Researchers and practitioners are increasingly using machine‐generated synthetic data as a tool for advancing health science and practice, by expanding access to health data while—potentially—mitigating privacy and related ethical concerns around data sharing. While using synthetic data in this way holds promise, we argue that it also raises significant ethical, legal, and policy concerns, including persistent privacy and security problems, accuracy and reliability issues, worries about fairness and bias, and new regulatory challenges. The virtue (...) of synthetic data is often understood to be its detachment from the data subjects whose measurement data is used to generate it. However, we argue that addressing the ethical issues synthetic data raises might require bringing data subjects back into the picture, finding ways that researchers and data subjects can be more meaningfully engaged in the construction and evaluation of datasets and in the creation of institutional safeguards that promote responsible use. (shrink)

BackgroundConsent for data research in acute and critical care is complex as patients become at least temporarily incapacitated or die. Existing guidelines and regulations in the European Union are of limited help and there is a lack of literature about the use of data from this vulnerable group. To aid the creation of a patient-centred framework for responsible data research in the acute setting, we explored views of patients and next-of-kin about the collection, storage, sharing and use (...) of genetic and health-related data for observational research.MethodsWe conducted qualitative interviews (n = 19) with Dutch sudden cardiac arrest survivors who donated clinical and socio-economic data and genetic samples to research. We also interviewed their next-of-kin. Topics were informed by ethics literature and we used scenario-sketches to aid discussion of complex issues.ResultsSudden cardiac arrest survivors displayed limited awareness of their involvement in health data research and of the content of their given consent. We found that preferences regarding disclosure of clinically actionable genetic findings could change over time. When data collection and use were limited to the medical realm, patients trusted researchers to handle data responsibly without concern for privacy or other risks. There was no consensus as to whether deferred consent should be explicitly asked from survivors. If consent is asked, this would ideally be done a few months after the event when cognitive capacities have been regained. Views were divided about the need to obtain proxy consent for research with deceased patients’ data. However, there was general support for the disclosure of potentially relevant post-mortem genetic findings to relatives.ConclusionsSudden cardiac arrest patients’ donation of data for research was grounded in trust in medicine overall, blurring the boundary between research and care. Our findings also highlight questions about the acceptability of a one-time consent and about responsibilities of patients, researchers and ethics committees. Finally, further normative investigation is needed regarding the (continued) use of participants’ data after death, which is of particular importance in this setting. Our findings are thought to be of relevance for other acute and life-threatening illnesses as well. (shrink)

Secondary electronic health data can provide many benefits and value when used for the following purposes: reasons of public interest in the fields of public health, personalised and occupational medicine; activities to guarantee high levels of quality and safety of healthcare services; advancements in education and scientific research; innovation and development of technological products contributing to population health and social welfare. A literature review was performed to explore health data sharing attitudes or intentions together (...) with associated motivators/barriers, and significant modulators of participants’ sharing behaviour, to provide a qualitative summary in the field of secondary use of health data. Despite the fact that during the last two decades, sharing health data for secondary purposes has gained great attention due to its numerous applications and associated benefits, people’s attitude towards sharing health data are not always positive. These attitudes are in fact influenced by several factors such as: types of health information, privacy concerns, information on security level, results of health information use, altruism, illness histories. Further analyses and studies are needed to better understand healthcare advances through disruptive technologies. (shrink)

Meta-Health is a paradigm shift in healthcare, which embraces big data, digital technologies, and the idea of interconnection to bring improvements to patient care and its corresponding outcomes. However, integration and analysis of vast amounts of sensitive health information create significant demands and challenges in assuring data privacy and security. Specifically, this chapter will elaborate on challenges of data privacy and security in Meta-Health, focusing on major concerns and threats and regulatory requirements that shape (...) the landscape; the current study of the leading issues includes data privacy principles and standards, security frameworks, risk management strategies, and emerging technologies such as AI, blockchain, and IoT that are driving Meta-Health data security. This chapter also talks about ethical considerations and the dynamic regulatory environment to provide a view on best practices toward patient data protection while allowing access to such data. By considering the right attention paid to these critical areas, the chapter offers professionals in the healthcare field, data scientists, and policymakers the foundation of a broad-based understanding of the strategies for Meta-Health that will further patiently trust and enable the use of health data in a secure manner in this digital era. (shrink)

Intensified and extensive data production and data storage are characteristics of contemporary western societies. Health data sharing is increasing with the growth of Information and Communication Technology platforms devoted to the collection of personal health and genomic data. However, the sensitive and personal nature of health data poses ethical challenges when data is disclosed and shared even if for scientific research purposes. With this in mind, the Science and Values Working Group (...) of the COST Action CHIP ME ‘Citizen's Health through public-private Initiatives: Public health, Market and Ethical perspectives’ identified six core values they considered to be essential for the ethical sharing of health data using ICT platforms. We believe that using this ethical framework will promote respectful scientific practices in order to maintain individuals’ trust in research. We use these values to analyse five ICT platforms and explore how emerging data sharing platforms are reconfiguring the data sharing experience from a range of perspectives. We discuss which types of values, rights and responsibilities they entail and enshrine within their philosophy or outlook on what it means to share personal health information. Through this discussion we address issues of the design and the development process of personal health data and patient-oriented infrastructures, as well as new forms of technologically-mediated empowerment. (shrink)

In this chapter, we introduce the concept of Health Data Science and define its three domains: technology, analytics, and conceptual. In the technology domain, we drill down from computer science via health informatics to public health informatics. The analytics domain includes biostatistics, bioinformatics, epidemiology, and simulation. In the conceptual domain, we introduce the philosophy of information, and of health and causation. Taken together, these domains provide the theoretical backdrop for the remainder of the book.

