A Comparison of Quality Improvement Practices at Adult and Pediatric Trauma Centers*
Bibliographic record
Abstract
OBJECTIVES: Quality assurance practices are structured performance improvement and patient safety processes designed to continuously monitor, evaluate, and improve the performance of a trauma program. These practices are integral in the provision of quality injury care, and yet no comprehensive description of existing quality improvement practices used by pediatric trauma centers is available. Therefore, we compared the quality improvement programs used in adult and pediatric trauma centers by performing a reanalysis of our recent survey of trauma quality improvement practices in Canada, United States, Australia, and New Zealand. DESIGN: Prospective observational study. SETTING: Pediatric and adult trauma centers in United States, Canada, and Australasia. PATIENTS: None. INTERVENTIONS: None. MEASUREMENTS: We surveyed 184 trauma centers verified by professional trauma organizations in the United States, Canada, and Australasia regarding their quality improvement programs. Centers were classified according to population served (adult, adult and pediatric, or pediatric patients), and quality improvement programs were compared using descriptive statistics. RESULTS: Most of the trauma centers reported engagement in quality improvement activities. Adult centers devoted a larger percentage of their quality indicators to the measurement of safety (adult 50% vs adult and pediatric 53% vs pediatric 38%, p < 0.001), whereas pediatric centers placed a greater emphasis on the timeliness of care (20% vs 24% vs 30%, p < 0.001). Few centers used quality indicators to measure the patient-centered nature of care, long-term outcomes, or secondary injury prevention. CONCLUSIONS: Opportunities for the improvement of pediatric quality improvement programs exist including a need to determine the optimal structure for trauma quality improvement, develop patient-centered quality indicators of injury care, measure long-term outcomes, and create measures of secondary injury prevention.
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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 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".