Quality improvement practices used by teaching versus non-teaching trauma centres: analysis of a multinational survey of adult trauma centres in the United States, Canada, Australia, and New Zealand
Bibliographic record
Abstract
BACKGROUND: Although studies have suggested that a relationship exists between hospital teaching status and quality improvement activities, it is unknown whether this relationship exists for trauma centres. METHODS: We surveyed 249 adult trauma centres in the United States, Canada, Australia, and New Zealand (76% response rate) regarding their quality improvement programs. Trauma centres were stratified into two groups (teaching [academic-based or -affiliated] versus non-teaching) and their quality improvement programs were compared. RESULTS: All participating trauma centres reported using a trauma registry and measuring quality of care. Teaching centres were more likely than non-teaching centres to use indicators whose content evaluated treatment (18% vs. 14%, p < 0.001) as well as the Institute of Medicine aim of timeliness of care (23% vs. 20%, p < 0.001). Non-teaching centres were more likely to use indicators whose content evaluated triage and patient flow (15% vs. 18%, p < 0.001) as well as the Institute of Medicine aim of efficiency of care (25% vs. 30%, p < 0.001). While over 80% of teaching centres used time to laparotomy, pulmonary complications, in hospital mortality, and appropriate admission physician/service as quality indicators, only two of these (in hospital mortality and appropriate admission physician/service) were used by over half of non-teaching trauma centres. The majority of centres reported using morbidity and mortality conferences (96% vs. 97%, p = 0.61) and quality of care audits (94% vs. 88%, p = 0.08) while approximately half used report cards (51% vs. 43%, p = 0.22). CONCLUSIONS: Teaching and non-teaching centres reported being engaged in quality improvement and exhibited largely similar quality improvement activities. However, differences exist in the type and frequency of quality indicators utilized among teaching versus non-teaching trauma centres.
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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 | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".