A review of attitudes towards the reuse of health data among people in the European Union: The primacy of purpose and the common good

Landscape analysis of available European data sources amenable for machine learning and recommendations on usability for rare diseases screening

BACKGROUND

Patient registries and databases are essential tools for advancing clinical research in the area of rare diseases, as well as for enhancing patient care and healthcare planning. The primary aim of this study is a landscape analysis of available European data sources amenable to machine learning (ML) and their usability for Rare Diseases screening, in terms of findable, accessible, interoperable, reusable(FAIR), legal, and business considerations. Second, recommendations will be proposed to provide a better understanding of the health data ecosystem.

METHODS

In the period of March 2022 to December 2022, a cross-sectional study using a semi-structured questionnaire was conducted among potential respondents, identified as main contact person of a health-related databases. The design of the self-completed questionnaire survey instrument was based on information drawn from relevant scientific publications, quantitative and qualitative research, and scoping review on challenges in mapping European rare disease (RD) databases. To determine database characteristics associated with the adherence to the FAIR principles, legal and business aspects of database management Bayesian models were fitted.

RESULTS

In total, 330 unique replies were processed and analyzed, reflecting the same number of distinct databases (no duplicates included). In terms of geographical scope, we observed 24.2% (n = 80) national, 10.0% (n = 33) regional, 8.8% (n = 29) European, and 5.5% (n = 18) international registries coordinated in Europe. Over 80.0% (n = 269) of the databases were still active, with approximately 60.0% (n = 191) established after the year 2000 and 71.0% last collected new data in 2022. Regarding their geographical scope, European registries were associated with the highest overall FAIR adherence, while registries with regional and "other" geographical scope were ranked at the bottom of the list with the lowest proportion. Responders' willingness to share data as a contribution to the goals of the Screen4Care project was evaluated at the end of the survey. This question was completed by 108 respondents; however, only 18 of them (16.7%) expressed a direct willingness to contribute to the project by sharing their databases. Among them, an equal split between pro-bono and paid services was observed.

CONCLUSIONS

The most important results of our study demonstrate not enough sufficient FAIR principles adherence and low willingness of the EU health databases to share patient information, combined with some legislation incapacities, resulting in barriers to the secondary use of data.

Attitude towards consent-free research use of personal medical data in the general German population

Background

The design of appropriate consent procedures for the secondary use of personal health data is a key concern of current medical research. In Germany, the concept of 'data donation' has recently come into focus, defined as a legal entitlement to the research use of personal medical data without prior consent, combined with an easy-to-exercise right of the data subjects to opt-out.

Methods

Standardized online interviews of 3,013 individuals, representative of the German online population, were conducted in August 2022 to determine their attitude towards data donation for medical research.

Results

A majority of participants supported a consent-free data donation regulation, both for publicly funded (85.1%) and for private medical research (66.4%). Major predictors of a positive attitude towards data donation included (i) sufficient appreciation of the respective kind of research (i.e. public or private), (ii) a reciprocity attitude that patients who benefit from research have a duty to support research, and (iii) sufficient trust in data protection and data control.

Conclusion

People's attitude towards data donation to medical research is generally positive in Germany and depends upon factors that can be curbed by legislation and internal rules of procedure. Worthy of note, designing data donation in the form of an opt-out regulation does not necessarily mean that the paradigm of informedness has to be abandoned. Rather the process of information provision must be shifted towards the creation of basic knowledge in the general population about the risks and benefits of data-intensive medical research ('health data literacy').

Privacy concerns among the users of a national patient portal: A cross-sectional population survey study

INTRODUCTION

Seeking and receiving care requires disclosure of personal information which is recorded as health data in electronic health records. Thereafter, restricting the flow of information is dependent on data protection, information security, ethical conduct, and law. Privacy concerns may arise as patients' options concerning privacy have been balanced to cater both the privacy of patients and the needs of healthcare, as well as secondary use of data.

METHODS

This study examined privacy concerns among the users of a national patient portal in a representative sample of Finnish adults aged 20 to 99 years old (n = 3,731). We used logistic regression analysis with population weights to seek answers to which factors are associated with privacy concerns. The cross-sectional survey data was collected in 2020.

RESULTS

Every third patient portal user had privacy concerns. Those who were 50 to 59 years old (p = 0.030) had privacy concerns more often than 20 to 49-year-olds. Those who had financial difficulties (p = 0.003) also had privacy concerns more often while those, who had good digital skills (p=<0.026), did not need guidance on telehealth service use (p=<0.001) and found telehealth service use to be beneficial (p = 0.008), had privacy concerns less often.

