Sync fast and solve things-best practices for responsible digital health

Digital health innovation is expected to transform healthcare, but it also generates ethical and societal concerns, such as privacy risks, and biases that can compound existing health inequalities. While such concerns are widely recognized, existing regulatory principles, oversight methods and ethical frameworks seem out of sync with digital health innovation. New governance and innovation best practices are thus needed to bring such principles to bear with the reality of business, innovation, and regulation.To grant practical insight into best practices for responsible digital health innovation, we conducted a qualitative study based on an interactive engagement methodology. We engaged key stakeholders (n = 46) operating at the translational frontier of digital health. This approach allowed us to identify three clusters of governance and innovation best practices in digital health innovation: i) inclusive co-creation, ii) responsive regulation, and iii) value-driven innovation. Our study shows that realizing responsible digital health requires diverse stakeholders' commitment to adapt innovation and regulation practices, embracing co-creation as the default modus operandi for digital health development. We describe these collaborative practices and show how they can ensure that innovation is neither slowed by overregulation, nor leads to unethical outcomes.

Mapping the ethical landscape of digital biomarkers: A scoping review

In the evolving landscape of digital medicine, digital biomarkers have emerged as a transformative source of health data, positioning them as an indispensable element for the future of the discipline. This necessitates a comprehensive exploration of the ethical complexities and challenges intrinsic to this cutting-edge technology. To address this imperative, we conducted a scoping review, seeking to distill the scientific literature exploring the ethical dimensions of the use of digital biomarkers. By closely scrutinizing the literature, this review aims to bring to light the underlying ethical issues associated with the development and integration of digital biomarkers into medical practice.

Research ethics and artificial intelligence for global health: perspectives from the global forum on bioethics in research

BACKGROUND

The ethical governance of Artificial Intelligence (AI) in health care and public health continues to be an urgent issue for attention in policy, research, and practice. In this paper we report on central themes related to challenges and strategies for promoting ethics in research involving AI in global health, arising from the Global Forum on Bioethics in Research (GFBR), held in Cape Town, South Africa in November 2022.

METHODS

The GFBR is an annual meeting organized by the World Health Organization and supported by the Wellcome Trust, the US National Institutes of Health, the UK Medical Research Council (MRC) and the South African MRC. The forum aims to bring together ethicists, researchers, policymakers, research ethics committee members and other actors to engage with challenges and opportunities specifically related to research ethics. In 2022 the focus of the GFBR was "Ethics of AI in Global Health Research". The forum consisted of 6 case study presentations, 16 governance presentations, and a series of small group and large group discussions. A total of 87 participants attended the forum from 31 countries around the world, representing disciplines of bioethics, AI, health policy, health professional practice, research funding, and bioinformatics. In this paper, we highlight central insights arising from GFBR 2022.

RESULTS

We describe the significance of four thematic insights arising from the forum: (1) Appropriateness of building AI, (2) Transferability of AI systems, (3) Accountability for AI decision-making and outcomes, and (4) Individual consent. We then describe eight recommendations for governance leaders to enhance the ethical governance of AI in global health research, addressing issues such as AI impact assessments, environmental values, and fair partnerships.

CONCLUSIONS

The 2022 Global Forum on Bioethics in Research illustrated several innovations in ethical governance of AI for global health research, as well as several areas in need of urgent attention internationally. This summary is intended to inform international and domestic efforts to strengthen research ethics and support the evolution of governance leadership to meet the demands of AI in global health research.

Digital tools for youth health promotion: principles, policies and practices in sub-Saharan Africa

Although digital health promotion (DHP) technologies for young people are increasingly available in low- and middle-income countries (LMICs), there has been insufficient research investigating whether existing ethical and policy frameworks are adequate to address the challenges and promote the technological opportunities in these settings. In an effort to fill this gap and as part of a larger research project, in November 2022, we conducted a workshop in Cape Town, South Africa, entitled 'Unlocking the Potential of Digital Health Promotion for Young People in Low- and Middle-Income Countries'. The workshop brought together 25 experts from the areas of digital health ethics, youth health and engagement, health policy and promotion and technology development, predominantly from sub-Saharan Africa (SSA), to explore their views on the ethics and governance and potential policy pathways of DHP for young people in LMICs. Using the World Café method, participants contributed their views on (i) the advantages and barriers associated with DHP for youth in LMICs, (ii) the availability and relevance of ethical and regulatory frameworks for DHP and (iii) the translation of ethical principles into policies and implementation practices required by these policies, within the context of SSA. Our thematic analysis of the ensuing discussion revealed a willingness to foster such technologies if they prove safe, do not exacerbate inequalities, put youth at the center and are subject to appropriate oversight. In addition, our work has led to the potential translation of fundamental ethical principles into the form of a policy roadmap for ethically aligned DHP for youth in SSA.

What are the bottlenecks to health data sharing in Switzerland? An interview study

BACKGROUND

While health data sharing for research purposes is strongly supported in principle, it can be challenging to implement in practice. Little is known about the actual bottlenecks to health data sharing in Switzerland.

AIMS OF THE STUDY

This study aimed to assess the obstacles to Swiss health data sharing, including legal, ethical and logistical bottlenecks.

METHODS

We identified 37 key stakeholders in data sharing via the Swiss Personalised Health Network ecosystem, defined as being an expert on sharing sensitive health data for research purposes at a Swiss university hospital (or a Swiss disease cohort) or being a stakeholder in data sharing at a public or private institution that uses such data. We conducted semi-structured interviews, which were transcribed, translated when necessary, and de-identified. The entire research team discussed the transcripts and notes taken during each interview before an inductive coding process occurred.

