Phase 1 – Exploration of Approaches to Support Transparency and Autonomy
The research carried out during this phase revealed that the meta consent model (Ploug & Holm, 2016) is the most effective method for promoting the autonomy of Quebec citizens. It enables them to be informed and have a say in the use of their health data in research, while being compatible with learning health systems.
A meta consent model allows individuals to choose, via a web portal (or any other technological infrastructure), how and how often they will be informed of access to and use of their health data, of ongoing research activities, and of the results of research projects. Thanks to this model, individuals can personalize their consent according to the characteristics of research projects. In short, this is the consent model that puts the individual at the heart of decisions-making regarding the use of their health data.
Meta Consent in Comic Strip
This comic strip was presented at the Journée annuelle du Réseau-1 Québec, and explains the meta consent model’s principles.
Context
Current consent models for the use of health data stored in public network institutions in research are not adapted to learning health systems. Individual consent, which is granted by an individual for a specific research project, hinders the deployment of research projects requiring large samples of data and cannot operate on a large scale. As for the delegation of consent to a third party, for which no information process is provided, this does not promote neither transparency nor the autonomy of citizens about the use of their health data in research.
Objectives
For this first phase of the research program, the following objectives have been defined:
OBJECTIVE 1
Identify and analyze the proposed information and consent methods for access to health data and its use in research in the context of learning health systems.
OBJECTIVE 2
Understand the level of acceptability and understanding of citizens toward the consent model deemed to be the most appropriate in the context as described above.
OBJECTIVE 3
Make recommendations promoting autonomy and transparency to guide the decision-makers responsible for developing the current ethical and legal frameworks in Quebec governing access to health data and its use in research.
Methodology
Through a scoping review, identify the consent models that promote citizen autonomy and that have been proposed for participation in research activities in a learning health system.
Analyze which approaches, depending on the context in which they are used, are considered the most feasible and acceptable from an ethical, legal, and social point of view.
Meta consent having been identified as the most autonomy-friendly consent method, the CLARET team carried out a sequential mixed methods study consisting of a survey and a series of focus groups with Quebec residents, including people with a low level of education. The purpose of these consultations was to sound out the opinions of citizens on the following subjects:
- current information methods and consent models;
- understanding and acceptability of meta consent, an innovative consent model in Quebec;
- conditions, obstacles, and possible solutions for implementing the meta consent model in Quebec.
This last objective consisted of consulting people with expertise in various fields (ethics, legal, data security, informatics, and research) and people with whom we have developed a patient partnership to draw up a series of recommendations. These recommendations, based on the results of the literature review and the major findings of the mixed study, were presented directly by some CLARET team members who took part in the working group drafting the Act respecting health and social services information, which was adopted in April 2023.
Conclusions
A Quebec citizen survey shows that:
Informed and consented use of health data in research
90.4%
of respondents support the use of their health data (including certain personal information) in research if they are informed about it and consent is requested.
Acceptability of the use in research of health data that includes certain personal information
81.2%
of respondents disagree with the use of their data in research if they are not informed about it and no consent is requested.
64.6%
of respondents disagree with the use of their data in research if they are informed about it but no consent is requested.
Transparency and autonomy in the use of health data in research
79.9%
of respondents support the use of a web-based platform to receive information about the use of their data and to express their consent on this matter.
Informed and consented use of health data in research
90.4%
of respondents support the use of their health data (including certain personal information) in research if they are informed about it and consent is requested.
Acceptability of the use in research of health data that includes certain personal information
81.2%
of respondents disagree with the use of their data in research if they are not informed about it and no consent is requested.
64.6%
of respondents disagree with the use of their data in research if they are informed about it but no consent is requested.
Transparency and autonomy in the use of health data in research
79.9%
of respondents support the use of a web-based platform to receive information about the use of their data and to express their consent on this matter.
Source: Citizens, Research Ethics Committee Members and Researchers’ Attitude Toward Information and Consent for the Secondary Use of Health Data: Implications for Research Within Learning Health Systems (2021)
Focus groups conducted with citizens across Quebec in 2022 have led us to conclude that:
Meta consent model
The meta consent model was generally well understood once simple explanations had been given to the participants.
It was well accepted because it promotes transparency and offers considerable autonomy in managing the use of health data.
There are five key factors to consider in the implementation in Quebec:
Transparency must be present at every stage of the implementation process.
Awareness campaigns and educational tools need to be developed.
Collaboration and involvement of front-line healthcare professionals is required.
Introduction of default settings for people who do not want to be actively involved in decisions about access to and use of their health data.
Establishing close partnerships with recognized and trusted institutions.
Source: Meta-consent for the secondary use of health data within a learning health system: a qualitative study of the public’s perspective (2021)
Scientific Benefits
Scientific Publications
Conferences and Presentations
Poster Presentations
Reports
Press Articles
- Ethier JF, Lavoie L, Cumyn A. L’intelligence artificielle en soutien aux systèmes de santé apprenants | Le Devoir [Internet]. Disponible à: https://www.ledevoir.com/societe/science/541357/l-intelligence-artificielle-en-soutien-aux-systemes-de-sante-apprenants
- Malboeuf MC. Accès aux données de recherche | Qui réutilise vos informations médicales ? | La Presse [Internet]. Disponible à: https://www.lapresse.ca/actualites/2021-07-19/acces-aux-donnees-de-recherche/qui-reutilise-vos-informations-medicales.php
- Épisodes | La période de questions | ICI RDI [Internet]. Disponible à: https://ici.radio-canada.ca/tele/la-periode-de-questions/site/episodes/477208/periode-de-questions-vente-donne-medical
Photos
Les activités de recherche de la phase 1 ont été diversifiées et enrichissantes, comme en témoignent ces photos prises.
