E.R. data and data use that is Findable, Accessible, Interoperable, Reproducible, Equitable and Responsible. Yet there is a paucity of international guidance on how to engage publics, patients and participants in genomics. To support meaningful and effective engagement and involvement we developed an Engagement Framework for involving and engaging participants, patients and publics in genomics research and health implementation. The Engagement Framework is intended to support all those working in genomics research, medicine, and healthcare to deliberatively consider approaches to participant, patient and public engagement and involvement in their work. Through a series of questions, the Engagement Framework prompts new ways of thinking about the aims and purposes of engagement, and support reflection on the strengths, limitations, likely outcomes and impacts of choosing different approaches to engagement. To guide genomics activities, we describe four themes and associated questions for deliberative reflection: (i) fairness; (ii) context; (iii) heterogeneity, and (iv) recognising tensions and conflict. The four key components in the Engagement provide a framework to assist those involved in genomics to reflect on decisions they make for their initiatives, including the strategies selected, the participant, patient and public stakeholders engaged, and the anticipated goals. The Engagement Framework is one step in an actively evolving process of building genomics research and implementation cultures which foster responsible leadership and are attentive to objectives which increase equality, diversity and inclusion in participation and outcomes.

GA4GH: International policies and standards for data sharing across genomic research and healthcare.

The Global Alliance for Genomics and Health (GA4GH) aims to accelerate biomedical advances by enabling the responsible sharing of clinical and genomic data through both harmonized data aggregation and federated approaches. The decreasing cost of genomic sequencing (along with other genome-wide molecular assays) and increasing evidence of its clinical utility will soon drive the generation of sequence data from tens of millions of humans, with increasing levels of diversity. In this perspective, we present the GA4GH strategies for addressing the major challenges of this data revolution. We describe the GA4GH organization, which is fueled by the development efforts of eight Work Streams and informed by the needs of 24 Driver Projects and other key stakeholders. We present the GA4GH suite of secure, interoperable technical standards and policy frameworks and review the current status of standards, their relevance to key domains of research and clinical care, and future plans of GA4GH. Broad international participation in building, adopting, and deploying GA4GH standards and frameworks will catalyze an unprecedented effort in data sharing that will be critical to advancing genomic medicine and ensuring that all populations can access its benefits.

International federation of genomic medicine databases using GA4GH standards.

We promote a shared vision and guide for how and when to federate genomic and health-related data sharing, enabling connections and insights across independent, secure databases. The GA4GH encourages a federated approach wherein data providers have the mandate and resources to share, but where data cannot move for legal or technical reasons. We recommend a federated approach to connect national genomics initiatives into a global network and precision medicine resource.