Secondary Use of Health Data for Medical AI: A Cross-Regional Examination of Taiwan and the EU.

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

Normative challenges in data governance: insights from global health research.

Many important questions in health professions education require datasets that are built from several sources, in some cases using data collected for a different purpose. In building and maintaining these datasets, project leaders will need to make decisions about the data. While such decisions are often construed as technical, there are several normative concerns, such as who should have access, how the data will be used, how products resulting from the data will be shared, and how to ensure privacy of the individuals the data is about is respected, etc. Establishing a framework for data governance can help project leaders in avoiding problems, related to such matters, that could limit what can be learned from the data or that might put the project (or future projects) at risk. In this paper, we highlight several normative challenges to be addressed when determining a data governance framework. Drawing from lessons in global health, we illustrate three kinds of normative challenges for projects that rely on data from multiple sources or involved partnerships across institutions or jurisdictions: (1) legal and regulatory requirements, (2) consent, and (3) equitable sharing and fair distribution.

Unveiling value patterns via deep reinforcement learning in heterogeneous data analytics.

Artificial intelligence has substantially improved the efficiency of data utilization across various sectors. However, the insufficient filtering of low-quality data poses challenges to uncertainty management, threatening system stability. In this study, we introduce a data-valuation approach employing deep reinforcement learning to elucidate the value patterns in data-driven tasks. By strategically optimizing with iterative sampling and feedback, our method is effective in diverse scenarios and consistently outperforms the classic methods in both accuracy and efficiency. In China's wind-power prediction, excluding 25% of the overall dataset deemed low-value led to a 10.5% improvement in accuracy. Utilizing just 42.8% of the dataset, the model discerned 80% of linear patterns, showcasing the data's intrinsic and transferable value. A nationwide analysis identified a data-value-sensitive geographic belt across 10 provinces, leading to robust policy recommendations informed by variances in power outputs and data values, as well as geographic climate factors.

Cross-border data sharing for research in Africa: An analysis of the data protection and research ethics requirements in 12 jurisdictions.

Background: In recent years, there has been a notable uptake in genomic and health-related research activities across the African continent. Similarly, there has been increased introduction of data protection legislation that affects the sharing of personal data such as health data and genomic data, including for research. Many of these statutes have stricter requirements when sharing personal data across borders. Consequently, the cross-border sharing of health data that includes genetic data requires careful navigation of the pertinent data protection legislation, in particular concerning the sharing of such data for research purposes. To help researchers navigate these legal frameworks, 12 African countries were analysed to develop country guides on cross-border data sharing. Results: Of the 12 countries that were analysed, ten have data protection laws in place (Botswana, Ghana, Kenya, Malawi, Nigeria, Rwanda, South Africa, Tanzania, Uganda, and Zimbabwe), while two countries (Cameroon and The Gambia) do not. With the exception of Ghana, all countries with data protection statutes or bills had additional requirements to be met when sharing personal data across borders. Consent and adequacy are the most common grounds for justifying the sharing of personal data across borders. Conclusion: Given the limitations of the current models of consent, consent is not a suitable basis to transfer large quantities of data for research. Adequacy is a common ground, but there are national differences in the implementation of this ground. Researchers must therefore analyse each national legal framework and make decisions on a case-by-case and country-by-country basis.

Balancing Protection and Quality in Big Data Analytics Pipelines.

Existing data engine implementations do not properly manage the conflict between the need of protecting and sharing data, which is hampering the spread of big data applications and limiting their impact. These two requirements have often been studied and defined independently, leading to a conceptual and technological misalignment. This article presents the architecture and technical implementation of a data engine addressing this conflict by integrating a new governance solution based on access control within a big data analytics pipeline. Our data engine enriches traditional components for data governance with an access control system that enforces access to data in a big data environment based on data transformations. Data are then used along the pipeline only after sanitization, protecting sensitive attributes before their usage, in an effort to facilitate the balance between protection and quality. The solution was tested in a real-world smart city scenario using the data of the Oslo city transportation system. Specifically, we compared the different predictive models trained with the data views obtained by applying the secure transformations required by different user roles to the same data set. The results show that the predictive models, built on data manipulated according to access control policies, are still effective.