BackgroundIncreasingly, hospitals and research institutes are developing technical solutions for sharing patient data in a privacy preserving manner. Two of these technical solutions are homomorphic encryption and distributed ledger technology. Homomorphic encryption allows computations to be performed on data without this data ever being decrypted. Therefore, homomorphic encryption represents a potential solution for conducting feasibility studies on cohorts of sensitive patient data stored in distributed locations. Distributed ledger technology provides a permanent record on all transfers and (...) processing of patient data, allowing data custodians to audit access. A significant portion of the current literature has examined how these technologies might comply with data protection and research ethics frameworks. In the Swiss context, these instruments include the Federal Act on Data Protection and the Human Research Act. There are also institutional frameworks that govern the processing of health related and genetic data at different universities and hospitals. Given Switzerland’s geographical proximity to European Union (EU) member states, the General Data Protection Regulation (GDPR) may impose additional obligations.MethodsTo conduct this assessment, we carried out a series of qualitative interviews with key stakeholders at Swiss hospitals and research institutions. These included legal and clinical data management staff, as well as clinical and research ethics experts. These interviews were carried out with two series of vignettes that focused on data discovery using homomorphic encryption and data erasure from a distributed ledger platform.ResultsFor our first set of vignettes, interviewees were prepared to allow data discovery requests if patients had provided general consent or ethics committee approval, depending on the types of data made available. Our interviewees highlighted the importance of protecting against the risk of reidentification given different types of data. For our second set, there was disagreement amongst interviewees on whether they would delete patient data locally, or delete data linked to a ledger with cryptographic hashes. Our interviewees were also willing to delete data locally or on the ledger, subject to local legislation.ConclusionOur findings can help guide the deployment of these technologies, as well as determine ethics and legal requirements for such technologies. (shrink)

The future of health research will be characterised by three continuing trends: rising demand for health data; increasing impracticability of obtaining specific consent for secondary research; and decreasing capacity to effectively anonymise data. In this context, governments, clinicians and the research community must demonstrate that they can be responsible stewards of health data. IRBs and RECs sit at heart of this process because in many jurisdictions they have the capacity to grant consent waivers when (...) research is judged to be of particular value. However, several different terms are used to refer to this value, indicating a lack of conceptual clarity regarding the appropriate test for access to health data for research without consent. In this paper we do three things. First we describe the current confusion and instability in terminology relating to public interest in the context of consent waivers. Second we argue for harmonisation of terminology on the grounds of clarity, transparency and consistency. Third we argue that the term ‘public interest’ best reflects the normative work required to justify consent waivers because it is the broadest of the competing terms. ‘Public interest’ contains within its scope positive and negative implications of a study, as well as welfare, justice and rights considerations. In making this argument, we explain the normative basis for consent waivers, and provide a starting place for further discussion about the precise conditions in which a given study can be said to advance the public interest. Ipsos MORI study found that: … the public would be broadly happy with administrative data linking for research projects provided Those projects have social value, broadly defined. Data are de-identified. Data are kept secure. Businesses are not able to access the data for profit. (shrink)

Disaggregation of public health data by race and ethnicity is critical to understanding health disparities and driving progress toward health equity. While the federal government updated the minimum set of categories federal agencies must use when collecting race and ethnicity data, implementation of these standards remains uncertain. Additionally, federal standards set a floor; states can adopt laws requiring additional data collection specific to their population. As of May 2025, 13 states have passed laws to (...) require disaggregation of race and ethnicity. One state – New York – is implementing the Asian and Native Hawaiian/Pacific Islander (NHPI) Data Disaggregation Law. Challenges include finding effective pressure points for the state agencies that are required to update data and helping agencies access funding for necessary changes. In California, the 2024 Latine and Indigenous Health Disparities Act builds on previous data disaggregation legislation for the Asian and NHPI community in California. Challenges with the bill’s adoption included pressure to narrow the agencies affected by the law and creating an appropriate implementation timeline. Key considerations in the adoption of a state data disaggregation law or policy include educating policymakers about the importance of data disaggregation, determining the scope of the policy, and preparing for implementation. (shrink)

Background The ownership status of individual-level health data affects the manner in which it is used. In this paper we analyze two competing models of the ownership status of the data discussed in the literature recently: private ownership and public ownership. Main body In this paper we describe the limitations of these two models of data ownership with respect to individual-level health data, in particular in terms of ethical principles of justice and autonomy, risk (...) mitigation, as well as technological, economic, and conceptual issues. We argue that undifferentiated application of neither private ownership nor public ownership will allow us to resolve all the problems associated with effective, equitable, and ethical use of data. We suggest that, instead of focusing on data ownership, we should focus on the institutional and procedural aspects of data governance, such as using Data Access Committees (DACs) or equivalent managed access processes, which can balance the elements of these two ownership frameworks. Conclusion Undifferentiated application of the ownership concept (private or public) is not helpful in resolving problems associated with sharing individual-level health data. DACs or equivalent managed access processes should be an integral part of data governance. They can approve or disapprove data access requests after considering the potential benefits and harms to data subjects, their communities, primary researchers, and the wider society. (shrink)

Effectively addressing ethical issues in precision medicine research in Africa requires a holistic social contract that integrates biomedical knowledge with local cultural values and Indigenous knowledge systems. Drawing on African epistemologies such as ubuntu and ujamaa and on our collective experiences in genomics and big data research for sickle cell disease, hearing impairment, and fragile X syndrome and the project Public Understanding of Big Data in Genomics Medicine in Africa, we envision a transformative shift in health research (...) data governance in Africa that could help create a sense of shared responsibility between all stakeholders in genomics and data‐driven health research in Africa. This shift includes proposing a social contract for genomics and data science in health research that is grounded in African communitarianism such as solidarity, shared decision‐making, and reciprocity. We make several recommendations for a social contract for genomics and data science in health, including the coproduction of genomics knowledge with study communities, power sharing between stakeholders, public education on the ethical and social implications of genetics and data science, benefit sharing, giving voice to data subjects through dynamic consent, and democratizing data access to allow wide access by all research stakeholders. Achieving this would require adopting participatory approaches to genomics and data governance. (shrink)