CONCLUSION

The usefulness of telehealth seems to play an important role in privacy concerns. Another important factor is the skills required to use telehealth services. We encourage providing guidance to those who lack the necessary skills for telehealth service use. We also encourage putting effort not only into data protection and information security measures of telehealth services, but also into providing transparent and comprehensible privacy information for the service users as privacy concerns are common.

Public Preferences for Digital Health Data Sharing: Discrete Choice Experiment Study in 12 European Countries

BACKGROUND

With new technologies, health data can be collected in a variety of different clinical, research, and public health contexts, and then can be used for a range of new purposes. Establishing the public's views about digital health data sharing is essential for policy makers to develop effective harmonization initiatives for digital health data governance at the European level.

OBJECTIVE

This study investigated public preferences for digital health data sharing.

METHODS

A discrete choice experiment survey was administered to a sample of European residents in 12 European countries (Austria, Denmark, France, Germany, Iceland, Ireland, Italy, the Netherlands, Norway, Spain, Sweden, and the United Kingdom) from August 2020 to August 2021. Respondents answered whether hypothetical situations of data sharing were acceptable for them. Each hypothetical scenario was defined by 5 attributes ("data collector," "data user," "reason for data use," "information on data sharing and consent," and "availability of review process"), which had 3 to 4 attribute levels each. A latent class model was run across the whole data set and separately for different European regions (Northern, Central, and Southern Europe). Attribute relative importance was calculated for each latent class's pooled and regional data sets.

RESULTS

A total of 5015 completed surveys were analyzed. In general, the most important attribute for respondents was the availability of information and consent during health data sharing. In the latent class model, 4 classes of preference patterns were identified. While respondents in 2 classes strongly expressed their preferences for data sharing with opposing positions, respondents in the other 2 classes preferred not to share their data, but attribute levels of the situation could have had an impact on their preferences. Respondents generally found the following to be the most acceptable: a national authority or academic research project as the data user; being informed and asked to consent; and a review process for data transfer and use, or transfer only. On the other hand, collection of their data by a technological company and data use for commercial communication were the least acceptable. There was preference heterogeneity across Europe and within European regions.

CONCLUSIONS

This study showed the importance of transparency in data use and oversight of health-related data sharing for European respondents. Regional and intraregional preference heterogeneity for "data collector," "data user," "reason," "type of consent," and "review" calls for governance solutions that would grant data subjects the ability to control their digital health data being shared within different contexts. These results suggest that the use of data without consent will demand weighty and exceptional reasons. An interactive and dynamic informed consent model combined with oversight mechanisms may be a solution for policy initiatives aiming to harmonize health data use across Europe.

Survey of Public Attitudes toward the Secondary Use of Public Healthcare Data in Korea

OBJECTIVES

Public healthcare data have become crucial to the advancement of medicine, and recent changes in legal structure on privacy protection have expanded access to these data with pseudonymization. Recent debates on public healthcare data use by private insurance companies have shown large discrepancies in perceptions among the general public, healthcare professionals, private companies, and lawmakers. This study examined public attitudes toward the secondary use of public data, focusing on differences between public and private entities.

METHODS

An online survey was conducted from January 11 to 24, 2022, involving a random sample of adults between 19 and 65 of age in 17 provinces, guided by the August 2021 census.

RESULTS

The final survey analysis included 1,370 participants. Most participants were aware of health data collection (72.5%) and recent changes in legal structures (61.4%) but were reluctant to share their pseudonymized raw data (51.8%). Overall, they were favorable toward data use by public agencies but disfavored use by private entities, notably marketing and private insurance companies. Concerns were frequently noted regarding commercial use of data and data breaches. Among the respondents, 50.9% were negative about the use of public healthcare data by private insurance companies, 22.9% favored this use, and 1.9% were "very positive."

CONCLUSIONS

This survey revealed a low understanding among key stakeholders regarding digital health data use, which is hindering the realization of the full potential of public healthcare data. This survey provides a basis for future policy developments and advocacy for the secondary use of health data.

The European health data space: Too big to succeed?