Ethical and Equitable Digital Health Research: Ensuring Self-Determination in Data Governance for Racialized Communities.

Recent studies highlight the need for ethical and equitable digital health research that protects the rights and interests of racialized communities. We argue for practices in digital health that promote data self-determination for these communities, especially in data collection and management. We suggest that researchers partner with racialized communities to curate data that reflects their wellness understandings and health priorities, and respects their consent over data use for policy and other outcomes. These data governance approach honors and builds on Indigenous Data Sovereignty (IDS) decolonial scholarship by Indigenous and non-indigenous researchers and its adaptations to health research involving racialized communities from former European colonies in the global South. We discuss strategies to practice equity, diversity, inclusion, accessibility and decolonization (EDIAD) principles in digital health. We draw upon and adapt the concept of Precision Health Equity (PHE) to emphasize models of data sharing that are co-defined by racialized communities and researchers, and stress their shared governance and stewardship of data that is generated from digital health research. This paper contributes to an emerging research on equity issues in digital health and reducing health, institutional, and technological disparities. It also promotes the self-determination of racialized peoples through ethical data management.

Adoption of routine surgical video recording: a nationwide freedom of information act request across England and Wales.

Background: Surgical video contains data with significant potential to improve surgical outcome assessment, quality assurance, education, and research. Current utilisation of surgical video recording is unknown and related policies/governance structures are unclear. Methods: A nationwide Freedom of Information (FOI) request concerning surgical video recording, technology, consent, access, and governance was sent to all acute National Health Service (NHS) trusts/boards in England/Wales between 20th February and 20th March 2023. Findings: 140/144 (97.2%) trusts/boards in England/Wales responded to the FOI request. Surgical procedures were routinely recorded in 22 trusts/boards. The median estimate of consultant surgeons routinely recording their procedures was 20%. Surgical video was stored on internal systems (n = 27), third-party products (n = 29), and both (n = 9). 32/140 (22.9%) trusts/boards ask for consent to record procedures as part of routine care. Consent for recording included non-clinical purposes in 55/140 (39.3%) trusts/boards. Policies for surgeon/patient access to surgical video were available in 48/140 (34.3%) and 32/140 (22.9%) trusts/boards, respectively. Surgical video was used for non-clinical purposes in 64/140 (45.7%) trusts/boards. Governance policies covering surgical video recording, use, and/or storage were available from 59/140 (42.1%) trusts/boards. Interpretation: There is significant heterogeneity in surgical video recording practices in England and Wales. A minority of trusts/boards routinely record surgical procedures, with large variation in recording/storage practices indicating scope for NHS-wide coordination. Revision of surgical video consent, accessibility, and governance policies should be prioritised by trusts/boards to protect key stakeholders. Increased availability of surgical video is essential for patients and surgeons to maximally benefit from the ongoing digital transformation of surgery. Funding: KL is supported by an NIHR Academic Clinical Fellowship and acknowledges infrastructure support for this research from the National Institute for Health Research (NIHR) Imperial Biomedical Research Centre (BRC).

Unconventional data, unprecedented insights: leveraging non-traditional data during a pandemic.

