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Record W7047729018

Improving Access to Family Medicine in Quebec through Quotas and Numerical Targets

2019· article· en· W7047729018 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSuperconducting and THz Device Technology
Canadian institutionsnot available
Fundersnot available
KeywordsLegislatureNegotiationHealth careFamily doctorsPrimary careLegislationSocial policyBill of rights
DOInot available

Abstract

fetched live from OpenAlex

Despite various health reforms over the last 20 years, access to primary care remained stagnant in Québec, and in 2014 the province had the highest proportion of residents in Canada without a family physician. In November 2014, the Québec Minister of Health and Social Services introduced Bill 20, An Act to promote access to family medicine and specialized medicine services and to amend various legislative provisions relating to assisted procreation. Bill 20 aimed to increase access to family medicine through a system of quotas of registered patients and penalties for family physicians. Health system user support groups and the governmental advisory group on women's rights supported Bill 20's approach to ensure the rights of system users to access family physicians. However, the union of general practitioners was strongly against the bill due to the clash between the minister's reliance on numbers and the realities of family practice. The union of general practitioners entered negotiations with the minister and while Bill 20 was legalized in 2015, it was agreed that family physicians would be excused from the bill as long as they reached two targets at the end of December 2017: 1) 85% of Québecers must have a family doctor and 2) family doctors must ensure the patients registered to them see them, and not other doctors, 80% of the time. The targets were not met at the end of December 2017 but the quota system in Bill 20 has yet to be implemented. Malgré diverses réformes de la santé au cours des 20 dernières années, l'accès aux soins primaires est demeuré stagnant au Québec et en 2014, la province affichait la plus forte proportion au Canada de résidents sans médecin de famille. En novembre 2014, le ministre de la Santé et des Services sociaux du Québec a présenté le projet de loi 20, Loi favorisant l'accès aux services de médecine familiale et de médecine spécialisée et modifiant diverses dispositions législatives en matière de procréation assistée. Le projet de loi 20 visait à accroître l'accès à la médecine familiale grâce à un système de quotas de patients inscrits et de pénalités pour les médecins de famille ne se conformant pas à ces quotas. Les groupes d'usagers du système de santé et le groupe consultatif gouvernemental sur les droits des femmes ont appuyé l'approche du projet de loi 20. En contraste, la Fédération des médecins omnipraticiens du Québec s'est vivement opposée au projet de loi, arguant que les quotas qui seraient imposés ne tenaient pas compte des contraintes structurelles imposées sur la pratique de la médecine familiale, elles-mêmes issues de mandats gouvernementaux. Le syndicat des médecins généralistes a entamé des négociations avec le ministre et, bien que le projet de loi 20 ait été légalisé en 2015, il a été convenu que les médecins de famille seraient dispensés de l'application du projet de loi à condition d'atteindre deux objectifs à la fin du mois de décembre 2017: 1) tous les Québécois devaient avoir un médecin de famille et 2) les médecins de famille devaient s'assurer que 80% des visites à un médecin d'un patient soient avec le médecin avec lequel ils sont inscrits. Bien que les objectifs n'aient pas été atteints à la fin de décembre 2017, le système de quotas prévu dans le projet de loi 20 n'a pas encore été mis en œuvre.

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)0.008
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.070
Threshold uncertainty score0.509

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0030.002
Scholarly communication0.0050.002
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0150.001

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 head0.153
GPT teacher head0.501
Teacher spread0.348 · 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 designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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