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

• Published in: Journal of Medical Internet Research
• Main Authors: Biasiotto, Roberta, Viberg Johansson, Jennifer, Alemu, Melaku Birhanu, Romano, Virginia, Bentzen, Heidi Beate, Kaye, Jane, Ancillotti, Mirko, Blom, Johanna Maria Catharina, Chassang, Gauthier, Hallinan, Dara, Jónsdóttir, Guðbjörg Andrea, Monasterio Astobiza, Aníbal, Rial-Sebbag, Emmanuelle, Rodríguez-Arias, David, Shah, Nisha, Skovgaard, Lea, Staunton, Ciara, Tschigg, Katharina, Veldwijk, Jorien, Mascalzoni, Deborah
• Format: Article in Journal/Newspaper
• Language: English
• Published: JMIR Publications 2023
• Subjects: Norway; Iceland
• Online Access: http://hdl.handle.net/10852/107755; https://doi.org/10.2196/47066

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 ...