Institutional and provider factors impeding access to trauma center care
Bibliographic record
Abstract
BACKGROUND: More than a third of patients with severe injury who receive initial care at nontrauma centers (NTCs) are not transferred to trauma center care. In those who are transferred, significant delays have been described. The availability of specialists, imaging modalities, or critical care resources might significantly affect transfer practices. METHODS: We undertook a population-based retrospective cohort study of adult patients with severe injury who were transported from the scene to an NTC. NTCs were characterized based on the availability of general and orthopedic surgeons, computed tomographic scanners, intensive care units, and emergency department staffing. NTCs that had all of the resources were characterized as resource rich, while those with none were characterized as resource limited. We evaluated the relationships between NTC resources and the likelihood and timeliness of interfacility transfer through the use of hierarchical regression modeling. RESULTS: We identified 15,906 patients with severe injury across 192 NTCs (22% were resource limited, 57% were resource intermediate, and 21% were resource rich). Patients at resource rich centers, as compared with those at resource limited centers, were less likely to be transferred (27% vs. 50%, p < 0.001). This association persisted after adjustment for confounders (odds ratio, 0.66; 95% confidence interval, 0.47-0.92). Among patients who were transferred, median emergency department length of stay (ED-LOS) was 3.5 hours (interquartile range, 1.7-4.6 hours). However, ED-LOS varied significantly because resource rich centers had a greater proportion of patients experiencing prolonged ED-LOS when compared with resource limited centers (31% vs. 15%, p < 0.001). This association also persisted on multivariable analysis (odds ratio, 2.02; 95% confidence interval, 1.19-3.43). CONCLUSION: Severely injured patients who received initial care in resource rich NTCs were less likely to be transferred to a trauma center compared with resource limited NTCs. Significant delays in the transfer process were identified. However, patients transferred from resource rich centers were more likely to experience prolonged ED-LOS compared with resource limited NTCs. LEVEL OF EVIDENCE: Epidemiologic study, level II.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.005 | 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".