Taxonomy of advanced access practice profiles among family physicians, nurse practitioners and nurses in university-affiliated team-based primary healthcare clinics in Quebec
Bibliographic record
Abstract
Objectives The advanced access model is highly recommended to improve timely access to primary healthcare (PHC). However, its adoption varies among PHC providers. We aim to identify the advanced access profiles of PHC providers. Design A cross-sectional study was conducted between October 2019 and March 2020. Latent class analysis (LCA) measures were used to identify PHC provider profiles based on 14 variables, 2 organisational context characteristics (clinical size and geographical area) and 12 advanced access strategies. Setting and participants All family physicians, nurse practitioners and nurses working in the 49 university-affiliated team-based PHC clinics in Quebec, Canada, were invited, of which 35 participated. Primary outcome measure The LCA was based on 335 respondents. We determined the optimal number of profiles using statistical criteria (Akaike information criterion, Bayesian information criterion) and qualitatively named each of the six advanced access profiles. Results (1) Low supply and demand planification (25%) was characterised by the smallest proportion of strategies used to balance supply and demand. (2) Reactive interprofessional collaboration (25%) was characterised by high collaboration and long opening periods for appointment scheduling. (3) Structured interprofessional collaboration (19%) was characterised by high use of interprofessional team meetings. (4) Small urban delegating practices (13%) was exclusively composed of family physicians and characterised by task delegation to other PHC providers on the team. (5) Comprehensive practices in urban settings (13%) was characterised by including as many services as possible on each visit. (6) Rural agility (4%) was characterised by the highest uptake of advanced access strategies based on flexibility, including adjusting the schedule to demand and having a large number of open-slot appointments available in the next 48 hours. Conclusion The different patterns of advanced access strategy adoption confirm the need for training to be tailored to individuals, categories of PHC providers and contexts.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".