[Management systems of the quality of health care in Quebec hospitals].
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to take stock of the development of quality management systems in the Quebec health care services. METHODS: The study relied on semi-guided interviews and on a documentary analysis. It concerned the structure and the activity of quality management in 4 Montreal university hospitals as well as on outside organizations dealing with quality of care. RESULTS: Quality management of the health care services is dealt with by council on health care accreditation and regional health and social services agencies. In hospitals, the quality of services is managed by structures created by the administration council and the top management: the piloting committee, the head of quality assurance, the executive committees and the multidisciplinary team or self-evaluation of the hospital, and development of plans for improvement. Other activities are management of complaints, users satisfaction evaluation and follow-up of indicators. CONCLUSIONS: This system of quality management of services is currently expanding. This change of paradigm leads to accepting the view of services users and to change quality management methods. Those methods have evolved from normative approach to a continuous quality improvement approach.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".