Health research increasingly relies on organized collections of health data and biological samples. There are many types of sample and data collections that are used for health research, though these are collected for many purposes, not all of which are health-related. These collections exist under different jurisdictional and regulatory arrangements and include: 1) Population biobanks, cohort studies, and genome databases 2) Clinical and public health data 3) Direct-to-consumer genetic testing 4) Social media (...) 5) Fitness trackers, health apps, and biometric data sensors Population biobanks, cohort studies, and genome databases Clinical and public health data Direct-to-consumer genetic testing Social media Fitness trackers, health apps, and biometric data sensors Ethical, legal, and social challenges of such collections are well recognized, but there has been limited attention to the broader societal implications of the existence of these collections. Although health research conducted using these collections is broadly recognized as beneficent, secondary uses of these data and samples may be controversial. We examine both documented and hypothetical scenarios of secondary uses of health data and samples. In particular, we focus on the use of health data for purposes of: Forensic investigations Civil lawsuits Identification of victims of mass casualty events Denial of entry for border security and immigration Making health resource rationing decisions Facilitating human rights abuses in autocratic regimes Forensic investigations Civil lawsuits Identification of victims of mass casualty events Denial of entry for border security and immigration Making health resource rationing decisions Facilitating human rights abuses in autocratic regimes Current safeguards relating to the use of health data and samples include research ethics oversight and privacy laws. These safeguards have a strong focus on informed consent and anonymization, which are aimed at the protection of the individual research subject. They are not intended to address broader societal implications of health data and sample collections. As such, existing arrangements are insufficient to protect against subversion of health databases for non-sanctioned secondary uses, or to provide guidance for reasonable but controversial secondary uses. We are concerned that existing debate in the scholarly literature and beyond has not sufficiently recognized the secondary data uses we outline in this paper. Our main purpose, therefore, is to raise awareness of the potential for unforeseen and unintended consequences, in particular negative consequences, of the increased availability and development of health data collections for research, by providing a comprehensive review of documented and hypothetical non-health research uses of such data. (shrink)

The predominant view is that a study using health data is observational research and should require individual consent unless it can be shown that gaining consent is impractical. But recent arguments have been made that citizens have an ethical obligation to share their health information for research purposes. In our view, this obligation is sufficient ground to expand the circumstances where secondary use research with identifiable health information is permitted without explicit subject consent. As such, for (...) some studies the Institutional Review Board/Research Ethics Committee review process should not assess the practicality of gaining consent for data use. Instead the review process should focus on assessing the public good of the research, public engagement and transparency. (shrink)

For the first time, the revised Common Rule specifies that public health surveillance activities are not research. This article reviews the historical development of the public health surveillance exclusion and implications for other foundational public health practices.

In this article we provide an in-depth description of a new model of informed consent called ‘meta consent’ and consider its practical implementation. We explore justifications for preferring meta consent over alternative models of consent as a solution to the problem of secondary use of health data for research. We finally argue that meta consent strikes an appropriate balance between enabling valuable research and protecting the individual.

One of the core goals of Digital Health Technologies (DHT) is to transform healthcare services and delivery by shifting primary care from hospitals into the community. However, achieving this goal will rely on the collection, use and storage of large datasets. Some of these datasets will be linked to multiple sources, and may include highly sensitive health information that needs to be transferred across institutional and jurisdictional boundaries. The growth of DHT has outpaced the establishment of clear legal (...) pathways to facilitate the collection, use and transfer of potentially sensitive health data. Our study aimed to address this gap with an ethical code to guide researchers developing DHT with international collaborative partners in Singapore. We generated this code using a modified Policy Delphi process designed to engage stakeholders in the deliberation of health data ethics and governance. This paper reports the outcomes of this process along with the key components of the code and identifies areas for future research. (shrink)

Data access and data sharing are vital to advance medicine. A growing number of public private partnerships are set up to facilitate data access and sharing, as private and public actors possess highly complementary health data sets and treatment development resources. However, the priorities and incentives of public and private organizations are frequently in conflict. This has complicated partnerships and sparked public concerns around ethical issues such as trust, justice or privacy—in turn raising an important (...) problem in business and data ethics: how can ethical theory inform the practice of public and private partners to mitigate misaligned incentives, and ensure that they can deliver societally beneficial innovation? In this paper, we report on the development of the Swiss Personalized Health Network’s ethical guidelines for health data sharing in public private partnerships. We describe the process of identifying ethical issues and engaging core stakeholders to incorporate their practical reality on these issues. Our report highlights core ethical issues in health data public private partnerships and provides strategies for how to overcome these in the Swiss health data context. By agreeing on and formalizing ethical principles and practices at the beginning of a partnership, partners and society can benefit from a relationship built around a mutual commitment to ethical principles. We present this summary in the hope that it will contribute to the global data sharing dialogue. (shrink)