In May 2022, the European Commission issued the Proposal for a Regulation on the European Health Data Space (EHDS), with the aims of granting citizens increased access to and control of their (electronic) health data across the EU, and facilitating health data re-use for research, innovation, and policymaking. As the first in a series of European domain-specific "data spaces", the EHDS is a high-stakes development that will transform health data governance in the EU region. As an international consortium of experts from health policy, law, ethics and the social sciences, we are concerned that the EHDS Proposal will detract from, rather than lead to the achievement of, its stated aims. We are in no doubt on the benefits of using health data for secondary purposes, and we appreciate attempts to facilitate such uses across borders in a carefully curated manner. Based on the current draft Regulation, however, the EHDS risks undermining rather than enhancing patient control over data; hindering rather than facilitating the work of health professionals and researchers; and eroding rather than increasing the public value generated through health data sharing. Therefore, significant adjustments are needed if the EHDS is to realize its promised benefits. Besides analyzing the implications for key groups and European societies at large who will be affected by the implementation of the EHDS, this contribution advances targeted policy recommendations to address the identified shortcomings of the EHDS Proposal.

Record linkage as a vital key player for the COVID-19 syndemic - The call for legal harmonization to overcome research challenges

Key messages: Chronicity and social context influence COVID-19 risk highlighting its syndemic dimension Record Linkage advances knowledge on COVID-19, associated chronic diseases, and social indicators Further harmonization of data protection requirements for scientific research may create multilevel public health measures As a multidimensional tool, it optimizes integrated strategies and fosters solidarity on Health in All Policies (HiAP)

Patient perspectives on data sharing regarding implementing and using artificial intelligence in general practice - a qualitative study

BACKGROUND

Due to more elderly and patients with complex illnesses, there is an increasing pressure on the healthcare system. General practice especially feels this pressure as being the first point of contact for the patients. Developments in digitalization have undergone fast progress and data-driven artificial intelligence (AI) has shown great potential for use in general practice. To develop AI as a support tool for general practitioners (GPs), access to patients' health data is needed, but patients have concerns regarding data sharing. Furthermore, studies show that trust is important regarding the patient-GP relationship, data sharing, and AI. The aim of this paper is to uncover patient perspectives on trust regarding the patient-GP relationship, data sharing and AI in general practice.

METHOD

This study investigated 10 patients' perspectives through qualitative interviews and written vignettes were chosen to elicit the patients (interviewees) perspectives on topics that they were not familiar with prior to the interviews. The study specifically investigated perspectives on 1) The patient-GP relationship, 2) data sharing regarding developing AI for general practice, and 3) implementation and use of AI in general practice using thematic analysis. The study took place in the North Denmark Region and the interviewees included had to be registered in general practice and be above 18 years in age. We included four men between 25 to 74 years in age and six women between 27 to 46 years in age.

RESULTS

The interviewees expressed a high level of trust towards their GP and were willing to share their health data with their GP. The interviewees believed that AI could be a great help to GPs if used as a support tool in general practice. However, it was important for the interviewees that the GP would still be the primary decision maker.

CONCLUSION

Patients may be willing to share health data to help implement and use AI in general practice. If AI is implemented in a way that preserves the patient-GP relationship and used as a support tool for the GP, our results indicate that patients may be positive towards the use of AI in general practice.

Patient Perspectives and Preferences for Consent in the Digital Health Context: State-of-the-art Literature Review

BACKGROUND

The increasing integration of digital health tools into care may result in a greater flow of personal health information (PHI) between patients and providers. Although privacy legislation governs how entities may collect, use, or share PHI, such legislation has not kept pace with digital health innovations, resulting in a lack of guidance on implementing meaningful consent. Understanding patient perspectives when implementing meaningful consent is critical to ensure that it meets their needs. Consent for research in the context of digital health is limited.

OBJECTIVE

This state-of-the-art review aimed to understand the current state of research as it relates to patient perspectives on digital health consent. Its objectives were to explore what is known about the patient perspective and experience with digital health consent and provide recommendations on designing and implementing digital health consent based on the findings.

METHODS

A structured literature search was developed and deployed in 4 electronic databases-MEDLINE, IEEE Xplore, Scopus, and Web of Science-for articles published after January 2010. The initial literature search was conducted in March 2021 and updated in March 2022. Articles were eligible for inclusion if they discussed electronic consent or consent, focused on the patient perspective or preference, and were related to digital health or digital PHI. Data were extracted using an extraction template and analyzed using qualitative content analysis.

RESULTS

In total, 75 articles were included for analysis. Most studies were published within the last 5 years (58/75, 77%) and conducted in a clinical care context (33/75, 44%) and in the United States (48/75, 64%). Most studies aimed to understand participants' willingness to share PHI (25/75, 33%) and participants' perceived usability and comprehension of an electronic consent notice (25/75, 33%). More than half (40/75, 53%) of the studies did not describe the type of consent model used. The broad open consent model was the most explored (11/75, 15%). Of the 75 studies, 68 (91%) found that participants were willing to provide consent; however, their consent behaviors and preferences were context-dependent. Common patient consent requirements included clear and digestible information detailing who can access PHI, for what purpose their PHI will be used, and how privacy will be ensured.

