Development of Patient-Inclusive Teams: Toward a Structured Methodology
Bibliographic record
Abstract
Over the last few years, the role of patients in the health system has become essential to improving the quality of care and services.However, the literature shows that patient engagement is not always ideally applied to improve the quality and safety of care and that patient engagement can be tokenistic.Through experiences conducted in Quebec, it is possible to outline a structured process involving both professional stakeholders and patients that illustrates optimal conditions to be applied for successful teamwork involving patients. RésuméAu cours des dernières années, le rôle des patients dans le système de santé est devenu essentiel pour améliorer la qualité des soins et des services.Cependant, la littérature montre que l'engagement des patients n'est pas toujours réalisé idéalement pour améliorer la qualité et la sécurité des soins et que l'engagement des patients peut être symbolique.Au travers de l'expérience menée au Québec, il est possible de faire ressortir un processus structuré portant à la fois sur les intervenants et les patients, qui permet de mettre en œuvre les conditions optimales à une réussite du travail d'équipe incluant des patients.
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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 | 0.160 | 0.111 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.005 | 0.011 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".