RESULTS

Eleven semi-structured interviews were conducted (primarily in English) with 17 individuals representing lawyers, data protection officers, ethics committee members, scientists, project managers, bioinformaticians, clinical trials unit members, and biobank stakeholders. Most respondents felt that it was not the actual data transfer that was the bottleneck but rather the processes and systems around it, which were considered time-intensive and confusing. The templates developed by the Swiss Personalised Health Network and the Swiss General Consent process were generally felt to have streamlined processes significantly. However, these logistics and data quality issues remain practical bottlenecks in Swiss health data sharing. Areas of legal uncertainty include privacy laws when sharing data internationally, questions of "who owns the data", inconsistencies created because the Swiss general consent is perceived as being implemented differently across different institutions, and definitions and operationalisation of anonymisation and pseudo-anonymisation. Many participants desired to create a "culture of data sharing" and to recognise that data sharing is a process with many steps, not an event, that requires sustainability efforts and personnel. Some participants also stressed a desire to move away from data sharing and the current privacy focus towards processes that facilitate data access.

CONCLUSIONS

Facilitating a data access culture in Switzerland may require legal clarifications, further education about the process and resources to support data sharing, and further investment in sustainable infrastructureby funders and institutions.

How Do Molecular Systems Engineering Scientists Frame the Ethics of Their Research?

BACKGROUND

There are intense discussions about the ethical and societal implications of biomedical engineering, but little data to suggest how scientists think about the ethics of their work. The aim of this study is to describe how scientists frame the ethics of their research, with a focus on the field of molecular systems engineering.

METHODS

Semi-structured qualitative interviews were conducted during 2021-2022, as part of a larger study. This analysis includes a broad question about how participants view ethics as related to their work, with follow up probes about the topics they consider most important. Interviews were transcribed, inductively coded by two researchers to consensus, and analyzed thematically.

RESULTS

Twenty-four scientists participated in the study. Interviewees hold positions as professors, principal investigators, and senior staff researchers in universities or research institutes in the United States and Europe. Among those scientists who reported reflecting on ethical considerations in their work, many equated ethics with research ethics topics (e.g., safety, replicability), or with regulation and guidelines. Participants expressed the view that ethical issues are primarily relevant for clinical trials of bioengineered products, or for those working with animal or human subjects. Scientists described their research as "too early" or "not examining anything living" with regard to ethical reflection. Finally, many felt that ethics is seen as territory for experts and therefore beyond scientists' competencies.

CONCLUSIONS

Molecular systems engineering scientists currently focus on regulatory aspects as the framework for their ethical analyses. They describe using a framework to define when life arises, as a means to determine when further ethical engagement is warranted. Further research is needed to investigate how scientists relate to the ethics of their scientific work, and build consensus around concepts of life, autonomous behavior, and physiological relevance of bioengineered systems.

Digital bioethics: introducing new methods for the study of bioethical issues

The online space has become a digital public square, where individuals interact and share ideas on the most trivial to the most serious of matters, including discussions of controversial ethical issues in science, technology and medicine. In the last decade, new disciplines like computational social science and social data science have created methods to collect and analyse such data that have considerably expanded the scope of social science research. Empirical bioethics can benefit from the integration of such digital methods to investigate novel digital phenomena and trace how bioethical issues take shape online.Here, using concrete examples, we demonstrate how novel methods based on digital approaches in the social sciences can be used effectively in the domain of bioethics. We show that a digital turn in bioethics research aligns with the established aims of empirical bioethics, integrating with normative analysis and expanding the scope of the discipline, thus offering ways to reinforce the capacity of bioethics to tackle the increasing complexity of present-day ethical issues in science and technology. We propose to call this domain of research in bioethics digital bioethics.

Ethical Aspects of Pediatric Genetic Care: Testing and Treatment

Pediatric health care providers caring for patients and families with genetic disease will encounter a range of ethical issues. These include traditional pediatric health care issues, such as surrogate decision making and end-of-life care. Genetic testing raises the importance of informed consent for potential risks that move beyond the oft discussed physical risks and into longer term concepts such as psychological impact, privacy and potential discrimination. Predictive testing in childhood also raises questions of whether the child has an autonomy interest in delaying testing until they have decision making capacity to do so on their own. And finally, treatments including gene therapies and gene editing, may raise issues of identity for families dealing with genetic disease.

Unlock digital health promotion in LMICs to benefit the youth

As digital technologies such as smartphones and fitness bands become more ubiquitous, individuals can engage in self-monitoring and self-care, gaining greater control over their health trajectories along the life-course. These technologies appeal particularly to young people, who are more familiar with digital devices. How this digital transformation facilitates health promotion is therefore a topic of animated debate. However, most research to date focuses on the promise and peril of digital health promotion (DHP) in high-income settings, while DHP in low- and middle-income countries (LMICs) remain largely unexplored. This narrative review aims to fill this gap by critically examining key ethical challenges of implementing DHP in LMICs, with a focus on young people. In the existing literature, we identified potential impediments as well as enabling conditions. Aspects to consider in unlocking the potential of DHP include (1) addressing the digital divide and structural injustice in data-related practices; (2) engaging the target population and responding to their specific needs given their economic, cultural, and social contexts; (3) monitoring the quality and impact of DHP over time; and (4) improving responsible technology governance and its implementation. Addressing these concerns could result in meaningful health benefits for populations lacking access to more conventional healthcare resources.

The Challenges for Regulating Medical Use of ChatGPT and Other Large Language Models

This Viewpoint discusses how regulators across the world should approach the legal and ethical challenges, including privacy, device regulation, competition, intellectual property rights, cybersecurity, and liability, raised by the medical use of large language models.

Talking Ethics Early in Health Data Public Private Partnerships

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.