CONCLUSIONS

There is growing interest in understanding the patient perspective on digital health consent in the context of providing clinical care. There is evidence suggesting that many patients are willing to consent for various purposes, especially when there is greater transparency on how the PHI is used and oversight mechanisms are in place. Providing this transparency is critical for fostering trust in digital health tools and the innovative uses of data to optimize health and system outcomes.

Use of the Hashtag #DataSavesLives on Twitter: Exploratory and Thematic Analysis

Background

“Data Saves Lives” is a public engagement campaign that highlights the benefits of big data research and aims to establish public trust for this emerging research area.

Objective

This study explores how the hashtag #DataSavesLives is used on Twitter. We focused on the period when the UK government and its agencies adopted #DataSavesLives in an attempt to support their plans to set up a new database holding National Health Service (NHS) users’ medical data.

Methods

Public tweets published between April 19 and July 15, 2021, using the hashtag #DataSavesLives were saved using NCapture for NVivo 12. All tweets were coded twice. First, each tweet was assigned a positive, neutral, or negative attitude toward the campaign. Second, inductive thematic analysis was conducted. The results of the thematic analysis were mapped under 3 models of public engagement: deficit, dialogue, and participatory.

Results

Of 1026 unique tweets available for qualitative analysis, discussion around #DataSavesLives was largely positive (n=716, 69.8%) or neutral (n=276, 26.9%) toward the campaign with limited negative attitudes (n=34, 3.3%). Themes derived from the #DataSavesLives debate included ethical sharing, proactively engaging the public, coproducing knowledge with the public, harnessing potential, and gaining an understanding of big data research. The Twitter discourse was largely positive toward the campaign. The hashtag is predominantly used by similar-minded Twitter users to share information about big data projects and to spread positive messages about big data research when there are public controversies. The hashtag is generally used by organizations and people supportive of big data research. Tweet authors recognize that the public should be proactively engaged and involved in big data projects. The campaign remains UK centric. The results indicate that the communication around big data research is driven by the professional community and remains 1-way as members of the public rarely use the hashtag.

Conclusions

The results demonstrate the potential of social media but draws attention to hashtag usage being generally confined to “Twitter bubbles”: groups of similar-minded Twitter users.

Data authority: Public debate about personalized medicine in Denmark

Personalized medicine has generated massive investments in data integration initiatives and stimulated new flows of health data among multiple actors. Such flows raise questions as to who should be able to access data, for which purposes, and how this access and use should be regulated. We suggest thinking of these questions as matters of 'data authority': who can legitimately do what with health data? In this article, we analyze a public debate developing in written media about personalized medicine to understand negotiations of data authority. We demonstrate how the debate creates no consensus and yet seems to stimulate selective regulatory changes. The changes are selective in the sense that they focus on the protection of autonomy but fail to address concerns about, for example, commercial interests. We argue that data authority rests on enduring conflict and that this conflict can be seen as constitutive for personalized medicine as a sociotechnical phenomenon.

How can Big Data Analytics Support People-Centred and Integrated Health Services: A Scoping Review

Introduction:

Health systems in high-income countries face a variety of challenges calling for a systemic approach to improve quality and efficiency. Putting people in the centre is the main idea of the WHO model of people-centred and integrated health services. Integrating health services is fuelled by an integration of health data with great potentials for decision support based on big data analytics. The research question of this paper is “How can big data analytics support people-centred and integrated health services?”

Methods:

A scoping review following the recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses – Scoping Review (PRISMA-ScR) statement was conducted to gather information on how big data analytics can support people-centred and integrated health services. The results were summarized in a role model of a people-centred and integrated health services platform illustrating which data sources might be integrated and which types of analytics might be applied to support the strategies of the people-centred and integrated health services framework to become more integrated across the continuum of care. Additional rapid literature reviews were conducted to generate frequency distributions of the most often used data types and analytical methods in the medical literature. Finally, the main challenges connected with big data analytics were worked out based on a content analysis of the results from the scoping literature review.

