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Record W4403350980 · doi:10.1186/s12875-024-02614-y

Organizational innovations related to Primary Care Access Points (GAP) for unattached patients in Quebec: a multi-case qualitative study

2024· article· en· W4403350980 on OpenAlexafffundabout
Mylaine Breton, Véronique Deslauriers, Catherine Lamoureux‐Lamarche, Mélanie Ann Smithman, Carine Sauvé, Marie Beauséjour, Maude Laberge, Aude Motulsky, Marie‐Pascale Pomey

Bibliographic record

VenueBMC Primary Care · 2024
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsCentre Hospitalier de l’Université de MontréalUniversité de MontréalSanté MontérégieUniversité LavalCentre hospitalier de l'Université LavalToronto Public HealthUniversité de Sherbrooke
FundersCanadian Institutes of Health Research
KeywordsPrimary careQualitative researchKnowledge managementMedicineBusinessProcess managementComputer scienceSociologyFamily medicineSocial science

Abstract

fetched live from OpenAlex

BACKGROUND: Being attached to a primary care (PC) provider is at the core of a strong primary health care system. Centralized waiting lists (CWL) for unattached patients have been implemented in eight provinces of Canada to support the attachment process. In Quebec, the Ministry of Health mandated the implementation of Primary Care Access Points (GAP) across the province to help unattached patients navigate the health system while awaiting attachment through the CWL. Several local health territories developed complementary innovations to the GAP to respond to local population needs. This paper aims to describe five organizational innovations implemented locally. METHODS: This multi-case qualitative study was conducted in four local health territories in the province of Quebec. Fifty-two semi-structured interviews with healthcare managers, nurses, physicians, other health professionals and administrative staff were conducted between April 2023 and April 2024. An interview guide was developed based on existing frameworks on the implementation of innovations and the evaluation of the GAP. Thematic analysis was conducted using NVivo software. Inductive and deductive approaches were used to develop relevant codes and themes. Logic models were built to describe the organizational innovations. RESULTS: Five organizational innovations are described. First, a multidisciplinary clinic aimed at responding to patients with mental health issues was implemented. Second, a nurse clinic was implemented to provide temporary care for patients with unstable chronic illnesses. The third innovation is a mobile proximity clinic where unattached GAP patients are first evaluated by a paramedic before receiving care from a nurse. Fourth, a pharmacist trajectory was implemented to increase engagement of community pharmacists to respond to GAP patients. The last innovation is a decentralized GAP offering in-person nursing care to unattached GAP patients. CONCLUSIONS: Descriptions of these five innovations are key to inform other territories and provinces on ways to improve access for unattached patients while they are waiting to be attached. The introduction of the GAP and the organizational innovations, suggests a transition where access to PC services does not rely solely on attachment status.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.126
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.104
GPT teacher head0.491
Teacher spread0.387 · 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 teacher head, not a consensus.

Study designObservational
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
Published2024
Admission routes3
Has abstractyes

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