Decentralised clinical trials: ethical opportunities and challenges

Fuelled by adaptations to clinical trial implementation during the COVID-19 pandemic, decentralised clinical trials are burgeoning. Decentralised clinical trials involve many digital tools to facilitate research without physical contact between research teams and participants at various stages, such as recruitment, enrolment, informed consent, administering study interventions, obtaining patient-reported outcome measures, and safety monitoring. These tools can provide ways of ensuring participants' safety and research integrity, while sometimes reducing participant burden and trial cost. Research sponsors and investigators are interested in expanding the use of decentralised clinical trials. The US Food and Drug Administration and other regulators worldwide have issued guidance on how to implement such adaptations. However, there has been little focus on the distinct ethical challenges these trials pose. In this Health Policy report, which is informed by both traditional research ethics and digital ethics frameworks, we group the related ethical issues under three areas requiring increased ethical vigilance: participants' safety and rights, scientific validity, and ethics oversight. Our aim is to describe these issues, offer practical means of addressing them, and prompt the delineation of ethical standards for decentralised trials.

How Interactive Visualizations Compare to Ethical Frameworks as Stand-Alone Ethics Learning Tools for Health Researchers and Professionals

BACKGROUND

Despite the bourgeoning of digital tools for bioethics research, education, and engagement, little research has empirically investigated the impact of interactive visualizations as a way to translate ethical frameworks and guidelines. To date, most frameworks take the format of text-only documents that outline and offer ethical guidance on specific contexts. This study's goal was to determine whether an interactive-visual format supports frameworks in transferring ethical knowledge by improving learning, deliberation, and user experience.

METHODS

An experimental comparative study was conducted with a pre-, mid-, and post-test design using the online survey platform Qualtrics. Participants were university based early-stage health researchers who were randomly assigned to either the control condition (text-only document) or the experimental condition (interactive-visual). The primary outcome variables were learning, (measured using a questionnaire), deliberation (using cases studies) and user experience (measured using the SED/UD Scale). Analysis was conducted using descriptive statistics and mixed-effects linear regression.

RESULTS

Of the 80 participants, 44 (55%) used the text-only document and 36 (45%) used the interactive-visual. Results of the knowledge-test scores showed a statistically significant difference between participants' post-test scores, indicating that the interactive-visual format better supported understanding, acquisition, and application of the framework's knowledge. Findings from the case studies showed both formats supported ethical deliberation. Results further indicated the interactive-visual provided an overall better episodic and remembered user experience compared with the text-only document.

CONCLUSIONS

Our findings show that ethical frameworks formatted with interactive and visual qualities provide a more pleasing user experience and are effective formats for ethics learning and deliberation. These findings have implications for practitioners developing and deploying ethical frameworks and guidelines (e.g., in educational or employee-onboarding settings), in that the knowledge generated can lead to more effective dissemination practices of normative guidelines and health data ethics concepts.

Stuck in translation: Stakeholder perspectives on impediments to responsible digital health

Spurred by recent advances in machine learning and electronic hardware, digital health promises to profoundly transform medicine. At the same time, however, it raises conspicuous ethical and regulatory issues. This has led to a growing number of calls for responsible digital health. Based on stakeholder engagement methods, this paper sets out to identify core impediments hindering responsible digital health in Switzerland. We developed a participatory research methodology to access stakeholders' fragmented knowledge of digital health, engaging 46 digital health stakeholders over a period of five months (December 2020-April 2021). We identified ineffective stakeholder collaboration, lack of ethical awareness among digital health innovators, and lack of relevant regulation as core impediments to responsible digital health. The stakeholders' accounts indicate that ethical concerns may considerably slow the pace of digital health innovation - implying that responsible innovation is a core catalyst for the progress of digital health overall.

Expectations and attitudes towards medical artificial intelligence: A qualitative study in the field of stroke

INTRODUCTION

Artificial intelligence (AI) has the potential to transform clinical decision-making as we know it. Powered by sophisticated machine learning algorithms, clinical decision support systems (CDSS) can generate unprecedented amounts of predictive information about individuals' health. Yet, despite the potential of these systems to promote proactive decision-making and improve health outcomes, their utility and impact remain poorly understood due to their still rare application in clinical practice. Taking the example of AI-powered CDSS in stroke medicine as a case in point, this paper provides a nuanced account of stroke survivors', family members', and healthcare professionals' expectations and attitudes towards medical AI.

METHODS

We followed a qualitative research design informed by the sociology of expectations, which recognizes the generative role of individuals' expectations in shaping scientific and technological change. Semi-structured interviews were conducted with stroke survivors, family members, and healthcare professionals specialized in stroke based in Germany and Switzerland. Data was analyzed using a combination of inductive and deductive thematic analysis.

RESULTS

Based on the participants' deliberations, we identified four presumed roles that medical AI could play in stroke medicine, including an administrative, assistive, advisory, and autonomous role AI. While most participants held positive attitudes towards medical AI and its potential to increase accuracy, speed, and efficiency in medical decision making, they also cautioned that it is not a stand-alone solution and may even lead to new problems. Participants particularly emphasized the importance of relational aspects and raised questions regarding the impact of AI on roles and responsibilities and patients' rights to information and decision-making. These findings shed light on the potential impact of medical AI on professional identities, role perceptions, and the doctor-patient relationship.

CONCLUSION

Our findings highlight the need for a more differentiated approach to identifying and tackling pertinent ethical and legal issues in the context of medical AI. We advocate for stakeholder and public involvement in the development of AI and AI governance to ensure that medical AI offers solutions to the most pressing challenges patients and clinicians face in clinical care.

Beyond high hopes: A scoping review of the 2019-2021 scientific discourse on machine learning in medical imaging

Machine learning has become a key driver of the digital health revolution. That comes with a fair share of high hopes and hype. We conducted a scoping review on machine learning in medical imaging, providing a comprehensive outlook of the field's potential, limitations, and future directions. Most reported strengths and promises included: improved (a) analytic power, (b) efficiency (c) decision making, and (d) equity. Most reported challenges included: (a) structural barriers and imaging heterogeneity, (b) scarcity of well-annotated, representative and interconnected imaging datasets (c) validity and performance limitations, including bias and equity issues, and (d) the still missing clinical integration. The boundaries between strengths and challenges, with cross-cutting ethical and regulatory implications, remain blurred. The literature emphasizes explainability and trustworthiness, with a largely missing discussion about the specific technical and regulatory challenges surrounding these concepts. Future trends are expected to shift towards multi-source models, combining imaging with an array of other data, in a more open access, and explainable manner.