Results:

Based on the results from the rapid literature reviews the most often used data sources for big data analytics (BDA) in healthcare were biomarkers (39.3%) and medical images (30.9%). The most often used analytical models were support vector machines (27.3%) and neural networks (20.4%). The people-centred and integrated health services framework defines different strategic interventions for health services to become more integrated. To support all aspects of these interventions a comparably integrated platform of health-related data would be needed, so that a role model labelled as people-centred health platform was developed. Based on integrated data the results of the scoping review (n = 72) indicate, that big data analytics could for example support the strategic intervention of tailoring personalized health plans (43.1%), e.g. by predicting individual risk factors for different therapy options. Also BDA might enhance clinical decision support tools (31.9%), e.g. by calculating risk factors for disease uptake or progression. BDA might also assist in designing population-based services (26.4% by clustering comparable individuals in manageable risk groups e.g. mentored by specifically trained, non-medical professionals. The main challenges of big data analytics in healthcare were categorized in regulatory, (information-) technological, methodological, and cultural issues, whereas methodological challenges were mentioned most often (55.0%), followed by regulatory challenges (43.7%).

Discussion:

The BDA applications presented in this literature review are based on findings which have already been published. For some important components of the framework on people-centred care like enhancing the role of community care or establishing intersectoral partnerships between health and social care institutions only few examples of enabling big data analytical tools were found in the literature. Quite the opposite does this mean that these strategies have less potential value, but rather that the source systems in these fields need to be further developed to be suitable for big data analytics.

Conclusions:

Big data analytics can support people-centred and integrated health services e.g. by patient similarity stratifications or predictions of individual risk factors. But BDA fails to unfold its full potential until data source systems are still disconnected and actions towards a comprehensive and people-centred health-related data platform are politically insufficiently incentivized. This work highlighted the potential of big data analysis in the context of the model of people-centred and integrated health services, whereby the role model of the person-centered health platform can be used as a blueprint to support strategies to improve person-centered health care. Likely because health data is extremely sensitive and complex, there are only few practical examples of platforms to some extent already capable of merging and processing people-centred big data, but the integration of health data can be expected to further proceed so that analytical opportunities might also become reality in the near future.

The ethical challenges of artificial intelligence-driven digital pathology

Digital pathology - the digitalisation of clinical histopathology services through the scanning and storage of pathology slides - has opened up new possibilities for health care in recent years, particularly in the opportunities it brings for artificial intelligence (AI)-driven research. Recognising, however, that there is little scholarly debate on the ethics of digital pathology when used for AI research, this paper summarises what it sees as four key ethical issues to consider when deploying AI infrastructures in pathology, namely, privacy, choice, equity, and trust. The themes are inspired from the authors' experience grappling with the challenge of deploying an ethical digital pathology infrastructure to support AI research as part of the National Pathology Imaging Cooperative (NPIC), a collaborative of universities, hospital trusts, and industry partners largely located across the North of England. Though focusing on the UK case, internationally, few pathology departments have gone fully digital, and so the themes developed here offer a heuristic for ethical reflection for other departments currently making a similar transition or planning to do so in the future. We conclude by promoting the need for robust public governance mechanisms in AI-driven digital pathology.

The life and death of confidentiality: a historical analysis of the flows of patient information

Health data can contain sensitive information. People who consult a doctor seek help on issues that matter to them: they typically expect some form of confidentiality. However, the notion and practices of confidentiality have changed dramatically over time. In this article, we trace the history of confidentiality in the Danish healthcare system, which has one of the world's most integrated patient information infrastructures. Building on an analysis of legal and political documents dating back to the late seventeenth century, we show that confidentiality originated as a social phenomenon that helped build trust in healthcare professionals and gradually developed into an idiom of citizens rights. Lately, confidentiality has given way to more technocratic forms of data protection. As the political, legal and technological reality, which the idea of confidentiality once referred to, has radically changed, we argue that confidentiality has become what Ulrik Beck has called a 'zombie category'-a notion that lives on even if its content has passed away. If confidentiality has become a zombie concept, we suggest it is time to discuss what may take its place so that patient interests are protected in the current political economy of health data.

