Evidence map›Paper›PMID 34187453›Full record

ArticleBMC medical ethics2021

Meta-consent for the secondary use of health data within a learning health system: a qualitative study of the public's perspective.

Annabelle Cumyn, Adrien Barton, Roxanne Dault, Nissrine Safa, Anne-Marie Cloutier, Jean-François Ethier

Abstract read
In one paragraph

Article in BMC medical ethics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed.

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  14. Who Will Get Paid for Artificial Intelligence in Medicine?Radiology. Artificial intelligence · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Annabelle CumynGroupe de Recherche Interdisciplinaire en Informatique de la Santé (GRIIS), Faculté de Médecine et des Sciences de la Santé, Université de Sherbrooke, 2500 Boulevard de l'Université, Sherbrooke, QC, J1K 2R1, Canada.ORCID 0000-0002-6802-6472
Adrien BartonGroupe de Recherche Interdisciplinaire en Informatique de la Santé (GRIIS), Faculté de Médecine et des Sciences de la Santé, Université de Sherbrooke, 2500 Boulevard de l'Université, Sherbrooke, QC, J1K 2R1, Canada.ORCID 0000-0001-5500-6539
Roxanne DaultGroupe de Recherche Interdisciplinaire en Informatique de la Santé (GRIIS), Faculté de Médecine et des Sciences de la Santé, Université de Sherbrooke, 2500 Boulevard de l'Université, Sherbrooke, QC, J1K 2R1, Canada.ORCID 0000-0003-1444-553X
Nissrine SafaGroupe de Recherche Interdisciplinaire en Informatique de la Santé (GRIIS), Faculté de Médecine et des Sciences de la Santé, Université de Sherbrooke, 2500 Boulevard de l'Université, Sherbrooke, QC, J1K 2R1, Canada.
Anne-Marie CloutierGroupe de Recherche Interdisciplinaire en Informatique de la Santé (GRIIS), Faculté de Médecine et des Sciences de la Santé, Université de Sherbrooke, 2500 Boulevard de l'Université, Sherbrooke, QC, J1K 2R1, Canada.ORCID 0000-0001-9682-276X
Jean-François EthierGroupe de Recherche Interdisciplinaire en Informatique de la Santé (GRIIS), Faculté de Médecine et des Sciences de la Santé, Université de Sherbrooke, 2500 Boulevard de l'Université, Sherbrooke, QC, J1K 2R1, Canada. Jean-Francois.Ethier@USherbrooke.ca.ORCID 0000-0001-9408-0109

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Learning Health SystemCanadaHumansInformed ConsentQualitative ResearchQuebecFocus groupsHealth dataLearning healthcare systemMeta-consentPublic opinion

Identifiers

PMID34187453
PMCPMC8240433

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.