Background Improving the ways in which routinely-collected mental health data are shared could facilitate substantial advances in research and treatment. However, this process should only be undertaken in partnership with those who provide such data. Despite relatively widespread investigation of public perspectives on health data sharing more generally, there is a lack of research on the views of people with mental illness. Methods Twelve people with lived experience of mental illness took part in semi-structured interviews (...) via online video software. Participants had experience of a broad range of mental health conditions including anxiety, depression, schizophrenia, eating disorders and addiction. Interview questions sought to establish how participants felt about the use of routinely-collected health data for research purposes, covering different types of health data, what health data should be used for, and any concerns around its use. Results Thematic analysis identified four overarching themes: benefits of sharing mental health data, concerns about sharing mental health data, safeguards, and data types. Participants were clear that health data sharing should facilitate improved scientific knowledge and better treatments for mental illness. There were concerns that data misuse could become another way in which individuals and society discriminate against people with mental illness, for example through insurance premiums or employment decisions. Despite this there was a generally positive attitude to sharing mental health data as long as appropriate safeguards were in place. Conclusions There was notable strength of feeling across participants that more should be done to reduce the suffering caused by mental illness, and that this could be partly facilitated by well-managed sharing of health data. The mental health research community could build on this generally positive attitude to mental health data sharing by following rigorous best practice tailored to the specific concerns of people with mental illness. (shrink)

This paper conducts a comparative analysis of data governance mechanisms concerning the secondary use of health data in Taiwan and the European Union (EU). Both regions have adopted distinctive approaches and regulations for utilizing health data beyond primary care, encompassing areas such as medical research and healthcare system enhancement. Through an examination of these models, this study seeks to elucidate the strategies, frameworks, and legal structures employed by Taiwan and the EU to strike a delicate (...) balance between the imperative of data-driven healthcare innovation and the safeguarding of individual privacy rights. This paper examines and compares several key aspects of the secondary use of health data in Taiwan and the EU. These aspects include data governance frameworks, legal and regulatory frameworks, data access and sharing mechanisms, and privacy and security considerations. This comparative exploration offers invaluable insights into the evolving global landscape of health data governance. It provides a deeper understanding of the strategies implemented by these regions to harness the potential of health data while upholding the ethical and legal considerations surrounding its secondary use. The findings aim to inform best practices for responsible and effective health data utilization, particularly in the context of medical AI applications. (shrink)

Health data hold immense potential for advancing medical science and informing public health strategies; however, their secondary use for research purposes has been poorly exploited, partly due to uncertainty and compliance concerns brought about by the Protection of Personal Information Act (POPIA). Researchers often assume that re-consent is the only option for secondary use. Yet POPIA provides several lawful grounds for processing special personal information, which includes health data, without necessarily obtaining re-consent. The present article (...) serves as a practical guide for researchers navigating POPIA’s requirements for the secondary use of health data for research. A systematic approach is recommended: first, researchers should establish whether the original consent encompasses the intended secondary use. If it does not, they should determine which lawful grounds for processing special personal information best suit their context and can be relied upon. Options include obtaining re-consent, relying on a research purpose, or seeking authorisation from the Information Regulator. In addition, researchers may consider de-identifying the dataset, which would exempt it from the ambit of POPIA. Situations where pseudonymisation might achieve a similar outcome are also unpacked. By taking proactive, well-documented steps, researchers can better capitalise on existing health datasets to advance vital health research in South Africa. (shrink)

Wearable self-tracking devices capture multidimensional health data and offer several advantages including new ways of facilitating research. However, they also create a conflict between individual interests of avoiding privacy harms, and collective interests of assembling and using large health data sets for public benefits. While some scholars argue for transparency and accountability mechanisms to resolve this conflict, an average user is not adequately equipped to access and process information relating to the consequences of consenting to further (...) uses of her data. As an alternative, this paper argues for fiduciary relationships, which put deliberative demands on digital health data controllers to keep the interests of their data subjects at the forefront as well as cater to the contextual nature of privacy. These deliberative requirements ensure that users can engage in collective participation and share their health data at a lower risk of privacy harms. This paper also proposes a way to balance the flexible and open-ended nature of fiduciary law with the specific nature and scope of fiduciary duties that digital health data controllers should owe to their data subjects. (shrink)

The increased use of information technology in every day health care creates vast amounts of stored health data that can be used for research. The secondary research use of routinely collected data raises questions about appropriate consent mechanisms for such use. One option is meta consent where individuals state their own consent preferences in relation to future use of their data, e.g. whether they want the data to be accessible to researchers under conditions of (...) specific consent, broad consent, blanket consent or not at all. This study investigates whether meta consent preferences can be successfully elicited by a smartphone application in the adult Danish population. A smartphone app was developed for the elicitation of meta consent preferences. An invitation to use the app was distributed to a stratified, representative sample of the Danish adult population. The meta consent choices, the use of the app, user experience data, and demographic data were logged and analysed statistically using IBM SPSS version 20. Of 1000 potential respondents 221 used the app. One hundred eighty-eight of the respondents were female and 103 male. The age range was 19 to 79 years with an average of 51 years. Most users indicate 1) that they find the choices they are asked to make easy to understand, 2) that the application is easy to use, and 3) that this kind of choice should be offered to people. It is possible to collect meta consent preferences in the general, adult population using a smartphone app. (shrink)

In this article, we use the theory of Information Ethics to argue that deceased people have a prima facie moral right to privacy in the context of health data research, and that this should be reflected in regulation and guidelines. After death, people are no longer biological subjects but continue to exist as informational entities which can still be harmed/damaged. We find that while the instrumental value of recognising post-mortem privacy lies in the preservation of the social contract (...) for health research, its intrinsic value is grounded in respect for the dignity of the post-mortem informational entity. However, existing guidance on post-mortem data protection is available only in the context of genetic studies. In comparing the characteristics of genetic data and other health-related data, we identify two features of DNA often given as arguments for this genetic exceptionalism: relationality and embodiment. We use these concepts to show that at the appropriate Level of Abstraction, there is no morally relevant distinction between posthumous genetic and other health data. Thus, genetic data should not automatically receive special moral status after death. Instead we make a plea for ‘contextual exceptionalism’. Our analysis concludes by reflecting on a real-world case and providing suggestions for contextual factors that researchers and oversight bodies should take into account when designing and evaluating research projects with health data from deceased subjects. (shrink)

