Ethical Issues in Consent for the Reuse of Data in Health Data Platforms

Patient consent for the secondary use of health data in artificial intelligence (AI) models: A scoping review

BACKGROUND

The secondary use of health data for training Artificial Intelligence (AI) models holds immense potential for advancing medical research and healthcare delivery. However, ensuring patient consent for such utilization is paramount to uphold ethical standards and data privacy. Patient informed consent means patients are fully informed about how their data will be collected, used, and protected, and they voluntarily agree to allow their data to be used for AI models. In addition to formal consent frameworks, establishing a social license is critical to foster public trust and societal acceptance for the secondary use of health data in AI systems. This study examines patient consent practices in this domain.

METHOD

In this scoping review, we searched Web of Science, PubMed, and Scopus. We included studies in English that addressed the core issues of interest, namely, privacy, security, legal, and ethical issues related to the secondary use of health data in AI models. Articles not addressing the core issues, as well as systematic reviews, meta-analyses, books, letters, conference abstracts, and study protocols were excluded. Two authors independently screened titles, abstracts, and full texts, resolving disagreements with a third author. Data was extracted using a data extraction form.

RESULTS

After screening 774 articles, a total of 38 articles were ultimately included in the review. Across these studies, a total of 178 barriers and 193 facilitators were identified. We consolidated similar codes and extracted 65 barriers and 101 facilitators, which we then categorized into four themes: "Structure," "People," "Physical system," and "Task." We identified notable emphasis on "Legal and Ethical Challenges" and "Interoperability and Data Governance." Key barriers included concerns over privacy and security breaches, inadequacies in informed consent processes, and unauthorized data sharing. Critical facilitators included enhancing patient consent procedures, improving data privacy through anonymization, and promoting ethical standards for data usage.

CONCLUSION

Our study underscores the complexity of patient consent for the secondary use of health data in AI models, highlighting significant barriers and facilitators within legal, ethical, and technological domains. We recommend the development of specific guidelines and actionable strategies for policymakers, practitioners, and researchers to improve informed consent, ensuring privacy, trust, and ethical use of data, thereby facilitating the responsible advancement of AI in healthcare.

Exploring Consent to Use Real-World Data in Lung Cancer Radiotherapy: Decision of a Citizens' Jury for an 'Informed Opt-Out' Approach

An emerging approach to complement randomised controlled trial (RCT) data in the development of radiotherapy treatments is to use routinely collected 'real-world' data (RWD). RWD is the data collected as standard-of-care about all patients during their usual cancer care pathway. Given the nature of this data, important questions remain about the permissibility and acceptability of using RWD in routine practice. We involved and engaged with patients, carers and the public in a two-day citizens' jury to understand their views and obtain decisions regarding two key issues: (1) preferred approaches to consent for the use of RWD within the context of patients receiving radiotherapy for lung cancer in RAPID-RT and (2) how RWD use should be best communicated to patients. Individual views were polled using questionnaires at various stages of the jury, whilst group discussion activities prompted further dialogue about the rationale behind choices of consent. Key decisions obtained from the jury include: (1) an opt-out approach to consent for the use of RWD; (2) the opt-out approach to consent should be informed. Furthermore, it was advised that information and communication regarding the consent process and use of RWD should be accessible, clear and available in a variety of formats. It is important that the consent process for patient data use is underpinned by principles of autonomy and transparency with clear channels of communication between those asking for and giving consent. Moreover, the process of seeking consent from patients should be proportionate to the risks presented from their participation.

Ethical implications of artificial intelligence in sport: A systematic scoping review

BACKGROUND

Although there is growing evidence of the use of artificial intelligence (AI) techniques in sports, ethical issues surrounding AI use are being discussed at a minimal level. Thus, this systematic scoping review aimed to summarize the current ethical implications associated with using AI in sports.

METHODS

In this study, a total of 9 databases-MEDLINE/PubMed, Embase, Cochrane Library, ProQuest, EBSCOhost, IEEE Xplore, Web of Science, Scopus, and Google Scholar-were searched. The review protocol was registered (https://osf.io/42a8q) before extracting data. The search yielded 397 studies, and 25 studies met the inclusion and exclusion criteria.