Health data privacy through homomorphic encryption and distributed ledger computing: an ethical-legal qualitative expert assessment study

BACKGROUND

Increasingly, 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.

METHODS

To 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.

RESULTS

For 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.

CONCLUSION

Our findings can help guide the deployment of these technologies, as well as determine ethics and legal requirements for such technologies.

In the shadow of privacy: Overlooked ethical concerns in COVID-19 digital epidemiology

The COVID-19 pandemic witnessed a surge in the use of health data to combat the public health threat. As a result, the use of digital technologies for epidemic surveillance showed great potential to collect vast volumes of data, and thereby respond more effectively to the healthcare challenges. However, the deployment of these technologies raised legitimate concerns over risks to individual privacy. While the ethical and governance debate focused primarily on these concerns, other relevant issues remained in the shadows. Leveraging examples from the COVID-19 pandemic, this perspective article aims to investigate these overlooked issues and their ethical implications. Accordingly, we explore the problem of the digital divide, the role played by tech companies in the public health domain and their power dynamics with the government and public research sector, and the re-use of personal data, especially in the absence of adequate public involvement. Even if individual privacy is ensured, failure to properly engage with these other issues will result in digital epidemiology tools that undermine equity, fairness, public trust, just distribution of benefits, autonomy, and minimization of group harm. On the contrary, a better understanding of these issues, a broader ethical and data governance approach, and meaningful public engagement will encourage adoption of these technologies and the use of personal data for public health research, thus increasing their power to tackle epidemics.

Autonomous surgical robotic systems and the liability dilemma

Background

Advances in machine learning and robotics have allowed the development of increasingly autonomous robotic systems which are able to make decisions and learn from experience. This distribution of decision-making away from human supervision poses a legal challenge for determining liability.

Methods

The iRobotSurgeon survey aimed to explore public opinion towards the issue of liability with robotic surgical systems. The survey included five hypothetical scenarios where a patient comes to harm and the respondent needs to determine who they believe is most responsible: the surgeon, the robot manufacturer, the hospital, or another party.

Results

A total of 2,191 completed surveys were gathered evaluating 10,955 individual scenario responses from 78 countries spanning 6 continents. The survey demonstrated a pattern in which participants were sensitive to shifts from fully surgeon-controlled scenarios to scenarios in which robotic systems played a larger role in decision-making such that surgeons were blamed less. However, there was a limit to this shift with human surgeons still being ascribed blame in scenarios of autonomous robotic systems where humans had no role in decision-making. Importantly, there was no clear consensus among respondents where to allocate blame in the case of harm occurring from a fully autonomous system.

Conclusions

The iRobotSurgeon Survey demonstrated a dilemma among respondents on who to blame when harm is caused by a fully autonomous surgical robotic system. Importantly, it also showed that the surgeon is ascribed blame even when they have had no role in decision-making which adds weight to concerns that human operators could act as “moral crumple zones” and bear the brunt of legal responsibility when a complex autonomous system causes harm.

Public preferences towards data management and governance in Swiss biobanks: results from a nationwide survey

OBJECTIVES

This article aims to measure the willingness of the Swiss public to participate in personalised health research, and their preferences regarding data management and governance.

SETTING

Results are presented from a nationwide survey of members of the Swiss public.

PARTICIPANTS

15 106 randomly selected Swiss residents received the survey in September 2019. The response rate was 34.1% (n=5156). Respondent age ranged from 18 to 79 years, with fairly uniform spread across sex and age categories between 25 and 64 years.

PRIMARY AND SECONDARY OUTCOME MEASURES

Willingness to participate in personalised health research and opinions regarding data management and governance.

RESULTS

Most respondents preferred to be contacted and reconsented for each new project using their data (39%, 95% CI: 37.4% to 40.7%), or stated that their preference depends on the project type (29.4%, 95% CI: 27.9% to 31%). Additionally, a majority (52%, 95% CI: 50.3% to 53.8%) preferred their data or samples be stored anonymously or in coded form (43.4%, 95% CI: 41.7% to 45.1%). Of those who preferred that their data be anonymised, most also indicated a wish to be recontacted for each new project (36.8%, 95% CI: 34.5% to 39.2%); however, these preferences are in conflict. Most respondents desired to personally own their data. Finally, most Swiss respondents trust their doctors, along with researchers at universities, to protect their data.

CONCLUSION

Insight into public preference can enable Swiss biobanks and research institutions to create management and governance strategies that match the expectations and preferences of potential participants. Models allowing participants to choose how to interact with the process, while more complex, may increase individual willingness to provide data to biobanks.

Towards a Governance Framework for Brain Data

The increasing availability of brain data within and outside the biomedical field, combined with the application of artificial intelligence (AI) to brain data analysis, poses a challenge for ethics and governance. We identify distinctive ethical implications of brain data acquisition and processing, and outline a multi-level governance framework. This framework is aimed at maximizing the benefits of facilitated brain data collection and further processing for science and medicine whilst minimizing risks and preventing harmful use. The framework consists of four primary areas of regulatory intervention: binding regulation, ethics and soft law, responsible innovation, and human rights.

Assessing the Governance of Digital Contact Tracing in Response to COVID-19: Results of a Multi-National Study

This paper describes the results of a multi-country survey of governance approaches for the use of digital contact tracing (DCT) in response to the COVID-19 pandemic. We argue that the countries in our survey represent two distinct models of DCT governance, both of which are flawed. The "data protection model" emphasizes privacy protections at the expense of public health benefit, while the "emergency response model" sacrifices transparency and accountability, prompting concerns about excessive governance surveillance. The ethical and effective use of DCT in the future requires a new governance approach that is better suited to this novel use of mobile phone data to promote public health."

