Evaluation of the implementation of single points of access for unattached patients in primary care and their effects: a study protocol
Bibliographic record
Abstract
Introduction Attachment to a primary care provider is an important component of primary care as it facilitates access. In Québec, Canada, attachment to a family physician is a concern. To address unattached patients’ barriers to accessing primary care, the Ministry of Health and Social Services mandated Québec’s 18 administrative regions to implement single points of access for unattached patients ( Guichets d’accès première ligne (GAPs)) that aim to better orient patients towards the most appropriate services to meet their needs. The objectives of this study are to (1) analyse the implementation of GAPs, (2) measure the effects of GAPs on performance indicators and (3) assess unattached patients’ experiences of navigation, access and service utilisation. Methods and analysis A longitudinal mixed-methods case study design will be conducted. Objective 1. Implementation will be analysed through semistructured interviews with key stakeholders, observations of key meetings and document analysis. Objective 2. GAP effects on indicators will be measured using performance dashboards produced using clinical and administrative data. Objective 3. Unattached patients’ experiences will be assessed using a self-administered electronic questionnaire. Findings for each case will be interpreted and presented using a joint display, a visual tool for integrating qualitative and quantitative data. Intercase analyses will be conducted highlighting the similarities and differences across cases. Ethics and dissemination This study is funded by the Canadian Institutes of Health Research (# 475314) and the Fonds de Soutien à l’innovation en santé et en services sociaux (# 5-2-01) and was approved by the CISSS de la Montérégie-Centre Ethics Committee (MP-04-2023-716).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.168 | 0.091 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.007 | 0.005 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.037 | 0.009 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".