RESULTS

The 25 studies were categorized into 4 primary ethical concerns: fairness and bias, transparency and explainability, privacy and data ethics, and accountability in AI's application in sports. These categorizations were derived based on the systematic review of ethical issues highlighted across the selected studies. Fifteen studies delved into fairness and bias, focusing on how AI can perpetuate existing inequalities in sports. Thirteen studies addressed the lack of transparency, emphasizing the challenges in interpretability and trust in AI-driven decisions. Privacy and data ethics emerged as significant in 22 studies, highlighting risks related to the misuse of athletes' sensitive data. Finally, accountability was examined in 8 studies, stressing the ethical obligations of AI developers and users in sports contexts. The thematic analysis revealed overlapping concerns, as some studies addressed multiple issues simultaneously.

CONCLUSION

Future research should focus on developing ethical frameworks tailored to underrepresented sports contexts and creating global standards for AI regulation in sports. This includes investigating the implications of AI applications in amateur sports, enhancing diversity in AI training datasets, and exploring the integration of ethical AI practices across various sports governance structures.

Data altruism and the "consent" question: a study into the "consent" models used under the GDPR and how the data altruism mechanism can act as a potential solution for the research community in the reuse of health data

Introduction

The General Data Protection Regulation ("GDPR") legal basis for obtaining consent for the processing of personal data for research purposes, where those purposes cannot be fully specified in advance, is provided for in Articles 6, 7 and Recital 33. However, GDPR's requirements for obtaining consent, as to the secondary use and sharing of data in research, have been argued to have generated confusion, whilst the conflicts between the Regulation itself, its practical application and research ethics are well-documented (1). The requirements for "informed consent", as defined within the GDPR, have not been well defined in the context of genome research or clinical trials (2), which has in turn led to the implementation and interpretation of the lawful basis to span into different idiosyncratic models. This naturally has fed into the uncertainty of how the legal basis can be applied in practice and calls for an investigation into the requirements for consent to be "informed" in the context of health research. This work aims to provide a scoping review and analysis of relevant publications with ultimate purpose to examine whether the concept of 'data altruism', as stipulated within Article 2 (10) of the Data Governance Act ("DGA"), addresses the gaps left behind by the application of the legal basis of 'consent', under the GDPR (Art. 6 (1) and 7), in so far as the secondary uses of data for research are concerned. In this light the article, by exploring available solutions found in relevant literature and used in practice in national and European projects, examines how 'data altruism' can add any value and work as a cohesive solution that the research community can use.

Objectives

The article, through its research, intends to answer the following questions:What gaps has the GDPR left when it comes to the interpretation and practical application of "consent" towards the secondary use of health data;Can the DGA, through the mechanism of 'data altruism', address these issues and provide a solution;What solutions have been used so far in practice to address this issue.

Methodology

To address the above-mentioned questions, the Arskey and O'Malley scoping review methodology and best practice, as outlined in the Joanna Briggs scoping review guidelines, have been applied. The research questions have been identified through an extensive literature review and consultation with subject matter experts. The search was conducted using six search engines and utilising a tailored search strategy, with the application of both MESH and non-MESH based search terms. From the identified relevant publications, 148 abstracts were kept to be read and 60 of those publications were kept as relevant. A PRISMA chart showcases the process in which the publications were reviewed and the process which led to the final papers kept as relevant. The title-abstract and full text screening and charting the data were concluded independently by two reviewers. Discrepancies were then resolved by a third reviewer. Results are summarised in both chart and narrative form below.

Results

The final 60 publications were then split into three subcategories: (i) GDPR critique (23 publications listed); (ii) iterations of consent and data altruism (21 publications listed); and (iii) proposed solutions and current practices (31 publications). Certain of the publications fell into more than one of the above subcategories, given the interdisciplinary element of the subject and theme of each paper. Throughout the research, 5 of the publications discuss the Data Governance Act and data altruism, with 4 of those providing a critique over the text used in the DGA and the concept of 'data altruism' in relation to 'consent' as defined within the GDPR and the overall legislative framework for the secondary uses of data.