Before the EU General Data Protection Regulation entered into force in May 2018, we witnessed an intense struggle of actors associated with data-dependent fields of science, in particular health-related academia and biobanks striving for legal derogations for data reuse in research. These actors engaged in a similar line of argument and formed issue alliances to pool their collective power. Using descriptive coding followed by an interpretive analysis, this article investigates the argumentative repertoire of these actors and (...) embeds the analysis in ethical debates on data sharing and biobank-related data governance. We observe efforts to perform a paradigmatic shift of the discourse around the General Data Protection Regulation-implementation away from ‘protecting data’ as key concern to ‘protecting health’ of individuals and societies at large. Instead of data protection, the key risks stressed by health researchers became potential obstacles to research. In line, exchange of information with data subjects is not a key concern in the arguments of biobank-related actors and it is assumed that patients want ‘their’ data to be used. We interpret these narratives as a ‘reaction’ to potential restrictions for data reuse and in line with a broader trend towards Big Data science, as the very idea of biobanking is conceptualized around long-term use of readily prepared data. We conclude that a sustainable implementation of biobanks needs not only to comply with the General Data Protection Regulation, but must proactively re-imagine its relation to citizens and data subjects in order to account for the various ways that science gets entangled with society. (shrink)

BackgroundThe past 10 years have witnessed a significant growth in sharing of health data for secondary uses. Alongside this there has been growing interest in the public acceptability of data sharing and data linkage practices. Public acceptance is recognised as crucial for ensuring the legitimacy of current practices and systems of governance. Given the growing international interest in this area this systematic review and thematic synthesis represents a timely review of current evidence. It highlights the key (...) factors influencing public responses as well as important areas for further research.MethodsThis paper reports a systematic review and thematic synthesis of qualitative studies examining public attitudes towards the sharing or linkage of health data for research purposes. Twenty-five studies were included in the review. The included studies were conducted primarily in the UK and North America, with one study set in Japan, another in Sweden and one in multiple countries. The included studies were conducted between 1999 and 2013. The qualitative methods represented in the studies included focus groups, interviews, deliberative events, dialogue workshops and asynchronous online interviews.ResultsKey themes identified across the corpus of studies related to the conditions necessary for public support/acceptability, areas of public concern and implications for future research. The results identify a growing body of evidence pointing towards widespread general—though conditional—support for data linkage and data sharing for research purposes. Whilst a variety of concerns were raised in cases where participants perceived there to be actual or potential public benefits from research and had trust in the individuals or organisations conducting and/or overseeing data linkage/sharing, they were generally supportive. The studies also find current low levels of awareness about existing practices and uses of data.ConclusionsWhilst the results indicate widespread public support for data sharing and linkage for research purposes, a range of concerns exist. In order to ensure public support for future research uses of data greater awareness raising combined with opportunities for public engagement and deliberation are needed. This will be essential for ensuring the legitimacy of future health informatics research and avoiding further public controversy. (shrink)

Here, we analyze the public health implications of recent legal developments — including privacy legislation, intergovernmental data exchange, and artificial intelligence governance — with a view toward the future of public health informatics and the potential of diverse data to inform public health actions and drive population health outcomes.

Ongoing efforts among federal agencies to expunge public health data from websites and other media in line with Trump administration directives on “gender ideology” and other themes has led to widespread confusion, angst, and concern among health officials, medical practitioners, and patients. It has also generated legal claims seeking to reverse and stop public health data purges. Framed within statutory or constitutional limits, legal strategies countering these data policies help assure access to core public (...) health information essential to specific services, care, and outcomes. (shrink)

Hundreds of articles have been written over the past several decades delineating the ethical tensions of health data commercialization, empirically querying the preferences of data contributors, an...

Medical devicesMedical devices based on machine learning (ML)Machine learning (ML) promise to have a significant impact and make advances in healthcare. This chapter analyzes to what extent data protectionData protection law, de lege lata and de lege ferenda, enables the development of ML-based medical devices. A key aspect of this is the processing of health dataHealth data, which does not originate with the developers but with the healthcare providers. ML-based medical devicesMedical devices are trained with a large (...) amount of health data. According to the current legal situation under the General Data Protection Regulation (GDPR)General Data Protection Regulation (GDPR), secondary use of health dataHealth data is possible in principle (Article 6 (4) GDPR). However, the consentConsent of the data subjects faces certain difficulties, and as the following analysis shows, the development of an ML-based medical device does not necessarily constitute scientific researchScientific research within the meaning of the GDPR. Therefore, this chapter argues that a separate legal basis is needed. This must be accompanied by technical-organizational measures that safeguard the rights of the data subject to a large extent and should only be allowed if the general public benefits from the research on and/or deployment of the ML-based medical deviceMedical devices. In addition, there is a need for infrastructural measures such as the establishment or expansion of intermediary bodies, given the lack of incentives, personnel capacity, and expertise among healthcare providers to share health data with a broad range of interested parties. Furthermore, to ensure a reliable output from ML-based medical devices, standards for data preparation must be established. Finally, this chapter discusses the proposal of the European Health DataHealth dataSpace (EHDS)European Health Data Space (EHDS) and briefly examines whether this is a step in the right direction. (shrink)

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. Methods 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. Results 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. Conclusions 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. (shrink)

