Towards Principles-Based Approaches to Governance of Health-related Research using Personal Data

Specific measures for data-intensive health research without consent: a systematic review of soft law instruments and academic literature

It is a common misunderstanding of current European data protection law that when consent is not being used as lawful basis, the processing of personal data is prohibited. Article 9(2)(j) of the European General Data Protection Regulation (GDPR) permits Member States to establish a legal basis in national law that allows for the processing of personal data for scientific research purposes without consent. However, the European legislator has formulated this "research exemption" as an opening clause, rendering the GDPR not specific as to what measures exactly are required to comply with the research exemption. This may have significant implications for both the protection of personal data and the advancement of data-intensive health research. We performed a systematic review of relevant soft law instruments and academic literature to identify what measures are mentioned in those documents. Our analysis resulted in the identification of four overarching themes of suggested measures: organizational measures; technical measures; oversight and review mechanisms; and public engagement and participation. Some of the suggested measures do not substantially contribute to the clarification of the GDPR's "suitable and specific measures" requirement because they remain vague or broad in nature and encompass all types of data processing. However, the themes oversight and review mechanisms and public engagement and participation provide valuable insights which can be put to practice. Nevertheless, further clarification of the measures and safeguards that should be installed when invoking the research exemption remains necessary.

"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.

Notches on the dial: a call to action to develop plain language communication with the public about users and uses of health data

Population data science [1] researchers are not alone in recognizing the value of health and health-related data. In the era of big data, and with advent of machine learning and other artificial intelligence methods, organizations around the world are actively working to turn data into knowledge, and, in some cases, profit. The media and members of the public have taken notice, with high profile news stories about data breaches and privacy concerns [2-4] alongside some stories that call for increased use of data [5,6]. In response, public and private sector data-holding organizations and jurisdictions are turning their attention to policies, processes and regulations intended to ensure that personal data are used in ways that that the public supports. In some cases, these efforts include involving “publics” in decisions about data, such as using patient and lay person advice and other inputs to help shape policies [7-10].

Participatory governance over research in an academic research network: the case of Diabetes Action Canada

Digital data generated in the course of clinical care are increasingly being leveraged for a wide range of secondary purposes. Researchers need to develop governance policies that can assure the public that their information is being used responsibly. Our aim was to develop a generalisable model for governance of research emanating from health data repositories that will invoke the trust of the patients and the healthcare professionals whose data are being accessed for health research. We developed our governance principles and processes through literature review and iterative consultation with key actors in the research network including: a data governance working group, the lead investigators and patient advisors. We then recruited persons to participate in the governing and advisory bodies. Our governance process is informed by eight principles: (1) transparency; (2) accountability; (3) follow rule of law; (4) integrity; (5) participation and inclusiveness; (6) impartiality and independence; (7) effectiveness, efficiency and responsiveness and (8) reflexivity and continuous quality improvement. We describe the rationale for these principles, as well as their connections to the subsequent policies and procedures we developed. We then describe the function of the Research Governing Committee, the majority of whom are either persons living with diabetes or physicians whose data are being used, and the patient and data provider advisory groups with whom they consult and communicate. In conclusion, we have developed a values-based information governance framework and process for Diabetes Action Canada that adds value over-and-above existing scientific and ethics review processes by adding a strong patient perspective and contextual integrity. This model is adaptable to other secure data repositories.

Responsible data sharing in international health research: a systematic review of principles and norms

BACKGROUND

Large-scale linkage of international clinical datasets could lead to unique insights into disease aetiology and facilitate treatment evaluation and drug development. Hereto, multi-stakeholder consortia are currently designing several disease-specific translational research platforms to enable international health data sharing. Despite the recent adoption of the EU General Data Protection Regulation (GDPR), the procedures for how to govern responsible data sharing in such projects are not at all spelled out yet. In search of a first, basic outline of an ethical governance framework, we set out to explore relevant ethical principles and norms.

METHODS

We performed a systematic review of literature and ethical guidelines for principles and norms pertaining to data sharing for international health research.

RESULTS

We observed an abundance of principles and norms with considerable convergence at the aggregate level of four overarching themes: societal benefits and value; distribution of risks, benefits and burdens; respect for individuals and groups; and public trust and engagement. However, at the level of principles and norms we identified substantial variation in the phrasing and level of detail, the number and content of norms considered necessary to protect a principle, and the contextual approaches in which principles and norms are used.

