Good Neighbors? The Effect of a Level 1 Trauma Center on the Performance of Nearby Level 2 Trauma Centers
Bibliographic record
Abstract
OBJECTIVE: In this study, we sought to determine whether the proximity of a level 1 trauma center (TC) might affect the performance of a nearby level 2 TC. BACKGROUND: With the exception of research and teaching programs, level 2 TC must function at a level similar to that of level 1 TC, and provide high quality, definitive care to severely injured patients. However, the role of a level 2 TC within a region might vary significantly depending on the local trauma care environment. We postulated that the case mix, regional role and outcomes of level 2 TC are greatly influenced by the regional presence of a level 1 TC. METHODS: Data were derived from the National Trauma Databank (9.0), limiting to adults with Injury Severity Score ≥9. Level 2 TC were classified as either isolated trauma centers (ITC, >30 miles from the closest level 1 TC) or neighbored trauma centers (NTC, ≤30 miles from the closest level 1 TC). Regression was used to calculate risk-adjusted mortality at each center type. RESULTS: Fifty-five thousand six hundred and fifty-five patients were identified at 161 centers; 55% of patients were cared for at ITC (n = 84 centers). Case mix varied significantly across center type; in particular, ITC received significantly more transfer patients than NTC. After adjusting for differences in case mix, patients at ITC had a 12% lower risk of death than patients treated at NTC (0.88, 95% CI 0.78-0.98). CONCLUSIONS: Level 2 TC assume different roles depending on the local trauma system configuration. Ideally, a level 2 TC should benefit from the presence of a nearby level 1 TC through collaborations in care protocols and shared case reviews. However, these data suggest the opposite: level 2 centers in proximity to level 1 centers might perform at a lower than expected level.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.000 | 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".