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

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

Benefits, challenges, and contributors to success for national eHealth systems implementation: a scoping review

OBJECTIVE

Our scoping review aims to assess what legal, ethical, and socio-technical factors contribute to or inhibit the success of national eHealth system implementations. In addition, our review seeks to describe the characteristics and benefits of eHealth systems.

MATERIALS AND METHODS

We conducted a scoping review of literature published in English between January 2000 and 2020 using a keyword search on 5 databases: PubMed, Scopus, Web of Science, IEEEXplore, and ProQuest. After removal of duplicates, abstract screening, and full-text filtering, 86 articles were included from 8276 search results.

RESULTS

We identified 17 stakeholder groups, 6 eHealth Systems areas, and 15 types of legal regimes and standards. In-depth textual analysis revealed challenges mainly in implementation, followed by ethico-legal and data-related aspects. Key factors influencing success include promoting trust of the system, ensuring wider acceptance among users, reconciling the system with legal requirements, and ensuring an adaptable technical platform.

DISCUSSION

Results revealed support for decentralized implementations because they carry less implementation and engagement challenges than centralized ones. Simultaneously, due to decentralized systems' interoperability issues, federated implementations (with a set of national standards) might be preferable.

CONCLUSION

This study identifies the primary socio-technical, legal, and ethical factors that challenge and contribute to the success of eHealth system implementations. This study also describes the complexities and characteristics of existing eHealth implementation programs, and suggests guidance for resolving the identified challenges.

Digital Contact Tracing Against COVID-19 in Europe: Current Features and Ongoing Developments

The SARS-CoV-2 pandemic is a public health challenge of unprecedented scale. In the midst of the first wave of the pandemic, governments worldwide introduced digital contact tracing systems as part of a strategy to contain the spread of the virus. In Europe, after intense discussion about privacy-related risks involving policymakers, technology experts, information technology companies, and—albeit to a limited extent—the public at large, technical protocols were created to support the development of privacy-compatible proximity tracing apps. However, as the second wave of SARS-CoV-2 sweeps the continent, digital contact tracing in Europe is evolving in terms of both technological and governance features. To enable policymakers to harness the full potential of digital health tools against SARS-CoV-2, this paper examines the evolution of digital contact tracing in eight European countries. Our study highlights that while privacy and data protection are at the core of contact tracing apps in Europe, countries differ in their technical protocols, and in their capacity to utilize collected data beyond proximity tracing alone. In particular, the most recently released apps tend to offer users more granular information about risk in specific locations, and to collect data about user whereabouts, in order to enhance retrospective contact tracing capacity. These developments signal a shift from a strict interpretation of data minimization and purpose limitation toward a more expansive approach to digital contact tracing in Europe, calling for careful scrutiny and appropriate oversight.

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

BACKGROUND

Ethics review is the process of assessing the ethics of research involving humans. The Ethics Review Committee (ERC) is the key oversight mechanism designated to ensure ethics review. Whether or not this governance mechanism is still fit for purpose in the data-driven research context remains a debated issue among research ethics experts.

MAIN TEXT

In this article, we seek to address this issue in a twofold manner. First, we review the strengths and weaknesses of ERCs in ensuring ethical oversight. Second, we map these strengths and weaknesses onto specific challenges raised by big data research. We distinguish two categories of potential weakness. The first category concerns persistent weaknesses, i.e., those which are not specific to big data research, but may be exacerbated by it. The second category concerns novel weaknesses, i.e., those which are created by and inherent to big data projects. Within this second category, we further distinguish between purview weaknesses related to the ERC's scope (e.g., how big data projects may evade ERC review) and functional weaknesses, related to the ERC's way of operating. Based on this analysis, we propose reforms aimed at improving the oversight capacity of ERCs in the era of big data science.

CONCLUSIONS

We believe the oversight mechanism could benefit from these reforms because they will help to overcome data-intensive research challenges and consequently benefit research at large.

Qualitative analysis of visual risk communication on twitter during the Covid-19 pandemic

BACKGROUND

The Covid-19 pandemic is characterized by uncertainty and constant change, forcing governments and health authorities to ramp up risk communication efforts. Consequently, visuality and social media platforms like Twitter have come to play a vital role in disseminating prevention messages widely. Yet to date, only little is known about what characterizes visual risk communication during the Covid-19 pandemic. To address this gap in the literature, this study's objective was to determine how visual risk communication was used on Twitter to promote the World Health Organisations (WHO) recommended preventative behaviours and how this communication changed over time.

METHODS

We sourced Twitter's 500 most retweeted Covid-19 messages for each month from January-October 2020 using Crowdbreaks. For inclusion, tweets had to have visuals, be in English, come from verified accounts, and contain one of the keywords 'covid19', 'coronavirus', 'corona', or 'covid'. Following a retrospective approach, we then performed a qualitative content analysis of the 616 tweets meeting inclusion criteria.

RESULTS

Our results show communication dynamics changed over the course of the pandemic. At the start, most retweeted preventative messages came from the media and health and government institutions, but overall, personal accounts with many followers (51.3%) predominated, and their tweets had the highest spread (10.0%, i.e., retweet count divided by followers). Messages used mostly photographs and images were found to be rich with information. 78.1% of Tweets contained 1-2 preventative messages, whereby 'stay home' and 'wear a mask' frequented most. Although more tweets used health loss framing, health gain messages spread more.

CONCLUSION

Our findings can inform the didactics of future crisis communication. The results underscore the value of engaging individuals, particularly influencers, as advocates to spread health risk messages and promote solidarity. Further, our findings on the visual characteristic of the most retweeted tweets highlight factors that health and government organisations should consider when creating visual health messages for Twitter. However, that more tweets used the emotive medium of photographs often combined with health loss framing raises concerns about persuasive tactics. More research is needed to understand the implications of framing and its impact on public perceptions and behaviours.