CONCLUSIONS

While providing some helpful leads for further work on a coherent governance framework for data sharing, the current collection of principles and norms prompts important questions about how to streamline terminology regarding de-identification and how to harmonise the identified principles and norms into a coherent governance framework that promotes data sharing while securing public trust.

Contextual Anonymization for Secondary Use of Big Data in Biomedical Research: Proposal for an Anonymization Matrix

Background

The current law on anonymization sets the same standard across all situations, which poses a problem for biomedical research.

Objective

We propose a matrix for setting different standards, which is responsive to context and public expectations.

Methods

The law and ethics applicable to anonymization were reviewed in a scoping study. Social science on public attitudes and research on technical methods of anonymization were applied to formulate a matrix.

Results

The matrix adjusts anonymization standards according to the sensitivity of the data and the safety of the place, people, and projects involved.

Conclusions

The matrix offers a tool with context-specific standards for anonymization in data research.

Contextual Anonymization for Secondary Use of Big Data in Biomedical Research: Proposal for an Anonymization Matrix

BACKGROUND

The current law on anonymization sets the same standard across all situations, which poses a problem for biomedical research.

OBJECTIVE

We propose a matrix for setting different standards, which is responsive to context and public expectations.

METHODS

The law and ethics applicable to anonymization were reviewed in a scoping study. Social science on public attitudes and research on technical methods of anonymization were applied to formulate a matrix.

RESULTS

The matrix adjusts anonymization standards according to the sensitivity of the data and the safety of the place, people, and projects involved.

CONCLUSIONS

The matrix offers a tool with context-specific standards for anonymization in data research.

Research and Global Health Emergencies: On the Essential Role of Best Practice

This article addresses an important, overlooked regulatory challenge during global health emergencies (GHEs). It provides novel insights into how, and why, best practice can support decision makers in interpreting and implementing key guidance on conducting research during GHEs. The ability to conduct research before, during and after such events is crucial. The recent West-African Ebola outbreaks and the Zika virus have highlighted considerable room for improvement in meeting the imperative to research and rapidly develop effective therapies. A means of effectively capturing these experiences and folding them into future decision-making is lacking; the need for effective practical translational measures remains. The challenge for the research community lies in extracting meaningful action-guiding content from pre-existing guidelines-which draw upon practical examples of guidelines 'in action'-that assist in determining how to act in a particular (future) situation. Insights are provided into the role of best practice as a means to do so; such examples can provide invaluable support to decision makers in interpreting high-level guidance; overarching guidelines retain their necessary level of generality and flexibility, whilst corresponding best practice examples-which incorporate important lessons learned-illustrate how such guidelines can be interpreted at a practical level.

Challenges in accessing routinely collected data from multiple providers in the UK for primary studies: Managing the morass

INTRODUCTION

Researchers are increasingly using routinely collected data in addition to, or instead of, other data collection methods. The UK government continues to invest in research centres to encourage use of these data, and trials and cohort studies utilise data linkage methods in the follow-up of participants. This does not come without its limitations and challenges, such as data access delays.

OBJECTIVE

This paper outlines the challenges faced by three projects utilising individual-level routinely-collected linked data for the longer-term follow-up of participants.

METHODS

These studies are varied in design, study population and data providers. One researcher was common to the three studies and collated relevant study correspondence, formal documentary evidence such as data sharing agreements and, where relevant, meeting records to review. Key themes were identified and reviewed by other members of the research teams. Mitigating strategies were identified and discussed with a data provider representative and a broader group of researchers to finalise the recommendations presented.

RESULTS

The challenges discussed are grouped into five themes: Data application process; Project timelines; Dependencies and considerations related to consent; Information Governance; Contractual. In presenting our results descriptively we summarise each case study, identify the main cross-cutting themes and consider the potential for mitigation of challenges.

CONCLUSIONS

We make recommendations that identify responsibilities for both researchers and data providers for mitigating and managing data access challenges. A continued conversation within the research community and with data providers is needed to continue to enable researchers to access and utilise the wealth of routinely-collected data available. The suggestions made in this paper will help researchers be better prepared to deal with the challenges of applying for data from multiple data providers.

Challenges in accessing routinely collected data from multiple providers in the UK for primary studies: Managing the morass

Introduction

Researchers are increasingly using routinely collected data in addition to, or instead of, other data collection methods. The UK government continues to invest in research centres to encourage use of these data, and trials and cohort studies utilise data linkage methods in the follow-up of participants. This does not come without its limitations and challenges, such as data access delays.

Objective

This paper outlines the challenges faced by three projects utilising individual-level routinely-collected linked data for the longer-term follow-up of participants.

