Créer et maintenir de la valeur: Instaurer une culture d'amélioration continue
Bibliographic record
Abstract
En 2011, le Toronto East General Hospital (TEGH) a entrepris de mettre sur pied une culture d'amélioration continue. Il a fini par adopter un système d'amélioration dans l'ensemble de son organisation grâce à son engagement envers la responsabilité financière, l'innovation pratique, la gestion du rendement des équipes et les systèmes de gestion quotidienne. Grâce à cette culture, le TEGH se targue du temps d'attente le moins long du réseau local d'intégration des services de santé à la salle d'urgence pour les patients admis et a réduit de 46 % le séjour hospitalier des patients atteints d'une maladie pulmonaire obstructive chronique.
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 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 | 0.064 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.021 | 0.049 |
| Scholarly communication | 0.023 | 0.010 |
| Open science | 0.002 | 0.018 |
| Research integrity | 0.006 | 0.014 |
| Insufficient payload (model declined to judge) | 0.004 | 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".