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- Biasiotto, Roberta, et al.
(författare)
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Public Preferences for Digital Health Data Sharing : Discrete Choice Experiment Study in 12 European Countries.
- 2023
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Ingår i: Journal of Medical Internet Research. - : JMIR Publications. - 1438-8871. ; 25
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 2. |
- Budin-Ljosne, Isabelle, et al.
(författare)
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Dynamic Consent : a potential solution to some of the challenges of modern biomedical research
- 2017
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Ingår i: BMC Medical Ethics. - : Springer Science and Business Media LLC. - 1472-6939. ; 18
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Tidskriftsartikel (refereegranskat)abstract
- Background: Innovations in technology have contributed to rapid changes in the way that modern biomedical research is carried out. Researchers are increasingly required to endorse adaptive and flexible approaches to accommodate these innovations and comply with ethical, legal and regulatory requirements. This paper explores how Dynamic Consent may provide solutions to address challenges encountered when researchers invite individuals to participate in research and follow them up over time in a continuously changing environment. Methods: An interdisciplinary workshop jointly organised by the University of Oxford and the COST Action CHIP ME gathered clinicians, researchers, ethicists, lawyers, research participants and patient representatives to discuss experiences of using Dynamic Consent, and how such use may facilitate the conduct of specific research tasks. The data collected during the workshop were analysed using a content analysis approach. Results: Dynamic Consent can provide practical, sustainable and future-proof solutions to challenges related to participant recruitment, the attainment of informed consent, participant retention and consent management, and may bring economic efficiencies. Conclusions: Dynamic Consent offers opportunities for ongoing communication between researchers and research participants that can positively impact research. Dynamic Consent supports inter-sector, cross-border approaches and large scale data-sharing. Whilst it is relatively easy to set up and maintain, its implementation will require that researchers re-consider their relationship with research participants and adopt new procedures.
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| 3. |
- Budin-Ljøsne, Isabelle, et al.
(författare)
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Feedback of Individual Genetic Results to Research Participants : Is It Feasible in Europe?
- 2016
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Ingår i: Biopreservation and Biobanking. - : Mary Ann Liebert Inc. - 1947-5535 .- 1947-5543. ; 14:3, s. 241-248
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: There is growing consensus that individual genetic research results that are scientifically robust, analytically valid, and clinically actionable should be offered to research participants. However, the general practice in European research projects is that results are usually not provided to research participants for many reasons. This article reports on the views of European experts and scholars who are members of the European COST Action CHIP ME IS1303 (Citizen's Health through public-private Initiatives: Public health, Market and Ethical perspectives) regarding challenges to the feedback of individual genetic results to research participants in Europe and potential strategies to address these challenges.MATERIALS AND METHODS: A consultation of the COST Action members was conducted through an email survey and a workshop. The results from the consultation were analyzed following a conventional content analysis approach.RESULTS: Legal frameworks, professional guidelines, and financial, organizational, and human resources to support the feedback of results are largely missing in Europe. Necessary steps to facilitate the feedback process include clarifying legal requirements to the feedback of results, developing harmonized European best practices, promoting interdisciplinary and cross-institutional collaboration, designing educational programs and cost-efficient IT-based platforms, involving research ethics committees, and documenting the health benefits and risks of the feedback process.CONCLUSIONS: Coordinated efforts at pan-European level are needed to enable equitable, scientifically sound, and socially robust feedback of results to research participants.
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| 4. |
- Kaye, Jane, et al.
(författare)
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From patients to partners : participant-centric initiatives in biomedical research.
- 2012
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Ingår i: Nature reviews genetics. - : Springer Science and Business Media LLC. - 1471-0056 .- 1471-0064. ; 13:5, s. 371-6
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Tidskriftsartikel (refereegranskat)abstract
- Advances in computing technology and bioinformatics mean that medical research is increasingly characterized by large international consortia of researchers that are reliant on large data sets and biobanks. These trends raise a number of challenges for obtaining consent, protecting participant privacy concerns and maintaining public trust. Participant-centred initiatives (PCIs) use social media technologies to address these immediate concerns, but they also provide the basis for long-term interactive partnerships. Here, we give an overview of this rapidly moving field by providing an analysis of the different PCI approaches, as well as the benefits and challenges of implementing PCIs.