Introduction: The COVID-19 pandemic prompted new interest in non-traditional data sources to inform response efforts and mitigate knowledge gaps. While non-traditional data offers some advantages over traditional data, it also raises concerns related to biases, representativity, informed consent and security vulnerabilities. This study focuses on three specific types of non-traditional data: mobility, social media, and participatory surveillance platform data. Qualitative results are presented on the successes, challenges, and recommendations of key informants who used these non-traditional data sources during the COVID-19 pandemic in Spain and Italy. Methods: A qualitative semi-structured methodology was conducted through interviews with experts in artificial intelligence, data science, epidemiology, and/or policy making who utilized non-traditional data in Spain or Italy during the pandemic. Questions focused on barriers and facilitators to data use, as well as opportunities for improving utility and uptake within public health. Interviews were transcribed, coded, and analyzed using the framework analysis method. Results: Non-traditional data proved valuable in providing rapid results and filling data gaps, especially when traditional data faced delays. Increased data access and innovative collaborative efforts across sectors facilitated its use. Challenges included unreliable access and data quality concerns, particularly the lack of comprehensive demographic and geographic information. To further leverage non-traditional data, participants recommended prioritizing data governance, establishing data brokers, and sustaining multi-institutional collaborations. The value of non-traditional data was perceived as underutilized in public health surveillance, program evaluation and policymaking. Participants saw opportunities to integrate them into public health systems with the necessary investments in data pipelines, infrastructure, and technical capacity. Discussion: While the utility of non-traditional data was demonstrated during the pandemic, opportunities exist to enhance its impact. Challenges reveal a need for data governance frameworks to guide practices and policies of use. Despite the perceived benefit of collaborations and improved data infrastructure, efforts are needed to strengthen and sustain them beyond the pandemic. Lessons from these findings can guide research institutions, multilateral organizations, governments, and public health authorities in optimizing the use of non-traditional data.

Comparing Attitudes Toward Different Consent Mediums: Semistructured Qualitative Study.

BACKGROUND: As consent for data sharing evolves with the digital age, plain-text consent is not the only format in which information can be presented. However, designing a good consent form is highly challenging. The addition of graphics, video, and other mediums to use can vary widely in effectiveness; and improper use can be detrimental to users. OBJECTIVE: This study aims to explore the expectations and experiences of adults toward consent given in infographic, video, text, newsletter, and comic forms in a health data sharing scenario to better understand the appropriateness of different mediums and identify elements of each medium that most affect engagement with the content. METHODS: We designed mock consent forms in infographic, video, text, newsletter, and comic versions. Semistructured interviews were conducted with adults who were interviewed about their expectations for consent and were then shown each consent medium and asked about engaging elements across mediums, preferences for consent mediums, and the value of document quality criteria. We transcribed and qualitatively co-coded to identify themes and perform analyses. RESULTS: We interviewed 24 users and identified different thematic archetypes based on participant goals, such as the Trust Seeker, who considered their own understanding and trust in organizations when making decisions. The infographic was ranked first for enhancing understanding, prioritizing information, and maintaining the proper audience fit for serious consent in health data sharing scenarios. In addition, specific elements such as structure, step-by-step organization, and readability were preferred engaging elements. CONCLUSIONS: We identified archetypes to better understand user needs and elements that can be targeted to enhance user engagement with consent forms; this can help inform the design of more effective consent in the future. Overall, preferences for mediums are highly contextual, and more research should be done.

Digital twins in sustainable transition: exploring the role of EU data governance.

Introduction: Digital twins can accelerate sustainable development by leveraging big data and artificial intelligence to simulate state, reactions and potential developments of physical systems. In doing so, they can create a comprehensive basis for data-driven policy decisions. One of the purposes of digital twins is to facilitate the implementation of the EU's Green Deal-in line with internationally binding climate and environmental targets. One prerequisite for the success of digital twins is a comprehensive, high-quality database. This requires a suitable legal framework that ensures access to such data. Methods: Applying a qualitative governance analysis, the following article examines if the EU's strategies and legal acts on data governance are paving the way for digital twin projects which promote sustainability. Results: Results show important starting points for open and fair data use within the growing field of EU digital law. However, there is still a lot of progress to be made to legally link the use of digital twins with binding sustainability objectives.

Personal data store ecosystems in health and social care.

This paper considers how the development of personal data store ecosystems in health and social care may offer one person-centered approach to improving the ways in which individual generated and gathered data-e.g., from wearables and other personal monitoring and tracking devices-can be used for wellbeing, individual care, and research. Personal data stores aim to provide safe and secure digital spaces that enable people to self-manage, use, and share personal data with others in a way that aligns with their individual needs and preferences. A key motivation for personal data stores is to give an individual more access and meaningful control over their personal data, and greater visibility over how it is used by others. This commentary discusses meanings and motivations behind the personal data store concept-examples are provided to illustrate the opportunities such ecosystems can offer in health and social care, and associated research and implementation challenges are also examined.