Methods

These studies are varied in design, study population and data providers. One researcher was common to the three studies and collated relevant study correspondence, formal documentary evidence such as data sharing agreements and, where relevant, meeting records to review. Key themes were identified and reviewed by other members of the research teams. Mitigating strategies were identified and discussed with a data provider representative and a broader group of researchers to finalise the recommendations presented.

Results

The challenges discussed are grouped into five themes: Data application process; Project timelines; Dependencies and considerations related to consent; Information Governance; Contractual. In presenting our results descriptively we summarise each case study, identify the main cross-cutting themes and consider the potential for mitigation of challenges.

Conclusions

We make recommendations that identify responsibilities for both researchers and data providers for mitigating and managing data access challenges. A continued conversation within the research community and with data providers is needed to continue to enable researchers to access and utilise the wealth of routinely-collected data available. The suggestions made in this paper will help researchers be better prepared to deal with the challenges of applying for data from multiple data providers.

Personal health data: A systematic mapping study

BACKGROUND

Personal health data (PHD) research has been intensified over the last years, attracting the attention of scientists from different fields, such as software engineers, computer scientists and medical professionals. The increasing interest of researchers can be attributed to the exponential growth of the available PHD due to the widespread adoption of ubiquitous technology in everyday life, as well as to the potential of the ongoing digital transformation in healthcare. This increasing interest requires that academia has an overview of the published scientific literature to plan future endeavors.

OBJECTIVE

The main objective of this study is to identify and address research gaps in literature regarding PHD.

METHOD

This paper conducts a systematic mapping study to summarize the existing PHD approaches in literature and to organize the selected studies according to six classification criteria: publication source, publication year, research types, empirical types, contribution types and research topic.

RESULTS

In total 79 papers have been included after fulfilling the inclusion criteria and have been classified accordingly. There is an increasing amount of attention that has been paid to PHD since 2014. The majority of papers is published in journals. The two main research types found were solution proposals and evaluation research. The majority of the selected papers were empirically evaluated. The main contribution types were methods and frameworks. Data privacy is the most frequently addressed topic in PHD literature, followed by data sharing.

CONCLUSIONS

The findings of this systematic mapping study have implications for both researchers who are planning new studies in PHD and for practitioners who are working in connected health and would like to have an overview on the existent studies on PHD research area.

Criminal Prohibition of Wrongful Re‑identification: Legal Solution or Minefield for Big Data?

The collapse of confidence in anonymization (sometimes also known as de-identification) as a robust approach for preserving the privacy of personal data has incited an outpouring of new approaches that aim to fill the resulting trifecta of technical, organizational, and regulatory privacy gaps left in its wake. In the latter category, and in large part due to the growth of Big Data-driven biomedical research, falls a growing chorus of calls for criminal and penal offences to sanction wrongful re-identification of "anonymized" data. This chorus cuts across the fault lines of polarized privacy law scholarship that at times seems to advocate privacy protection at the expense of Big Data research or vice versa. Focusing on Big Data in the context of biomedicine, this article surveys the approaches that criminal or penal law might take toward wrongful re-identification of health data. It contextualizes the strategies within their respective legal regimes as well as in relation to emerging privacy debates focusing on personal data use and data linkage and assesses the relative merit of criminalization. We conclude that this approach suffers from several flaws and that alternative social and legal strategies to deter wrongful re-identification may be preferable.

A critique of the regulation of data science in healthcare research in the European Union

The EU offers a suitable milieu for the comparison and harmonisation of healthcare across different languages, cultures, and jurisdictions (albeit with a supranational legal framework), which could provide improvements in healthcare standards across the bloc. There are specific ethico-legal issues with the use of data in healthcare research that mandate a different approach from other forms of research. The use of healthcare data over a long period of time is similar to the use of tissue in biobanks. There is a low risk to subjects but it is impossible to gain specific informed consent given the future possibilities for research. Large amounts of data on a subject present a finite risk of re-identification. Consequently, there is a balancing act between this risk and retaining sufficient utility of the data. Anonymising methods need to take into account the circumstances of data sharing to enable an appropriate balance in all cases. There are ethical and policy advantages to exceeding the legal requirements and thereby securing the social licence for research. This process would require the examination and comparison of data protection laws across the trading bloc to produce an ethico-legal framework compatible with the requirements of all member states. Seven EU jurisdictions are given consideration in this critique.