Ethical issues in biomedical research using electronic health records: a systematic review

Digitization of a health record changes its accessibility. An electronic health record (EHR) can be accessed by multiple authorized users. Health information from EHRs contributes to learning healthcare systems' development. The objective of this systematic review is to answer a question: What are ethical issues concerning research using EHRs in the literature? We searched Medline Ovid, Embase and Scopus for publications concerning ethical issues of research use of EHRs. We employed the constant comparative method to retrieve common ethical themes. We descriptively summarized empirical studies. The study reveals the breadth, depth, and complexity of ethical problems associated with research use of EHRs. The central ethical question that emerges from the review is how to manage access to EHRs. Managing accessibility consists of interconnected and overlapping issues: streamlining research access to EHRs, minimizing risk, engaging and educating patients, as well as ensuring trustworthy governance of EHR data. Most of the ethical problems concerning EHR-based research arise from rapid cultural change. The framing of concepts of privacy, as well as individual and public dimensions of beneficence, are changing. We are currently living in the middle of this transition period. Human emotions and mental habits, as well as laws, are lagging behind technological developments. In the medical tradition, individual patient's health has always been in the center. Transformation of healthcare care, its digitalization, seems to have some impacts on our perspective of health care ethics, research ethics and public health ethics.

Motives for withdrawal of participation in biobanking and participants' willingness to allow linkages of their data

Data repositories, like research biobanks, seek to optimise the number of responding participants while simultaneously attempting to increase the amount of data donated per participant. Such efforts aim to increase the repository’s value for its uses in medical research to contribute to improve health care, especially when data linkage is permitted by participants. We investigated individuals’ motives for participating in such projects and potential reasons for their withdrawal from participation in a population-based biobank. In addition, we analysed how these motives were related to various characteristics of the participants and their willingness to permit data linkage to their personal data for research. These questions were explored using a sample of participants in the Dutch Lifelines biobank (n = 2615). Our results indicated that motives for participation and withdrawal were premised on benefits or harm to society and to the individuals themselves. Although general values and trust both played key roles in participation, potential withdrawal and willingness to permit data linkage, they were differentially associated with motives for participation and withdrawal. These findings support and nuance previous findings by highlighting the distinctiveness and complexity of decision making regarding participation in or withdrawal from data donation. We suggest some new directions for improving recruitment, retention and safeguarding strategies in biobanking. In addition, our data provide initial evidence regarding how factors may relate with the probability that individuals will agree to data linkages, when controlling for their unique effects. Future research should further investigate how perceptions of harm and benefits may influence decision making on withdrawal of participation.

Governing health data across changing contexts: A focus group study of citizen's views in England, Iceland, and Sweden

BACKGROUND

The governance structures associated with health data are evolving in response to advances in digital technologies that enable new ways of capturing, using, and sharing different types of data. Increasingly, health data moves between different contexts such as from healthcare to research, or to commerce and marketing. Crossing these contextual boundaries has the potential to violate societal expectations about the appropriate use of health data and diminish public trust. Understanding citizens' views on the acceptability of and preferences for data use in different contexts is essential for developing information governance policies in these new contexts.

METHODS

Focus group design presenting data sharing scenarios in England, Iceland, and Sweden.

RESULTS

Seventy-one participants were recruited. Participants supported the need for data to help understand the observable world, improve medical research, the quality of public services, and to benefit society. However, participants consistently identified the lack of information, transparency and control as barriers to trusting organisations to use data in a way that they considered appropriate. There was considerable support for fair and transparent data sharing practices where all parties benefitted.

CONCLUSION

Data governance policy should involve all stakeholders' perspectives on an ongoing basis, to inform and implement changes to health data sharing practices that accord with stakeholder views. The Findings showed that (1) data should be used for ethical purposes even when there was commercial interest; (2) data subjects and/or public institutions that provide and share data should also receive benefits from the sharing of data; (3) third parties use of data requires greater transparency and accountability than currently exists, (4) there should be greater information provided to empower data subjects.

E-Infrastructures and the divergent assetization of public health data: Expectations, uncertainties, and asymmetries

In this article, we examine some of the expectations, frictions and uncertainties involved with the assetization of de-identified NHS patient data by (primary care) research services in UK. Pledges to Electronic Health Record (EHR) data-driven research attempt to reconfigure public health data as an asset for realizing multiple values across healthcare, research and finance. We introduce the concept of 'asymmetrical divergence' in public health data assetization to study the various practices of configuring and using this data, both as a continuously generated resource to be extracted and as an asset to be circulated in the knowledge economy. As data assetization and exploitations grow bigger and more diverse, the capitalization of these datasets may constitute EHR data-driven research in healthcare as an attractive technoscientific activity, but one limited to those actors with specific sociotechnical resources in place to fully exploit them at the required scale.

