Temporal trends and differences in mortality at trauma centres across Ontario from 2005 to 2011: a retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: Care in a trauma centre is associated with significant reductions in mortality after severe injury. However, emerging evidence suggests that outcomes across similarly accredited trauma centres are not equivalent, even after adjusting for case-mix. The primary objective of this analysis was to evaluate secular trends in overall mortality at trauma centres. Secondarily, we explored trauma centre-specific mortality to determine the extent of variation between centres. METHODS: Data on 26 421 adults (≥□18 yr) admitted to a trauma centre between 2005 and 2011 were derived from the Ontario Trauma Registry. We used generalized estimating equations to calculate in-hospital mortality over time and hierarchical models to estimate trauma-centre-specific mortality. To quantify variability between centres, we calculated median odds ratios. Adjusted odds of death were calculated for each trauma centre to identify those with higher than expected, average and lower than expected mortality. RESULTS: Overall mortality at trauma centres decreased from 13.2% in 2005 to 11.2% in 2009. After adjusting for case mix, the odds of death decreased by approximately 3% a year (95% confidence interval 0%-5%). Trauma centre-specific mortality ranged from 11.4% to 13.1%. After adjusting for case mix, differences in trauma centre-specific mortality were observed (median odds ratio = 1.25), suggesting that the odds of dying could be 1.25-fold greater if the same patient was admitted to 1 randomly selected trauma centre as opposed to another. Differences were most pronounced for patients with isolated head injuries and among older patients as evidenced by higher median odds ratios and the number of outliers. INTERPRETATION: We observed a significant improvement over time in the mortality of severely injured patients cared for at Ontario's trauma centres. However, considerable differences in trauma centre-specific mortality were observed. Differences were most pronounced among older injured patients and those with isolated traumatic brain injury. System-wide performance improvement initiatives should target these subgroups.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".