The ADVANCE Code of Conduct for collaborative vaccine studies

Lessons learnt from the 2009 (H1N1) flu pandemic highlighted factors limiting the capacity to collect European data on vaccine exposure, safety and effectiveness, including lack of rapid access to available data sources or expertise, difficulties to establish efficient interactions between multiple parties, lack of confidence between private and public sectors, concerns about possible or actual conflicts of interest (or perceptions thereof) and inadequate funding mechanisms. The Innovative Medicines Initiative's Accelerated Development of VAccine benefit-risk Collaboration in Europe (ADVANCE) consortium was established to create an efficient and sustainable infrastructure for rapid and integrated monitoring of post-approval benefit-risk of vaccines, including a code of conduct and governance principles for collaborative studies. The development of the code of conduct was guided by three core and common values (best science, strengthening public health, transparency) and a review of existing guidance and relevant published articles. The ADVANCE Code of Conduct includes 45 recommendations in 10 topics (Scientific integrity, Scientific independence, Transparency, Conflicts of interest, Study protocol, Study report, Publication, Subject privacy, Sharing of study data, Research contract). Each topic includes a definition, a set of recommendations and a list of additional reading. The concept of the study team is introduced as a key component of the ADVANCE Code of Conduct with a core set of roles and responsibilities. It is hoped that adoption of the ADVANCE Code of Conduct by all partners involved in a study will facilitate and speed-up its initiation, design, conduct and reporting. Adoption of the ADVANCE Code of Conduct should be stated in the study protocol, study report and publications and journal editors are encouraged to use it as an indication that good principles of public health, science and transparency were followed throughout the study.

If you build it, they will come: unintended future uses of organised health data collections

BACKGROUND

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 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.

DISCUSSION

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

CONCLUSIONS

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.

On moving targets and magic bullets: Can the UK lead the way with responsible data linkage for health research?

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We explore key elements of good governance in health linkage.

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Adaptive reflexive governance models are essential.

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Two examples illustrate how we can achieve standardisation of practice.

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Distinct elements of governance compiled in a composite fashion tend to challenges.

Purpose

To provide an overview of essential elements of good governance of data linkage for health-related research, to consider lessons learned so far and to examine key factors currently impeding the delivery of good governance in this area. Given the considerable hurdles which must be overcome and the changing landscape of health research and data linkage, a principled, proportionate, risk-based approach to governance is advocated.

Discussion

In light of the considerable value of data linkage to health and well-being, the United Kingdom aspires to design and deliver good governance in health-related research. A string of projects have been asking: what does good governance look like in data linkage for health research? It is argued here that considerable progress can and must be made in order to develop the UK’s contribution to future health and wealth economies, particularly in light of mis-start initiatives such as care.data in NHS England. Discussion centres around lessons learned from previous successful health research initiatives, identifying those governance mechanisms which are essential to achieving good governance.

Conclusion

This article suggests that a crucial element in any step-increase of research capability will be the adoption of adaptive governance models. These must recognise a range of approaches to delivering safe and effective data linkage, while remaining responsive to public and research user expectations and needs as these shift and change with time and experience. The targets are multiple and constantly moving. There is not – nor should we seek – a single magic bullet in delivering good governance in health research.

The promotion of data sharing in pharmacoepidemiology

This article addresses the role of pharmacoepidemiology in patient safety and the crucial role of data sharing in ensuring that such activities occur. Against the backdrop of proposed reforms of European data protection legislation, it considers whether the current legislative landscape adequately facilitates this essential data sharing. It is argued that rather than maximising and promoting the benefits of such activities by facilitating data sharing, current and proposed legislative landscapes hamper these vital activities. The article posits that current and proposed data protection approaches to pharmacoepidemiology--and more broadly, re-uses of data--should be reoriented towards enabling these important safety enhancing activities. Two potential solutions are offered: 1) a dedicated working party on data reuse for health research and 2) the introduction of new, dedicated legislation.

Recognizing the Right Not to Know: Conceptual, Professional, and Legal Implications

This article argues for the importance of conceptual clarity in the debate about the so-called right not to know. This is vital both at the theoretical and the practical level. It is suggested that, unlike many formulations and attempts to give effect to this right, what is at stake is not merely an aspect of personal autonomy and therefore cannot and should not be reduced only to a question of individual choice. Rather, it is argued that the core interests that can be protected by the right not to know are better conceived of as privacy interests rather than autonomy interests. This not only helps us to understand what is in play but also informs regulatory, professional, and legal responses to handling information and taking decisions about whether or not to disclose information to persons about themselves. The practical implications of this conceptualization are explored in the context of feedback policies in health-related research.