Public willingness to participate in personalized health research and biobanking: A large-scale Swiss survey

This paper reports survey findings on the Swiss public's willingness, attitudes, and concerns regarding personalized health research participation by providing health information and biological material. The survey reached a sample of 15,106 Swiss residents, from which we received 5,156 responses (34.1% response rate). The majority of respondents were aware of research using human biological samples (71.0%) and held a positive opinion towards this type of research (62.4%). Of all respondents, 53.6% indicated that they would be willing to participate in a personalized health research project. Willingness to participate was higher in younger, higher educated, non-religious respondents with a background in the health sector. Respondents were more willing to provide 'traditional' types of health data, such as health questionnaires, blood or biological samples, as opposed to social media or app-related data. All respondents valued the return of individual research results, including risk for diseases for which no treatment is available. Our findings highlight that alongside general positive attitudes towards personalized health research using data and samples, respondents have concerns about data privacy and re-use. Concerns included potential discrimination, confidentiality breaches, and misuse of data for commercial or marketing purposes. The findings of this large-scale survey can inform Swiss research institutions and assist policymakers with adjusting practices and developing policies to better meet the needs and preferences of the public. Efforts in this direction could focus on research initiatives engaging in transparent communication, education, and engagement activities, to increase public understanding and insight into data sharing activities, and ultimately strengthen personalized health research efforts.

Revolutionizing Medical Data Sharing Using Advanced Privacy-Enhancing Technologies: Technical, Legal, and Ethical Synthesis

Multisite medical data sharing is critical in modern clinical practice and medical research. The challenge is to conduct data sharing that preserves individual privacy and data utility. The shortcomings of traditional privacy-enhancing technologies mean that institutions rely upon bespoke data sharing contracts. The lengthy process and administration induced by these contracts increases the inefficiency of data sharing and may disincentivize important clinical treatment and medical research. This paper provides a synthesis between 2 novel advanced privacy-enhancing technologies-homomorphic encryption and secure multiparty computation (defined together as multiparty homomorphic encryption). These privacy-enhancing technologies provide a mathematical guarantee of privacy, with multiparty homomorphic encryption providing a performance advantage over separately using homomorphic encryption or secure multiparty computation. We argue multiparty homomorphic encryption fulfills legal requirements for medical data sharing under the European Union's General Data Protection Regulation which has set a global benchmark for data protection. Specifically, the data processed and shared using multiparty homomorphic encryption can be considered anonymized data. We explain how multiparty homomorphic encryption can reduce the reliance upon customized contractual measures between institutions. The proposed approach can accelerate the pace of medical research while offering additional incentives for health care and research institutes to employ common data interoperability standards.

Digital contact-tracing during the Covid-19 pandemic: An analysis of newspaper coverage in Germany, Austria, and Switzerland

Governments around the globe have started to develop and deploy digital contact tracing apps to gain control over the spread of the novel coronavirus (Covid-19). The appropriateness and usefulness of these technologies as a containment measure have since sparked political and academic discussions globally. The present paper contributes to this debate through an exploration of how the national daily newspapers in Germany, Austria, and Switzerland reported on the development and adoption of digital contact-tracing apps during early and after stages of the lockdown. These countries were among the first in Europe to develop apps and were critical voices in the debate of decentralized vs. centralized data processing. We conducted thematic analysis on news coverage published between January and May 2020 in high-circulation national daily newspapers from Germany, Austria, and Switzerland. A total of 148 articles from nine newspaper companies were included in the final analysis. From our analysis emerged six core themes of the development and adoption of digital contact tracing apps: 1) data governance; 2) role of IT giants; 3) scientific rigor; 4) voluntariness; 5) functional efficacy; 6) role of the app. These results shed light on the different facets of discussion regarding digital contact tracing as portrayed in German-speaking media. This study complements emerging survey data on public perceptions of digital contact tracing apps by providing a better understanding of the ideas circulating in the media ecosystem.

Combining the best interest standard with shared decision-making in paediatrics-introducing the shared optimum approach based on a qualitative study

Paediatric decision-making is the art of respecting the interests of child and family with due regard for evidence, values and beliefs, reconciled using two important but potentially conflicting concepts: best interest standard (BIS) and shared decision-making (SD-M). We combine qualitative research, our own data and the normative framework of the United Nations Convention on the Rights of Children (UNCRC) to revisit current theoretical debate on the interrelationship of BIS and SD-M. Three cohorts of child, parent and health care professional interviewees (N_total = 47) from Switzerland and the United States considered SD-M an essential part of the BIS. Their responses combined with the UNCRC text to generate a coherent framework which we term the shared optimum approach (SOA) combining BIS and SD-M. The SOA separates different tasks (limiting harm, showing respect, defining choices and implementing plans) into distinct dimensions and steps, based on the principles of participation, provision and protection. The results of our empirical study call into question reductive approaches to the BIS, as well as other stand-alone decision-making concepts such as the harm principle or zone of parental discretion.Conclusion: Our empirical study shows that the BIS includes a well-founded harm threshold combined with contextual information based on SD-M. We propose reconciling BIS and SD-M within the SOA as we believe this will improve paediatric decision-making. What is Known: • Parents have wide discretion in deciding for their child in everyday life, while far-reaching treatment decisions should align with the child's best interest. • Shared decision-making harbours potential conflict between parental authority and a child's best interest. What is New: • The best interest standard should not be used narrowly as a way of saying "Yes" or "No" to a specific action, but rather in a coherent framework and process which we term the shared optimum approach. • By supporting this child-centred and family-oriented process, shared decision-making becomes crucial in implementing the best interest standard.