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| 6. |
- Viberg, Jennifer, et al.
(författare)
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Governance mechanisms for sharing of health data: An approach towards selecting attributes for complex discrete choice experiment studies
- 2021
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Ingår i: Technology in society. - : Elsevier BV. - 0160-791X .- 1879-3274. ; 66, s. 101625-101625
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Tidskriftsartikel (refereegranskat)abstract
- Background: Discrete Choice Experiment (DCE) is a well-established technique to elicit individual preferences, but it has rarely been used to elicit governance preferences for health data sharing. Objectives: The aim of this article was to describe the process of identifying attributes for a DCE study aiming to elicit preferences of citizens in Sweden, Iceland and the UK for governance mechanisms for digitally sharing different kinds of health data in different contexts. Methods: A three-step approach was utilised to inform the attribute and level selection: 1) Attribute identification, 2) Attribute development and 3) Attribute refinement. First, we developed an initial set of potential attributes from a literature review and a workshop with experts. To further develop attributes, focus group discussions with citizens (n = 13), ranking exercises among focus group participants (n = 48) and expert interviews (n = 18) were performed. Thereafter, attributes were refined using group discussion (n = 3) with experts as well as cognitive interviews with citizens (n = 11). Results: The results led to the selection of seven attributes for further development: 1) level of identification, 2) the purpose of data use, 3) type of information, 4) consent, 5) new data user, 6) collector and 7) the oversight of data sharing. Differences were found between countries regarding the order of top three attributes. The process outlined participants' conceptualisation of the chosen attributes, and what we learned for our attribute development phase. Conclusions: This study demonstrates a process for selection of attributes for a (multi-country) DCE involving three stages: Attribute identification, Attribute development and Attribute refinement. This study can contribute to improve the ethical aspects and good practice of this phase in DCE studies. Specifically, it can contribute to the development of governance mechanisms in the digital world, where people's health data are shared for multiple purposes.
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| 7. |
- Viberg Johansson, Jennifer, et al.
(författare)
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Preferences of the Public for Sharing Health Data : Discrete Choice Experiment
- 2021
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Ingår i: JMIR Medical Informatics. - : JMIR Publications. - 2291-9694. ; 9:7
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Tidskriftsartikel (refereegranskat)abstract
- Background: Digital technological development in the last 20 years has led to significant growth in digital collection, use, and sharing of health data. To maintain public trust in the digital society and to enable acceptable policy-making in the future, it is important to investigate people’s preferences for sharing digital health data.Objective: The aim of this study is to elicit the preferences of the public in different Northern European countries (the United Kingdom, Norway, Iceland, and Sweden) for sharing health information in different contexts.Methods: Respondents in this discrete choice experiment completed several choice tasks, in which they were asked if data sharing in the described hypothetical situation was acceptable to them. Latent class logistic regression models were used to determine attribute-level estimates and heterogeneity in preferences. We calculated the relative importance of the attributes and the predicted acceptability for different contexts in which the data were shared from the estimates.Results: In the final analysis, we used 37.83% (1967/5199) questionnaires. All attributes influenced the respondents’ willingness to share health information (P<.001). The most important attribute was whether the respondents were informed about their data being shared. The possibility of opting out from sharing data was preferred over the opportunity to consent (opt-in). Four classes were identified in the latent class model, and the average probabilities of belonging were 27% for class 1, 32% for class 2, 23% for class 3, and 18% for class 4. The uptake probability varied between 14% and 85%, depending on the least to most preferred combination of levels.Conclusions: Respondents from different countries have different preferences for sharing their health data regarding the value of a review process and the reason for their new use. Offering respondents information about the use of their data and the possibility to opt out is the most preferred governance mechanism.
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