Abstract
BackgroundThe advent of learning healthcare systems (LHSs) raises an important implementation challenge concerning how to request and manage consent to support secondary use of data in learning cycles, particularly research activities. Current consent models in Quebec were not established with the context of LHSs in mind and do not support the agility and transparency required to obtain consent from all involved, especially the citizens. Therefore, a new approach to consent is needed. Previous work identified the meta-consent model as a promising alternative to fulfill the requirements of LHSs, particularly large-scale deployments. We elicited the public’s attitude toward the meta-consent model to evaluate if the model could be understood by the citizens and would be deemed acceptable to prepare for its possible implementation in Quebec.MethodsEight focus groups, with a total of 63 members of the general public from various backgrounds were conducted in Quebec, Canada, in 2019. Explicit attention was given to literacy levels, language spoken at home and rural vs urban settings. We assessed attitudes, concerns and facilitators regarding key components of the meta-consent model: predefined categories to personalized consent requests, a dynamic web-based infrastructure to record meta-consent, and default settings. To analyse the discussions, a thematic content analysis was performed using a qualitative software.ResultsOur findings showed that participants were supportive of this new approach of consent as it promotes transparency and offers autonomy for the management of their health data. Key facilitators were identified to be considered in the implementation of a meta-consent model in the Quebec LHSs: information and transparency, awareness campaigns, development of educational tools, collaboration of front-line healthcare professionals, default settings deemed acceptable by the society as well as close partnerships with recognized and trusted institutions.ConclusionsThis qualitative study reveals the openness of a sample of the Quebec population regarding the meta-consent model for secondary use of health data for research. This first exploratory study conducted with the public is an important step in guiding decision-makers in the next phases of implementing the various strategies to support access and use of health data in Quebec.
Highlights
The advent of learning healthcare systems (LHSs) raises an important implementation challenge concerning how to request and manage consent to support secondary use of data in learning cycles, research activities
Study design As part of a sequential mixed methods study, a qualitative approach consisting of semi-structured focus groups was used to explore Quebec citizens’ perspectives regarding the use of health data for research purposes and specific elements of the meta-consent model required to meet the unique particularities of a Learn‐ ing Health System (LHS)
Since participants had various levels of knowledge concerning research involving health data, we developed two short animated video for the purpose of this study [14]: a first one explaining the nature of health data and how they might be used by researchers to contribute to the improvement of care, and a second one which briefly introduced the meta-consent model by presenting the idea of a web-based portal on which people could dynamically customize their consent preferences for the use of their health data according to different categories of research projects
Summary
The advent of learning healthcare systems (LHSs) raises an important implementation challenge concerning how to request and manage consent to support secondary use of data in learning cycles, research activities. An implementation of delegated consent for access to health data for research has been made possible in hospital contexts under the Act respecting Access to docu‐ ments held by public bodies and the Protection of personal information (CQLR c A-2.1, s 125) of the Compilation of Québec Laws and Regulations. It does not promote transparency—and autonomy—optimally, as it does not inform healthcare users about the use of their health data. It does not provide access to health care data distributed outside of the hospital context
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