Health research ethics training is highly variable, with some researchers receiving little to none, which is why ethical frameworks represent critical tools for ethical deliberation and guiding responsible practice. However, these documents' voluntary and abstract nature can leave health researchers seeking more operationalised guidance, such as in the form of checklists, even though this approach does not support reflection on the meaning of principles nor their implications. In search of more reflective and participatory practices in a pandemic context (...) with distance learning, this study explored whether co-design could support engagement and reflection on ethical principles amongst early-stage health researchers. In a pilot test using the Swiss Personalized Health Network's ethical framework for Responsible Usage of Personal Data in Health Research as a case study, we engaged health researchers to design visuals of four ethical principles. In two online workshops, participants (N = 10, N = 8) completed activities such as individual reflection, collaborative ideation, sketching, prototyping, discussion, and feedback. Our analysis shows that the co-design process helped foster in-depth engagement and reflection on the meaning and relevance of the SPHN ethical principles. Participants reported enjoying the experience, and most felt that visuals could motivate engagement with ethical frameworks. This study demonstrates the feasibility of a participatory, design-oriented approach to promote engagement with research ethics among early-career health researchers and highlights key challenges and lessons learned. In doing so, it lays the foundation for future research to investigate the impact of design-oriented, participatory learning to foster reflection and deliberation in ethics education. (shrink)

BackgroundThe advent of learning healthcare systems (LHSs) raises an important implementation challenge concerning how to request and manage consent to support secondary use of data in learning cycles, particularly research activities. Current consent models in Quebec were not established with the context of LHSs in mind and do not support the agility and transparency required to obtain consent from all involved, especially the citizens. Therefore, a new approach to consent is needed. Previous work identified the meta-consent model as a (...) promising alternative to fulfill the requirements of LHSs, particularly large-scale deployments. We elicited the public’s attitude toward the meta-consent model to evaluate if the model could be understood by the citizens and would be deemed acceptable to prepare for its possible implementation in Quebec.MethodsEight focus groups, with a total of 63 members of the general public from various backgrounds were conducted in Quebec, Canada, in 2019. Explicit attention was given to literacy levels, language spoken at home and rural vs urban settings. We assessed attitudes, concerns and facilitators regarding key components of the meta-consent model: predefined categories to personalized consent requests, a dynamic web-based infrastructure to record meta-consent, and default settings. To analyse the discussions, a thematic content analysis was performed using a qualitative software.ResultsOur findings showed that participants were supportive of this new approach of consent as it promotes transparency and offers autonomy for the management of their health data. Key facilitators were identified to be considered in the implementation of a meta-consent model in the Quebec LHSs: information and transparency, awareness campaigns, development of educational tools, collaboration of front-line healthcare professionals, default settings deemed acceptable by the society as well as close partnerships with recognized and trusted institutions.ConclusionsThis qualitative study reveals the openness of a sample of the Quebec population regarding the meta-consent model for secondary use of health data for research. This first exploratory study conducted with the public is an important step in guiding decision-makers in the next phases of implementing the various strategies to support access and use of health data in Quebec. (shrink)

Volume 24, Issue 10, October 2024, Page 101-103.

Data infrastructure includes the bureaucratic, technical, and social mechanisms that assist in actions like data management, analysis, storage, and sharing. While issues like data sharing have been addressed in depth in bioethical literature, data infrastructure presents its own ethical considerations, apart from the actions (such as data sharing and data analysis) that it enables. This essay outlines some of these considerations—namely, the ethics of efficiency, the visibility of infrastructure, the power of standards, and the (...) impact of new technologies—in order to invite the bioethics community to participate in conversations about infrastructure, as their expertise is both needed and welcomed. (shrink)

BackgroundThe ability of healthcare to protect sensitive personal data in medical records and registers might influence public trust, which in turn might influence willingness to allow healthcare to use such data. The aim of this study was to examine how the general public’s trust relates to their attitudes towards uses of health data.MethodsA stratified sample from the general Swedish population received a questionnaire about their willingness to share health data. Respondents were also asked about (...) their trust in the management and protection of electronic health data.ResultsA large majority (81.9%) of respondents revealed high levels of trust in the ability of healthcare to protect electronic patient data. Good health was associated with significantly higher levels of trust compared to bad health. Respondents with low levels of trust were significantly less willing to allow personal data to be used for different purposes and were more inclined to insist on being asked for permission beforehand. Those with low levels of trust also perceived risks of unauthorized access to personal data to be higher and the likely damage of such unauthorized access worse, compared to those with high levels of trust.ConclusionsTrust in the ability of healthcare to protect electronic health is generally high in Sweden. Those with higher levels of trust are more willing to let their data be used, including without informed consent. It thus seems crucial to promote trust in order to be able to reap the benefits that digitalization makes possible through increased access and use of data in healthcare. (shrink)

Powered by ‘big health data’ and enormous gains in computing power, artificial intelligence and related technologies are already changing the healthcare landscape. Harnessing the potential of these technologies will necessitate partnerships between health institutions and commercial companies, particularly as it relates to sharing health data. The need for commercial companies to be trustworthy users of data has been argued to be critical to the success of this endeavour. I argue that this approach is mistaken. (...) Our interactions with commercial companies need not, and should not, be based on trust. Rather, they should be based on confidence. I begin by elucidating the differences between trust, reliability, and confidence, and argue that trust is not the appropriate attitude to adopt when it comes to sharing data with commercial companies. I argue that what we really should want is confidence in a system of data sharing. I then provide an outline of what a confidence-worthy system of data sharing with commercial companies might look like, and conclude with some remarks about the role of trust within this system. (shrink)

Global health emergencies often lead to a proliferation of health-related research and resultant data, which is shared across borders to help control the outbreak of disease and support decision-making regarding public health interventions. However, efforts to share data can be hindered by diverse international ethical and legal frameworks. The frameworks aim to govern coordinated processing, sharing and transfer of health data across borders thus placing burdens on researchers who are willing or obligated to (...) share data. In this paper, we investigate ethical values and legal principles that can be applied to ensure a more streamlined approach in the governance of cross-border health data sharing during global health emergencies. A scoping review approach was used to better understand emerging evidence about issues related to the ethical and legal governance of cross-border health data sharing. We first highlight the challenges of sharing health data across borders. We then discuss how the challenges might be overcome through the application of ethical values and legal principles that have been identified in literature. This is followed by a proposal for possible ways of streamlining the governance of health data sharing from ethical and legal perspectives in a bid to better prepare for future global health emergencies and promote the responsible sharing of health data. (shrink)

Against the backdrop of a deepening funding crisis for academic research in the US, how and when can closer relationships between academia and industry better support the research enterprise? Spect...