Health data social licence: An inclusive process to learn more about the perspectives of experienced public and patient advisors

The term "social licence" has been used to describe which uses and users of health data the public supports - and under what conditions. From November 2022 to January 2023, Health Data Research Network Canada was funded by the Public Health Agency of Canada to explore whether there was consensus among experienced public and patient advisors on: (i) uses of health data that all members supported or opposed and (ii) what constitutes an essential requirement for a health data use or user to be within social licence. The project was conducted in English and French in collaboration with the Interdisciplinary Research Group in Health Informatics (GRIIS) at the University of Sherbrooke. It involved 20 public/patient advisor "participants" and an additional 13 public/patient advisors who served as peer-reviewers, all of whom had prior experience working in a health-related field and/or with health data. The process followed inclusive design principles in that it captured views held by the majority and minority of participants, including views expressed by only one or two participants. After two 2-hour facilitated sessions, participants agreed that it is within social licence for health data to be used (i) by healthcare practitioners to improve patient care, (ii) by governments and administrators to improve the health system, and (iii) by university-based researchers to understand disease and well-being. There was consensus opposition to (i) an individual or organisation selling someone else's identified health data and (ii) health data being used for a purpose that has no public or societal benefit. There was no consensus about what constitutes an essential requirement for a use or users of health data to be with social licence. The results of the process have been published in a non-peer-reviewed report co-authored with participants. This paper has been co-authored with a subset of the participants and peer-reviewers to present a high-level summary of the findings, methodological details, and templates to enable other groups to adapt the process to their own settings. It also presents the results of an anonymous evaluation of the process using the Public and Patient Engagement Evaluation Tool (PPEET), which were mostly positive and identified some areas for improvement.

The reuse of genetic information in research and informed consent

Important advances in genetics research have been made in recent years. Such advances have facilitated the availability of huge amounts of genetic information that could potentially be reused beyond the original purpose for which such information was obtained. Any such reuse must meet certain ethical criteria to ensure that the dignity, integrity, and autonomy of the individual from whom that information was obtained are protected. The aim of this paper is to reflect on these criteria through a critical analysis of the literature. To guarantee these values, ethical criteria need to be established in several respects. For instance, the question must be posed whether the information requires special attention and protection (so-called genetic exceptionalism). Another aspect to bear in mind is the most appropriate type of consent to be given by the person involved, on the one hand favouring research and the reuse of genetic information while on the other protecting the autonomy of that person. Finally, there is a need to determine what protection such reuse should have in order to avoid detrimental consequences and protect the rights of the individual. The main conclusions are that genetic information requires special care and protection (genetic exceptionalism) and that broad consent is the most practical and trustworthy type of consent for the reuse of genetic information.

Maintaining High-Touch in High-Tech Digital Health Monitoring and Multi-Omics Prognostication: Ethical, Equity, and Societal Considerations in Precision Health for Palliative Care

Advances in digital health, systems biology, environmental monitoring, and artificial intelligence (AI) continue to revolutionize health care, ushering a precision health future. More than disease treatment and prevention, precision health aims at maintaining good health throughout the lifespan. However, how can precision health impact care for people with a terminal or life-limiting condition? We examine here the ethical, equity, and societal/relational implications of two precision health modalities, (1) integrated systems biology/multi-omics analysis for disease prognostication and (2) digital health technologies for health status monitoring and communication. We focus on three main ethical and societal considerations: benefits and risks associated with integration of these modalities into the palliative care system; inclusion of underrepresented and marginalized groups in technology development and deployment; and the impact of high-tech modalities on palliative care's highly personalized and "high-touch" practice. We conclude with 10 recommendations for ensuring that precision health technologies, such as multi-omics prognostication and digital health monitoring, for palliative care are developed, tested, and implemented ethically, inclusively, and equitably.