Heritable Human Genome Editing: The Public Engagement Imperative

In the view of many, heritable human genome editing (HHGE) harbors the remedial potential of ridding the world of deadly genetic diseases. A Hippocratic obligation, if there ever was one, HHGE is widely viewed as a life-sustaining proposition. The national go/no-go decision regarding the implementation of HHGE, however, must not, in the collective view of the authors, proceed absent thorough public engagement. A comparable call for an "extensive societal dialogue" was recently issued by the International Commission on the Clinical Use of Human Germline Genome Editing. In this communication, the authors lay out the foundational principles undergirding the formation, modification, and evaluation of public opinion. It is against this backdrop that the societal decision to warrant or enjoin the clinical conduct of HHGE will doubtlessly transpire.

Early evidence of effectiveness of digital contact tracing for SARS-CoV-2 in Switzerland

In the wake of the pandemic of coronavirus disease 2019 (COVID-19), contact tracing has become a key element of strategies to control the spread of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Given the rapid and intense spread of SARS-CoV-2, digital contact tracing has emerged as a potential complementary tool to support containment and mitigation efforts. Early modelling studies highlighted the potential of digital contact tracing to break transmission chains, and Google and Apple subsequently developed the Exposure Notification (EN) framework, making it available to the vast majority of smartphones. A growing number of governments have launched or announced EN-based contact tracing apps, but their effectiveness remains unknown. Here, we report early findings of the digital contact tracing app deployment in Switzerland. We demonstrate proof-of-principle that digital contact tracing reaches exposed contacts, who then test positive for SARS-CoV-2. This indicates that digital contact tracing is an effective complementary tool for controlling the spread of SARS-CoV-2. Continued technical improvement and international compatibility can further increase the efficacy, particularly also across country borders.

Reporting Genetic Findings to Individual Research Participants: Guidelines From the Swiss Personalized Health Network

In 2017 the Swiss federal government established the Swiss Personalized Health Network (SPHN), a nationally coordinated data infrastructure for genetic research. The SPHN advisory group on Ethical, Legal, and Social Implications (ELSI) was tasked with the creation of a recommendation to ensure ethically responsible reporting of genetic research findings to research participants in SPHN-funded studies. Following consultations with expert stakeholders, including geneticists, pediatricians, sociologists, university hospitals directors, patient representatives, consumer protection associations, and insurers, the ELSI advisory group issued its recommendation on "Reporting actionable genetic findings to research participants" in May 2020. In this paper we outline the development of this recommendation and the provisions it contains. In particular, we discuss some of its key features, namely: (1) that participation in SPHN-funded studies as a research subject is conditional to accepting that medically relevant genetic research findings will be reported; (2) that a Multidisciplinary Expert Panel (MEP) should be created to support researchers' decision-making processes about reporting individual genetic research findings; (3) that such Multidisciplinary Expert Panel will make case-by-case decisions about whether to allow reporting of genetic findings, instead of relying on a pre-defined list of medically relevant variants; (4) that research participants shall be informed of the need to disclose genetic mutations when applying for private insurance, which may influence individual decisions about participation in research. By providing an account of the procedural background and considerations leading to the SPHN recommendation on "Reporting actionable genetic findings to research participants," we seek to promote a better understanding of the proposed guidance, as well as to contribute to the global dialog on the reporting of genetic research findings.

Explainability for artificial intelligence in healthcare: a multidisciplinary perspective

BACKGROUND

Explainability is one of the most heavily debated topics when it comes to the application of artificial intelligence (AI) in healthcare. Even though AI-driven systems have been shown to outperform humans in certain analytical tasks, the lack of explainability continues to spark criticism. Yet, explainability is not a purely technological issue, instead it invokes a host of medical, legal, ethical, and societal questions that require thorough exploration. This paper provides a comprehensive assessment of the role of explainability in medical AI and makes an ethical evaluation of what explainability means for the adoption of AI-driven tools into clinical practice.

METHODS

Taking AI-based clinical decision support systems as a case in point, we adopted a multidisciplinary approach to analyze the relevance of explainability for medical AI from the technological, legal, medical, and patient perspectives. Drawing on the findings of this conceptual analysis, we then conducted an ethical assessment using the "Principles of Biomedical Ethics" by Beauchamp and Childress (autonomy, beneficence, nonmaleficence, and justice) as an analytical framework to determine the need for explainability in medical AI.

RESULTS

Each of the domains highlights a different set of core considerations and values that are relevant for understanding the role of explainability in clinical practice. From the technological point of view, explainability has to be considered both in terms how it can be achieved and what is beneficial from a development perspective. When looking at the legal perspective we identified informed consent, certification and approval as medical devices, and liability as core touchpoints for explainability. Both the medical and patient perspectives emphasize the importance of considering the interplay between human actors and medical AI. We conclude that omitting explainability in clinical decision support systems poses a threat to core ethical values in medicine and may have detrimental consequences for individual and public health.

CONCLUSIONS

To ensure that medical AI lives up to its promises, there is a need to sensitize developers, healthcare professionals, and legislators to the challenges and limitations of opaque algorithms in medical AI and to foster multidisciplinary collaboration moving forward.

Public involvement in the governance of population-level biomedical research: unresolved questions and future directions

Population-level biomedical research offers new opportunities to improve population health, but also raises new challenges to traditional systems of research governance and ethical oversight. Partly in response to these challenges, various models of public involvement in research are being introduced. Yet, the ways in which public involvement should meet governance challenges are not well understood. We conducted a qualitative study with 36 experts and stakeholders using the World Café method to identify key governance challenges and explore how public involvement can meet these challenges. This brief report discusses four cross-cutting themes from the study: the need to move beyond individual consent; issues in benefit and data sharing; the challenge of delineating and understanding publics; and the goal of clarifying justifications for public involvement. The report aims to provide a starting point for making sense of the relationship between public involvement and the governance of population-level biomedical research, showing connections, potential solutions and issues arising at their intersection. We suggest that, in population-level biomedical research, there is a pressing need for a shift away from conventional governance frameworks focused on the individual and towards a focus on collectives, as well as to foreground ethical issues around social justice and develop ways to address cultural diversity, value pluralism and competing stakeholder interests. There are many unresolved questions around how this shift could be realised, but these unresolved questions should form the basis for developing justificatory accounts and frameworks for suitable collective models of public involvement in population-level biomedical research governance.