BackgroundHealth data-driven activities have become central in diverse fields (research, AI development, wearables, etc.), and new ethical challenges have arisen with regards to privacy, integrity, and appropriateness of use. To ensure the protection of individuals’ fundamental rights and freedoms in a changing environment, including their right to the protection of personal data, we aim to identify the ethical approaches adopted by scientists during intensive data exploitation when collecting, using, or sharing peoples’ health data.MethodsTwelve scientists who (...) were collecting, using, or sharing health data in different contexts in Sweden, were interviewed. We used systematic expert interviews to access these scientists’ specialist knowledge, and analysed the interviews with thematic analysis. Phrases, sentences, or paragraphs through which ethical values and norms were expressed, were identified and coded. Codes that reflected similar concepts were grouped, subcategories were formulated, and categories were connected to traditional ethical approaches.ResultsThrough several examples, the respondents expressed four different ethical approaches, which formed the main conceptual categories: consideration of consequences, respect for rights, procedural compliance, and being professional.ConclusionsTo a large extent, the scientists’ ethical approaches were consistent with ethical and legal principles. Data sharing was considered important and worth pursuing, even though it is difficult. An awareness of the complex issues involved in data sharing was reflected from different perspectives, and the respondents commonly perceived a general lack of practical procedures that would by default ensure ethical and legally compliant data collection and sharing. We suggest that it is an opportune time to move on from policy discussions to practical technological ethics-by-design solutions that integrate these principles into practice. (shrink)

BackgroundRandomized controlled trials (RCTs) are often complex and expensive to perform. Less than one third achieve planned recruitment targets, follow-up can be labor-intensive, and many have limited real-world generalizability. Designs for RCTs conducted using cohorts and routinely collected health data, including registries, electronic health records, and administrative databases, have been proposed to address these challenges and are being rapidly adopted. These designs, however, are relatively recent innovations, and published RCT reports often do not describe important aspects of (...) their methodology in a standardized way. Our objective is to extend the Consolidated Standards of Reporting Trials (CONSORT) statement with a consensus-driven reporting guideline for RCTs using cohorts and routinely collected health data.MethodsThe development of this CONSORT extension will consist of five phases. Phase 1 (completed) consisted of the project launch, including fundraising, the establishment of a research team, and development of a conceptual framework. In phase 2, a systematic review will be performed to identify publications (1) that describe methods or reporting considerations for RCTs conducted using cohorts and routinely collected health data or (2) that are protocols or report results from such RCTs. An initial “long list” of possible modifications to CONSORT checklist items and possible new items for the reporting guideline will be generated based on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) and The REporting of studies Conducted using Observational Routinely-collected health Data (RECORD) statements. Additional possible modifications and new items will be identified based on the results of the systematic review. Phase 3 will consist of a three-round Delphi exercise with methods and content experts to evaluate the “long list” and generate a “short list” of key items. In phase 4, these items will serve as the basis for an in-person consensus meeting to finalize a core set of items to be included in the reporting guideline and checklist. Phase 5 will involve drafting the checklist and elaboration-explanation documents, and dissemination and implementation of the guideline.DiscussionDevelopment of this CONSORT extension will contribute to more transparent reporting of RCTs conducted using cohorts and routinely collected health data. (shrink)

Background Older adults, especially those with dementia, are often excluded from health research due to physical and medical comorbidities, and the assumption that those with cognitive impairment won’t be able to consent. Using routinely collected data for research purposes is a way to include older people in research, and therefore the benefits of research. However, very little research has been done to examine the attitudes of older people towards sharing their routinely collected health data for research (...) purposes. Method Twenty-eight semi-structured interviews were conducted with older health service users in the Counties Manukau health district of Auckland, New Zealand. The interviews explored participants’ views around the use of de-identified health data for health service improvement and health services research. Data were analysed using thematic analysis. Results Themes identified were: 1) Benefits: participants believed that there were benefits to sharing their health data such as helping others, improving health services, advancing scientific knowledge, and giving back to the health system; sharing health data was also seen as a reflection of good character, and people felt that their pre-existing views about whether they wished to share health data should be respected even if they were no longer able to consent. 2) Concerns: participants had concerns about sharing data with private companies, the use of inaccurate data, and the potential personal and societal consequences of sharing health data. 3) Expectations: participants encouraged collaboration between institutions in New Zealand, but expected data privacy to be maintained, processes to be transparent and cultural values around data to be respected; there was an expectation those sharing health data (patients or institutions) should benefit from any private sector gains. Conclusion Older people in our study were supportive of sharing their deidentified health data for research purposes provided that the research would benefit others, now and in the future. This provides more confidence in the use routinely collected health data of older people for research, provided that researchers handle data in a respectful way and use it to benefit communities while avoiding potential harms. Trial Registration NA. (shrink)

