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Record W2051472621 · doi:10.13162/hro-ors.02.01.05

Implementing Centralized Waiting Lists for Patients without a Family Physician in Quebec

2014· article· fr· W2051472621 on OpenAlexaffvenueabout
Mylaine Breton, Jennissa Gagne, Fortuné Gankpe

Bibliographic record

VenueHealth Reform Observer - Observatoire des Réformes de Santé · 2014
Typearticle
Languagefr
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsIncentiveGovernment (linguistics)Family medicinePopulationMedicineBusinessEnvironmental health

Abstract

fetched live from OpenAlex

In 2008, the Québec government mandated the ninety-four Centres de Santé et des Services Sociaux (CSSS or Centres for Health and Social Services) to implement a Guichet d’Accès aux Clientèles Orphelines (GACO)—a centralized waiting list to help patients without a family physician find one. Specifically, the goal of GACOs is to increase the number of patients with a family physician as well as to give priority access to vulnerable patients. The media treatment of ‘orphan’ patients as well as the Fédération des Médecins Omnipraticiens du Québec (FMOQ or Federation of General Practitioners of Québec) both played a crucial role in the design and implementation of the reform. How the reform should be implemented was not detailed, leaving each CSSS considerable latitude in the strategies they adopted to introduce it on the ground. This room to manoeuvre led to large variability in what services GACOs offer and inequity in access to services for the population. Since their implementation, financial incentives set up to encourage the participation of family physicians have been modified twice, in particular with the goal of increasing the enrolment of more vulnerable patients through GACOs. A recent study shows that, despite a large difference in incentives to physicians for these vulnerable patients, more than 70% of patients enrolled with a family physician through a GACO are ‘non-vulnerable’ and are registered into the GACO from family physician self-referrals. Nonetheless, GACOs address an important problem by reducing the number of persons without a family physician. En 2008, le gouvernement du Québec a mandaté les quatre-vingt-quatorze centres de santé et des services sociaux (CSSS) d’introduire un guichet d’accès aux « clientèles orphelines » (GACO; le terme de clientèle orpheline désigne les patients n’ayant pas accès à un médecin de famille) au sein de leur organisation. L’objectif des GACO est d’augmenter le nombre de patients avec un médecin de famille et de prioriser les patients vulnérables. La médiatisation de l’enjeu des patients orphelins et la Fédération des médecins omnipraticiens du Québec ont joué un rôle prépondérant dans la conceptualisation et l’introduction de cette réforme. Peu de balises ont encadré le développement de cette réforme laissant donc une grande flexibilité dans les stratégies de mises en œuvre à chacun des CSSS. Cette marge de manœuvre à l’échelle locale a entraîné une variation dans l’offre de services des GACO, conduisant à une inéquité de services pour la population. Depuis leur implantation, les incitatifs financiers mis en place pour favoriser la participation des médecins de famille ont été modifiés à deux reprises, particulièrement pour faciliter la prise en charge des clientèles plus vulnérables via les GACO. Une étude récente a montré que, malgré un différentiel important dans les incitatifs financiers donnés aux médecins pour des patients vulnérables, plus de 70% des patients inscrits à un médecin de famille via les GACO étaient des patients non vulnérables et provenaient majoritairement d’une autoréférence par un médecin de famille. Le GACO répond, cependant, à une problématique importante en visant à réduire le nombre de personnes sans médecin de famille.

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)0.011
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.100
Threshold uncertainty score0.724

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0060.002
Scholarly communication0.0030.002
Open science0.0040.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0120.001

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 head0.058
GPT teacher head0.312
Teacher spread0.255 · 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
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".

Quick stats

Citations5
Published2014
Admission routes3
Has abstractyes

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