Big Data, Biomedical Research, and Ethics Review: New Challenges for IRBs

The increased use of big data in the medical field has shifted the way in which biomedical research is designed and carried out. The novelty of techniques and methods brought by big data research brings new challenges to institutional review boards (IRBs). Yet it is unclear if IRBs should be the responsible oversight bodies for big data research and, if so, which criteria they should use. A large but heterogenous set of ethics guidelines and normative responses have emerged to address these issues. In this study, we conducted a scoping review of soft-law documents and guidelines with the aim of assessing ongoing normative efforts that are proliferating in this domain. We also synthesize a set of recurrent guidelines that could work as a baseline to create a harmonized process for big data research ethics.

Assessing Public Opinion on CRISPR-Cas9: Combining Crowdsourcing and Deep Learning

Background

The discovery of the CRISPR-Cas9–based gene editing method has opened unprecedented new potential for biological and medical engineering, sparking a growing public debate on both the potential and dangers of CRISPR applications. Given the speed of technology development and the almost instantaneous global spread of news, it is important to follow evolving debates without much delay and in sufficient detail, as certain events may have a major long-term impact on public opinion and later influence policy decisions.

Objective

Social media networks such as Twitter have shown to be major drivers of news dissemination and public discourse. They provide a vast amount of semistructured data in almost real-time and give direct access to the content of the conversations. We can now mine and analyze such data quickly because of recent developments in machine learning and natural language processing.

Methods

Here, we used Bidirectional Encoder Representations from Transformers (BERT), an attention-based transformer model, in combination with statistical methods to analyze the entirety of all tweets ever published on CRISPR since the publication of the first gene editing application in 2013.

Results

We show that the mean sentiment of tweets was initially very positive, but began to decrease over time, and that this decline was driven by rare peaks of strong negative sentiments. Due to the high temporal resolution of the data, we were able to associate these peaks with specific events and to observe how trending topics changed over time.

Conclusions

Overall, this type of analysis can provide valuable and complementary insights into ongoing public debates, extending the traditional empirical bioethics toolset.

The Mobile Health App Trustworthiness Checklist: Usability Assessment

BACKGROUND

The mobile health (mHealth) app trustworthiness (mHAT) checklist was created to identify end users' opinions on the characteristics of trustworthy mHealth apps and to communicate this information to app developers. To ensure that the checklist is suited for all relevant stakeholders, it is necessary to validate its contents.

OBJECTIVE

The purpose of this study was to assess the feasibility of the mHAT checklist by modifying its contents according to ratings and suggestions from stakeholders familiar with the process of developing, managing, or curating mHealth apps.

METHODS

A 44-item online survey was administered to relevant stakeholders. The survey was largely comprised of the mHAT checklist items, which respondents rated on a 5-point Likert scale, ranging from completely disagree (1) to completely agree (5).

RESULTS

In total, seven professional backgrounds were represented in the survey: administrators (n=6), health professionals (n=7), information technology personnel (n=6), managers (n=2), marketing personnel (n=3), researchers (n=5), and user experience researchers (n=8). Aside from one checklist item-"the app can inform end users about errors in measurements"-the combined positive ratings (ie, completely agree and agree) of the checklist items overwhelmingly exceeded the combined negative ratings (ie, completely disagree and disagree). Meanwhile, two additional items were included in the checklist: (1) business or funding model of the app and (2) details on app uninstallation statistics.

CONCLUSIONS

Our results indicate that the mHAT checklist is a valuable resource for a broad range of stakeholders to develop trustworthy mHealth apps. Future studies should examine if the checklist works best for certain mHealth apps or in specific settings.

Digital tools against COVID-19: taxonomy, ethical challenges, and navigation aid

Data collection and processing via digital public health technologies are being promoted worldwide by governments and private companies as strategic remedies for mitigating the COVID-19 pandemic and loosening lockdown measures. However, the ethical and legal boundaries of deploying digital tools for disease surveillance and control purposes are unclear, and a rapidly evolving debate has emerged globally around the promises and risks of mobilising digital tools for public health. To help scientists and policy makers to navigate technological and ethical uncertainty, we present a typology of the primary digital public health applications that are in use. These include proximity and contact tracing, symptom monitoring, quarantine control, and flow modelling. For each, we discuss context-specific risks, cross-sectional issues, and ethical concerns. Finally, recognising the need for practical guidance, we propose a navigation aid for policy makers and other decision makers for the ethical development and use of digital public health tools.

"Hunting Down My Son's Killer": New Roles of Patients in Treatment Discovery and Ethical Uncertainty

The past few years have witnessed several media-covered cases involving citizens actively engaging in the pursuit of experimental treatments for their medical conditions-or those of their loved ones-in the absence of established standards of therapy. This phenomenon is particularly observable in patients with rare genetic diseases, as the development of effective therapies for these disorders is hindered by the limited profitability and market value of pharmaceutical research. Sociotechnical trends at the cross-section of medicine and society are facilitating the involvement of patients and creating the digital infrastructure necessary to its sustainment. Such participant-led research (PLR) has the potential to promote the autonomy of research participants as drivers of discovery and to open novel non-canonical avenues of scientific research. At the same time, however, the extra-institutional, self-appointed, and, often, oversight-free nature of PLR raises ethical concern. This paper explores the complex ethical entanglement of PLR by critically appraising case studies and discussing the conditions for its moral justification. Furthermore, we propose a path forward to ensure the safe and effective implementation of PLR within the current research ecosystem in a manner that maximizes the benefits for both individual participants and society at large, while minimizing the risks.