Consent in organ transplantation: putting legal obligations and guidelines into practice

Consent in medical practice is a process riddled with layers of complexities. To some extent, this is inevitable given that different medical conditions raise different sets of issues for doctors and patients. Informed consent and risk assessment are highly significant public health issues that have become even more prominent during the course of the Covid-19 pandemic. In this article we identity relevant factors for clinicians to consider when ensuring consent for solid organ transplantation. Consent to undergo solid organ transplantation is more complex than most surgical and other clinical interventions because of the many factors involved, the complexity of the options and the need to balance competing risks. We first out the context in which consent is given by the patient. We then outline the legal principles pertaining to consent in medical practice as it applies in the UK and the implication of recent legal judgments. The third section highlights specific complexities of consent in organ transplantation and identifies relevant factors in determining consent for organ transplantation. The fourth section offers practical recommendations. We propose a novel 'multi-factor approach' to informed consent in transplantation which includes understanding risk, effective communication, and robust review processes. Whilst understanding risk and communication are a given, our suggestion is that including review processes into the consent process is essential. By this we specifically mean identifying and creating room for discretion in decision-making to better ensure that informed consent is given in practice. Discretion implies that health care professionals use their judgement to use the legal judgements as guidance rather than prescriptive. Discretion is further defined by identifying the relevant options and scope of clinical and personal factors in specified transplantation decisions. In particular, we also highlight the need to pay attention to the institutional dimension in the consent process. To that end, our recommendations identify a gap in the current approaches to consent. The identification of areas of discretion in decision-making processes is essential for determining when patients need to be involved. In other words, clinicians and healthcare professionals need to consider carefully when there is room for direction and where there is little or no room for exercising discretion. In sum, our proposed approach is a modest contribution to the on-going debate about consent in medicine.

The Challenges of Big Data for Research Ethics Committees: A Qualitative Swiss Study

Big data trends in health research challenge the oversight mechanism of the Research Ethics Committees (RECs). The traditional standards of research quality and the mandate of RECs illuminate deficits in facing the computational complexity, methodological novelty, and limited auditability of these approaches. To better understand the challenges facing RECs, we explored the perspectives and attitudes of the members of the seven Swiss Cantonal RECs via semi-structured qualitative interviews. Our interviews reveal limited experience among REC members with the review of big data research, insufficient expertise in data science, and uncertainty about how to mitigate big data research risks. Nonetheless, RECs could strengthen their oversight by training in data science and big data ethics, complementing their role with external experts and ad hoc boards, and introducing precise shared practices.

Of Screening, Stratification, and Scores

Technological innovations including risk-stratification algorithms and large databases of longitudinal population health data and genetic data are allowing us to develop a deeper understanding how individual behaviors, characteristics, and genetics are related to health risk. The clinical implementation of risk-stratified screening programmes that utilise risk scores to allocate patients into tiers of health risk is foreseeable in the future. Legal and ethical challenges associated with risk-stratified cancer care must, however, be addressed. Obtaining access to the rich health data that are required to perform risk-stratification, ensuring equitable access to risk-stratified care, ensuring that algorithms that perform risk-scoring are representative of human genetic diversity, and determining the appropriate follow-up to be provided to stratification participants to alert them to changes in their risk score are among the principal ethical and legal challenges. Accounting for the great burden that regulatory requirements could impose on access to risk-scoring technologies is another critical consideration.

Ethics and equity in rare disease research and healthcare

Rapid advances in next-generation sequencing technology, particularly whole exome sequencing and whole genome sequencing, have greatly affected our understanding of genetic variation underlying rare genetic diseases. Herein, we describe ethical principles of guiding consent and sharing of genomics research data. We also discuss ethical dilemmas in rare diseases research and patient recruitment policies and address bioethical and societal aspects influencing the ethical framework for genetic testing. Moreover, we focus on addressing ethical issues surrounding research in low- and middle-income countries. Overall, this perspective aims to address key aspects and issues for building proper ethical frameworks, when conducting research involving genomics data with a particular emphasis on rare diseases and genetics testing.