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Record W4417296776 · doi:10.1093/pch/pxaf116.021

21 Health professionals’ experiences with uninsured children in Québec: A qualitative study in paediatric settings

2025· article· en· W4417296776 on OpenAlexaffabout
Annie Liv, Patricia Li, Samir Shaheen-Hussain, Janet Cleveland, Nathalie Gaucher

Bibliographic record

VenuePaediatrics & Child Health · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsCentre Hospitalier Universitaire Sainte-JustineMcGill UniversityCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalMcGill University Health CentreUniversité de Montréal
Fundersnot available
KeywordsSnowball samplingThematic analysisQualitative researchHealth careNonprobability samplingInterimPublic healthHealth professionals

Abstract

fetched live from OpenAlex

Abstract Background The 2021 Bill 83 (PL83) aimed to provide provincial public health insurance (RAMQ) to previously uninsured migrant children in Quebec. However, many children remain uninsured, posing ethical challenges for healthcare professionals that have yet to be thoroughly examined. Objectives This study sought to explore healthcare professionals' experiences with uninsured children, focusing on practical and ethical issues arising from lack of insurance. Design/Methods This qualitative study, adopting a comprehensive paradigm focused on participants' subjectivity, included semi-structured interviews with healthcare professionals. These participants were recruited through purposive and snowball sampling at Quebec's two largest paediatric hospitals, one of which had a clinic for recently migrated children. Interview topics included clinical experiences with uninsured children, the impact of lack of insurance, and strategies for overcoming barriers. Interviews were fully transcribed, and thematic analysis using inductive coding (NVivo) revealed key themes. Results Between January and October 2024, 25 participants (52% physicians, 20% nurses, 20% social workers) were recruited. Analysis identified four main themes:Organizational and systemic factors contribute to a lack of RAMQ coverage, especially for eligible newborns whose parents do not have RAMQ coverage (uninsured migrants or asylum)Quebec’s healthcare system relies on the possession of RAMQ; its absence leads to significant challenges, including hospital bills, difficulties accessing primary healthcare services or physicians refusing consultations. It affects children insured by the Interim Federal Health Program (IFHP) who do not have RAMQ.Emergency departments (EDs) become the only option for parents seeking medical care for their children. EDs are not designed to respond to the healthcare and psychosocial needs of these marginalized populations. When EDs have access to teams dedicated to caring for migrants, these teams are also limited in their capacity to respond due to high demand and lack of resources.Participants expressed frustration and a sense of injustice toward barriers children without RAMQ face. Ethical challenges prompt professionals to find solutions to provide equitable care, such as unpaid work, longer consultations time to guide parents in navigating the system, and adapting treatments to financial limitations and life circumstances. Participants expressed helplessness, as some solutions exist but remain limited compared to the complex needs of these marginalized populations. Conclusion Insights from healthcare professionals highlight strategies used to mitigate the impact of lack of RAMQ on children’s healthcare. Potential systemic solutions include presumed eligibility based on residency proof, educating the healthcare workforce, and improving access to primary care.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.207
Threshold uncertainty score0.417

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0190.010
Scholarly communication0.0060.002
Open science0.0020.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.025
GPT teacher head0.335
Teacher spread0.309 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2025
Admission routes2
Has abstractyes

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