Towards a Unified Framework for Information and Interoperability Governance.

Challenges in health data interoperability have highlighted overall health care system inefficiencies. Many organizations struggle to establish a robust data governance infrastructure to meet the increasing demands of advanced data uses, let alone sharing it with a large number of other organizations. There is a need for health care organizations to adopt information governance frameworks that encapsulates interoperability as a core attribute as this can improve data processing, knowledge translation and participation in the larger health data ecosystem. To establish interoperability between healthcare organizations, standards must exist in relation to how information is governed and circulates in the healthcare system, not just on how it is structured, stored and used within an organization. In this paper we demonstrate that interoperability between organizations cannot coherently exist without consideration of information governance within organizations. Lack of coherence can lead to lack of data accessibility, decreased organizational efficiencies, and poor data quality. With this in mind, we propose a unified framework that integrates the principles of both information and interoperability governance to increase the adaptability, flexibility, and efficiency of health information usage across the entire healthcare system.

National Regulation on Processing Data for Scientific Research Purposes and Biobanking Activities: Reflections on the Experience in Austria.

The application of the latest technologies in biology and medicine has brought them to a qualitatively new level of possibilities. Worldwide, biobanking is actively developing through the creation of biobanks of various types and purposes, whose resources are used to solve therapeutic or scientific problems. Legal science remains an open question concerning the boundary that runs between the right to data protection and the scope of disclosure of data needed for medical purposes. In this article, the author considers peculiarities of data processing in the context of biobanking activity on the example of Austria and its national legislation. In addition, the article reveals features of the approaches of the European Court of Human Rights (ECtHR) and the Council of Europe to the issue of biobanking in general, its characteristics in the context of data, and legal regulation of this phenomenon in the national law of states. The author devoted an important part of the study to the role of Austria's experience in the context of data processing for scientific purposes and the development of biobanking for a number of other European states. The aim of the article is to analyze the Austrian legislation on data processing for scientific research and biobanking, the attitude of the Council of Europe to this phenomenon, and the practice of the ECtHR, as well as to consider the impact of the current world situation on these activities. The leading method of research used in the article is the formal-legal method. The article analyzes the Austrian law in the context of data processing in medical research, the relationship of the specifics of personal data protection, and the need to disclose them for scientific purposes. The author pays special attention to the influence of Austrian law on the legislation of other countries, which is reflected in the conclusions to the article. In addition, based on an analysis of the application of the Austrian experience to the legislation of Poland and Ukraine, the author points out the necessary changes that should be made in the laws of these countries.

The regulation of health data sharing in Africa: a comparative study.

The sharing of health data is an essential component in the provision of healthcare, in medical research, and disease surveillance. Health data sharing is subject to regulatory frameworks that vary across jurisdictions. In Africa, numerous factors complicate the regulation of health data sharing, including technological, motivational, economic, and political barriers, as well as ethical and legal challenges. This comparative study examines the regulation of health data sharing in Africa by comparing and contrasting the legal and policy frameworks of five African countries. The study identifies gaps and inconsistencies in the current regulatory regimes and provides recommendations for improving the regulation of health data sharing in Africa.

Delivering Digital Health Solutions that Patients Need: A Call to Action.

Digital health solutions have the potential to complement traditional healthcare approaches and deliver improved health outcomes, but there are system-wide challenges that need to be addressed. These include fragmentation of the digital health landscape, regulatory processes that lack the agility to accommodate the fast pace of digital health advances, and inadequate transparency around data sharing and data governance. All of these challenges have led to mistrust, limited understanding and sharing of best practices, a lack of digital education and awareness, and insufficient patient and public engagement and involvement. In this paper, we argue that for digital health solutions to fulfil their potential, there needs to be a significant increase in early, meaningful, and sustained engagement with the people they intend to benefit. The uptake as well as the impact of digital solutions created in partnership with patients for patients are greater and more relevant to the communities they address.

Genetic research with Indigenous Peoples: perspectives on governance and oversight in the US.