Tribal nations possess the inherent sovereign authority to protect the health and welfare of their people. Without equitable access to public health data, Tribal nations cannot fulfill this essential governmental duty. Federal, state, and local public health agencies must implement Tribal data sovereignty principles to support the exchange and protection of Tribal public health data. The adoption of Tribal data-sharing agreements can provide a framework for strengthening Tribal data sovereignty and recognizing (...) a Tribe’s inherent right to collect and manage their data. (shrink)

Background Several jurisdictions, including Singapore, Australia, New Zealand and most recently Ireland, have a public interest or public good criterion for granting waivers of consent in biomedical research using secondary health data or tissue. However, the concept of the public interest is not well defined in this context, which creates difficulties for institutions, institutional review boards and regulators trying to implement the criterion. Main text This paper clarifies how the public interest criterion can be defensibly deployed. We first (...) explain the ethical basis for requiring waivers to only be granted to studies meeting the public interest criterion, then explore how further criteria may be set to determine the extent to which a given study can legitimately claim to be in the public interest. We propose an approach that does not attempt to measure magnitude of benefit directly, but rather takes into account metrics that are more straightforward to apply. To ensure consistent and justifiable interpretation, research institutions and IRBs should also incorporate procedural features such as transparency and public engagement in determining which studies satisfy the public interest requirement. Conclusion The requirement of public interest for consent waivers in secondary biomedical research should be guided by well-defined criteria for systematic evaluation. Such a criteria and its application need to be periodically subject to intra-committee and intra-institution review, reflection, deliberation and amendment. (shrink)

The inclusion of members of structurally marginalized communities in data-intensive innovation initiatives, such as precision medicine projects, is an urgent contemporary issue. On the one hand, th...

Contemporary health data governance in Europe operates within a persistent tension between the protection of individual rights and the collective benefits that can be achieved through data sharing. Recent legislative initiatives such as the Data Act, Data Governance Act and the European Health Data Space attempt to reconcile these values by promoting trustworthy data reuse while safeguarding individual rights. However, these frameworks often rely on models of citizens as passive data donors, (...) without ensuring citizen empowerment or equitable benefit sharing. This study examines how institutional stakeholders in Flanders understand the ethical conditions under which a Personal Health Data Space could be governed legitimately for secondary health-data use. We use literature on distributive, procedural, and recognition justice to interpret these expectations and to identify design considerations for participatory health-data governance. The study employed an embedded research design within the We Are project, a Personal Health Data Space system under development in Flanders (Belgium). Empirical data were collected through stakeholder interviews and complemented by a purposive conceptual literature review on justice in health data governance. Data were thematically analysed through the lens of the three justice dimensions. Findings indicate that stakeholders support data solidarity, entailing expectations of reciprocity, transparency, and accountability. Distributive justice was associated with fair benefit-sharing mechanisms and reinvestment of data-derived value into public goods. Procedural justice was understood as continuous citizen participation and oversight, rather than one-time consent. Recognition justice emerged as the need to value diverse forms of knowledge and to include marginalised or underrepresented groups through inclusive data stewardship. The study concludes that both literature and stakeholder views support data solidarity as a more ethically robust foundation for health data governance than data altruism. Collective and participatory governance arrangements can operationalise solidarity by embedding fairness, inclusivity, and accountability in data reuse. These findings provide practical and conceptual guidance for the ethical design of Personal Health Data Space systems. This study is not a clinical trial. It is a conceptual and empirical qualitative / ethical analysis study and therefore clinical trial registration is not applicable. (shrink)

Data platforms represent a new paradigm for carrying out health research. In the platform model, datasets are pooled for remote access and analysis, so novel insights for developing better stratified and/or personalised medicine approaches can be derived from their integration. If the integration of diverse datasets enables development of more accurate risk indicators, prognostic factors, or better treatments and interventions, this obviates the need for the sharing and reuse of data; and a platform-based approach is an appropriate (...) model for facilitating this. Platform-based approaches thus require new thinking about consent. Here we defend an approach to meeting this challenge within the data platform model, grounded in: the notion of ‘reasonable expectations’ for the reuse of data; Waldron’s account of ‘integrity’ as a heuristic for managing disagreement about the ethical permissibility of the approach; and the element of the social contract that emphasises the importance of public engagement in embedding new norms of research consistent with changing technological realities. While a social contract approach may sound appealing, however, it is incoherent in the context at hand. We defend a way forward guided by that part of the social contract which requires public approval for the proposal and argue that we have moral reasons to endorse a wider presumption of data reuse. However, we show that the relationship in question is not recognisably contractual and that the social contract approach is therefore misleading in this context. We conclude stating four requirements on which the legitimacy of our proposal rests. (shrink)

Developments in medical big data analytics may bring societal benefits but are also challenging privacy and other ethical values. At the same time, an overly restrictive data protection regime can form a serious threat to valuable observational studies. Discussions about whether data privacy or data solidarity should be the foundational value of research policies, have remained unresolved. We add to this debate with an empirically informed ethical analysis. First, experiences with the implementation of the General (...) class='Hi'>Data Protection Regulation (GDPR) within a European research consortium demonstrate a gap between the aims of the regulation and its effects in practice. Namely, strictly formalised data protection requirements may cause routinisation among researchers instead of substantive ethical reflection, and may crowd out trust between actors in the health data research ecosystem; while harmonisation across Europe and data sharing between countries is hampered by different interpretations of the law, which partly stem from different views about ethical values. Then, building on these observations, we use theory to argue that the concept of trust provides an escape from the privacy-solidarity debate. Lastly, the paper details three aspects of trust that can help to create a responsible research environment and to mitigate the encountered challenges: trust as multi-agent concept; trust as a rational and democratic value; and trust as method for priority setting. Mutual cooperation in research—among researchers and with data subjects—is grounded in trust, which should be more explicitly recognised in the governance of health data research. (shrink)