Italian public’s views on sharing genetic information and medical information: findings from the ‘Your DNA, Your Say’ study

Background: The collection and sharing of genomic and health data underpins global efforts to develop genomic medicine services. ‘Your DNA, Your Say’ is a cross-sectional survey with the goal of gathering lay public attitudes toward the access and sharing of deoxyribonucleic acid (DNA) information and medical information. It suggests significant international variation in the willingness to share information, and in trust in the actors associated with the collection and use of this information. This paper explores these questions in the Italian context.

Methods: The Italian Your DNA, Your Say campaign led to the collection of 1229 valid questionnaires. The sample was analysed using standard descriptive statistics. We described the sample in terms of gender, age ranges and self-reported religiosity, and split the sample amongst the five typically studied Italian macro-areas to explore regional variation. We analysed the relationship between these factors and trust and willingness to share medical and DNA information. 

Results: The majority of the sample, across all socio-demographics, were willing to share DNA and health information with all entities considered except for-profit researchers. Respondents tended not to trust institutions beyond their own doctor. There was no difference between Italian regions.

Conclusions: Despite the generally positive attitude towards sharing, we suggest that the lack of trust in non-profit researchers and the government needs to be better understood to inform public communication projects around genomics in the future and to enhance awareness of DNA and medical information in Italy.

Public acceptance of privacy-encroaching policies to address the COVID-19 pandemic in the United Kingdom

The nature of the COVID-19 pandemic may require governments to use privacy-encroaching technologies to help contain its spread. One technology involves co-location tracking through mobile Wi-Fi, GPS, and Bluetooth to permit health agencies to monitor people's contact with each other, thereby triggering targeted social-distancing when a person turns out to be infected. The effectiveness of tracking relies on the willingness of the population to support such privacy encroaching measures. We report the results of two large surveys in the United Kingdom, conducted during the peak of the pandemic, that probe people's attitudes towards various tracking technologies. The results show that by and large there is widespread acceptance for co-location tracking. Acceptance increases when the measures are explicitly time-limited and come with opt-out clauses or other assurances of privacy. Another possible future technology to control the pandemic involves "immunity passports", which could be issued to people who carry antibodies for the COVID-19 virus, potentially implying that they are immune and therefore unable to spread the virus to other people. Immunity passports have been considered as a potential future step to manage the pandemic. We probe people's attitudes towards immunity passports and find considerable support overall, although around 20% of the public strongly oppose passports.

"AI's gonna have an impact on everything in society, so it has to have an impact on public health": a fundamental qualitative descriptive study of the implications of artificial intelligence for public health

Background

Our objective was to determine the impacts of artificial intelligence (AI) on public health practice.

Methods

We used a fundamental qualitative descriptive study design, enrolling 15 experts in public health and AI from June 2018 until July 2019 who worked in North America and Asia. We conducted in-depth semi-structured interviews, iteratively coded the resulting transcripts, and analyzed the results thematically.

Results

We developed 137 codes, from which nine themes emerged. The themes included opportunities such as leveraging big data and improving interventions; barriers to adoption such as confusion regarding AI’s applicability, limited capacity, and poor data quality; and risks such as propagation of bias, exacerbation of inequity, hype, and poor regulation.

Conclusions

Experts are cautiously optimistic about AI’s impacts on public health practice, particularly for improving disease surveillance. However, they perceived substantial barriers, such as a lack of available expertise, and risks, including inadequate regulation. Therefore, investment and research into AI for public health practice would likely be beneficial. However, increased access to high-quality data, research and education regarding the limitations of AI, and development of rigorous regulation are necessary to realize these benefits.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-020-10030-x.

Willingness to Share yet Maintain Influence: A Cross-Sectional Study on Attitudes in Sweden to the Use of Electronic Health Data

We have investigated attitudes towards the use of health data among the Swedish population by analyzing data from a survey answered by 1645 persons. Health data are potentially useful for a variety of purposes. Yet information about health remains sensitive. A balance therefore has to be struck between these opposing considerations in a number of contexts. The attitudes among those whose data is concerned will influence the perceived legitimacy of policies regulating health data use. We aimed to investigate what views are held by the general public, and what aspects matter for the willingness to let one's data be used not only for one's own care but also for other purposes. We found that while there is a broad willingness to let one's data be used, the possibility to influence that use is considered important. The study also indicated that when respondents are required to balance different interests, priority is typically given to compulsory schemes ensuring that data are available where needed, rather than voluntary participation and data protection. The policy implications to be drawn from this are not self-evident, however, since the fact that a majority has a certain attitude does not by itself determine the most adequate policy.

Global Public Perceptions of Genomic Data Sharing: What Shapes the Willingness to Donate DNA and Health Data?