Introduction: Indigenous Peoples are increasingly exerting governance and oversight over genomic research with citizens of their nations, raising questions about how best to enforce research regulation between American Indian, Alaska Native, and Native Hawaiian peoples and researchers. Methods: Using a community-engaged research approach, we conducted 42 semi-structured interviews with Tribal leaders, clinicians, researchers, policy makers, and Tribal research review board members about their perspectives on ethical issues related to genetics research with Indigenous Peoples in the US. Results: We report findings related to (1) considerations for Indigenous governance, (2) institutional relationships upholding sovereignty, (3) expectations for research approvals, and (4) agreements enacting Indigenous governance. Participants described concerns about different ways of exerting oversight, relationships and agreements between Indigenous Peoples and researchers, and gaps that need to be addressed to strengthen existing governance of genomic data. Discussion: The results will ultimately guide policy-making and development of new strategies for Indigenous Peoples to enforce oversight in research to promote ethically and culturally appropriate research.

DATA GOVERNANCE in digital surgery.

Technological and computer advances have led to a "new era" of Surgery called Digital Surgery. In it, the management of information is the key. The development of Artificial Intelligence requires "Big Data" to create its algorithms. The use of digital technology for the systematic capture of data from the surgical process raises ethical issues of privacy, property, and consent. The use of these out-of-control data creates uncertainty and can be a source of mistrust and refusal by surgeons to allow its use, requiring a framework for the correct management of them. This paper exposes the current situation of Data Governance in Digital Surgery, the challenges posed and the lines of action necessary to resolve the areas of uncertainty that have arisen in the process, in which the surgeon must play a relevant role.

Indigenous Peoples and research: self-determination in research governance.

Indigenous Peoples are reimagining their relationship with research and researchers through greater self-determination and involvement in research governance. The emerging discourse around Indigenous Data Sovereignty has provoked discussions about decolonizing data practices and highlighted the importance of Indigenous Data Governance to support Indigenous decision-making and control of data. Given that much data are generated from research, Indigenous research governance and Indigenous Data Governance overlap. In this paper, we broaden the concept of Indigenous Data Sovereignty by using the CARE Principles for Indigenous Data Governance to discuss how research legislation and policy adopted by Indigenous Peoples in the US set expectations around recognizing sovereign relationships, acknowledging rights and interests in data, and enabling Indigenous Peoples' participation in research governance.

No longer hype, not yet mainstream? Recalibrating city digital twins' expectations and reality: a case study perspective.

While the concept of digital twin has already consolidated in industry, its spinoff in the urban environment-in the form of a City Digital Twin (CDT)-is more recent. A CDT is a dynamic digital model of the physical city whereby the physical and the digital are integrated in both directions, thus mutually affecting each other in real time. Replicating the path of smart cities, literature remarks that agendas and discourses around CDTs remain (1) tech-centered, that is, focused on overcoming technical limitations and lacking a proper sociotechnical contextualization of digital twin technologies; (2) practice-first, entailing hands-on applications without a long-term strategic governance for the management of these same technologies. Building on that, the goal of this article is to move beyond high-level conceptualizations of CDT to (a) get a cognizant understanding of what a CDT can do, how, and for whom; (b) map the current state of development and implementation of CDTs in Europe. This will be done by looking at three case studies-Dublin, Helsinki, and Rotterdam-often considered as successful examples of CDTs in Europe. Through exiting literature and official documents, as well as by relying on primary interviews with tech experts and local officials, the article explores the maturity of these CDTs, along the Gartner's hype-mainstream curve of technological innovations. Findings show that, while all three municipalities have long-term plans to deliver an integrated, cyber-physical real-time modeling of the city, currently their CDTs are still at an early stage of development. The focus remains on technical barriers-e.g., integration of different data sources-overlooking the societal dimension, such as the systematic involvement of citizens. As for the governance, all cases embrace a multistakeholder approach; yet CDTs are still not used for policymaking and it remains to see how the power across stakeholders will be distributed in terms of access to, control of, and decisions about CDTs.