Interprofessional advanced access – a quality improvement protocol for expanding access to primary care services
Bibliographic record
Abstract
BACKGROUND: The Advanced Access (AA) Model has shown considerable success in improving timely access for patients in primary care settings. As a result, a majority of family physicians have implemented AA in their organizations over the last decade. However, despite its widespread use, few professionals other than physicians and nurse practitioners have implemented the model. Among those who have integrated it to their practice, a wide variation in the level of implementation is observed, suggesting a need to support primary care teams in continuous improvement with AA implementation. This quality improvement research project aims to document and measure the processes and effects of practice facilitation, to implement and improve AA within interprofessional teams. METHODS: Five primary care teams at various levels of organizational AA implementation will take part in a quality improvement process. These teams will be followed independently over PDSA (Plan-Do-Study-Act) cycles for 18 months. Each team is responsible for setting their own objectives for improvement with respect to AA. The evaluation process consists of a mixed-methods plan, including semi-structured interviews with key members of the clinical and management teams, patient experience survey and AA-related metrics monitored from Electronic Medical Records over time. DISCUSSION: Most theories on organizational change indicate that practice facilitation should enable involvement of stakeholders in the process of change and enable improved interprofessional collaboration through a team-based approach. Improving access to primary care services is one of the top priorities of the Quebec's ministry of health and social services. This study will identify key barriers to quality improvement initiatives within primary care and help to develop successful strategies to help teams improve and broaden implementation of AA to other primary care professionals.
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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 | 0.124 | 0.099 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.017 | 0.004 |
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".