Analyzing genomic data across populations is central to understanding the role of genetic factors in health and disease. Successful data sharing relies on public support, which requires attention to whether people around the world are willing to donate their data that are then subsequently shared with others for research. However, studies of such public perceptions are geographically limited and do not enable comparison. This paper presents results from a very large public survey on attitudes toward genomic data sharing. Data from 36,268 individuals across 22 countries (gathered in 15 languages) are presented. In general, publics across the world do not appear to be aware of, nor familiar with, the concepts of DNA, genetics, and genomics. Willingness to donate one's DNA and health data for research is relatively low, and trust in the process of data's being shared with multiple users (e.g., doctors, researchers, governments) is also low. Participants were most willing to donate DNA or health information for research when the recipient was specified as a medical doctor and least willing to donate when the recipient was a for-profit researcher. Those who were familiar with genetics and who were trusting of the users asking for data were more likely to be willing to donate. However, less than half of participants trusted more than one potential user of data, although this varied across countries. Genetic information was not uniformly seen as different from other forms of health information, but there was an association between seeing genetic information as special in some way compared to other health data and increased willingness to donate. The global perspective provided by our "Your DNA, Your Say" study is valuable for informing the development of international policy and practice for sharing genomic data. It highlights that the research community not only needs to be worthy of trust by the public, but also urgent steps need to be taken to authentically communicate why genomic research is necessary and how data donation, and subsequent sharing, is integral to this.

Emerging health data platforms: From individual control to collective data governance

Health data have enormous potential to transform healthcare, health service design, research, and individual health management. However, health data collected by institutions tend to remain siloed within those institutions limiting access by other services, individuals or researchers. Further, health data generated outside health services (e.g., from wearable devices) may not be easily accessible or useable by individuals or connected to other parts of the health system. There are ongoing tensions between data protection and the use of data for the public good (e.g., research). Concurrently, there are a number of data platforms that provide ways to disrupt these traditional health data siloes, giving greater control to individuals and communities. Through four case studies, this paper explores platforms providing new ways for health data to be used for personal data sharing, self-health management, research, and clinical care. The case-studies include data platforms: PatientsLikeMe, Open Humans, Health Record Banks, and unforgettable.me. These are explored with regard to what they mean for data access, data control, and data governance. The case studies provide insight into a shift from institutional to individual data stewardship. Looking at emerging data governance models, such as data trusts and data commons, points to collective control over health data as an emerging approach to issues of data control. These shifts pose challenges as to how “traditional” health services make use of data collected on these platforms. Further, it raises broader policy questions regarding how to decide what public good data should be put towards.

Pros and cons of prosent as an alternative to traditional consent in medical research

In their recent article, Porsdam Mann et al propose to share biomedical research data more widely, securely and efficiently using blockchain technologies.1 They present compelling arguments for how the blockchain presents both a technological innovation, and a deontologically grounded policy innovation to traditional research consent. Their proposal can be read in conversation with a rich body of evidence to suggest current consent processes are problematic on at least one of tripartite bases in biomedical research: that it be fully informed. This response attempts to further the author's discussion of social justice discourse in, and of their proposed prosent model to enhance engagement among under-represented and vulnerable populations in research, specifically. Motivating this response is the view that advancing technological capabilities is no doubt necessary, but on its own insufficient to reinvigorate distributive, procedural and social justice as guiding principles for con/prosent processes. I offer three pros and cons to consider in effort to deepen the model's commitments to social justice to historically marginalised groups in the biomedical research enterprise.

Benefits and challenges of Big Data in healthcare: an overview of the European initiatives

Healthcare systems around the world are facing incredible challenges due to the ageing population and the related disability, and the increasing use of technologies and citizen’s expectations. Improving health outcomes while containing costs acts as a stumbling block. In this context, Big Data can help healthcare providers meet these goals in unprecedented ways. The potential of Big Data in healthcare relies on the ability to detect patterns and to turn high volumes of data into actionable knowledge for precision medicine and decision makers. In several contexts, the use of Big Data in healthcare is already offering solutions for the improvement of patient care and the generation of value in healthcare organizations. This approach requires, however, that all the relevant stakeholders collaborate and adapt the design and performance of their systems. They must build the technological infrastructure to house and converge the massive volume of healthcare data, and to invest in the human capital to guide citizens into this new frontier of human health and well-being. The present work reports an overview of best practice initiatives in Europe related to Big Data analytics in public health and oncology sectors, aimed to generate new knowledge, improve clinical care and streamline public health surveillance.