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Preferences of the Public for Sharing Health Data: Discrete Choice Experiment.
Viberg Johansson, Jennifer; Bentzen, Heidi Beate; Shah, Nisha; Haraldsdóttir, Eik; Jónsdóttir, Guðbjörg Andrea; Kaye, Jane; Mascalzoni, Deborah; Veldwijk, Jorien.
Afiliación
  • Viberg Johansson J; Centre for Research Ethics & Bioethics, Department of Public Health and Caring Sciences, Uppsala Universitet, Uppsala, Sweden.
  • Bentzen HB; Norwegian Research Center for Computers and Law, Faculty of Law, University of Oslo, Oslo, Norway.
  • Shah N; Centre for Health, Law, and Emerging Technologies, Faculty of Law, University of Oxford, Oxford, United Kingdom.
  • Haraldsdóttir E; Social Science Research Institute, University of Iceland, Reykjavik, Iceland.
  • Jónsdóttir GA; Social Science Research Institute, University of Iceland, Reykjavik, Iceland.
  • Kaye J; Centre for Health, Law, and Emerging Technologies, Faculty of Law, University of Oxford, Oxford, United Kingdom.
  • Mascalzoni D; Centre for Health, Law and Emerging Technologies, Melbourne Law School, University of Melbourne, Melbourne, Australia.
  • Veldwijk J; Centre for Research Ethics & Bioethics, Department of Public Health and Caring Sciences, Uppsala Universitet, Uppsala, Sweden.
JMIR Med Inform ; 9(7): e29614, 2021 Jul 05.
Article en En | MEDLINE | ID: mdl-36260402
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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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: JMIR Med Inform Año: 2021 Tipo del documento: Article País de afiliación: Suecia

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: JMIR Med Inform Año: 2021 Tipo del documento: Article País de afiliación: Suecia