Effects of closure of an urban level I trauma centre on adjacent hospitals and local injury mortality: a retrospective, observational study
Bibliographic record
Abstract
OBJECTIVE: To determine the association of the Martin Luther King Jr Hospital (MLK) closure on the distribution of admissions on adjacent trauma centres, and injury mortality rates in these centres and within the county. DESIGN: Observational, retrospective study. SETTING: Non-public patient-level data from the state of California were obtained for all trauma patients from 1999 to 2009. Geospatial analysis was used to visualise the redistribution of trauma patients to other hospitals after MLK closed. Variance of observed to expected injury mortality using multivariate logistic regression was estimated for the study period. PARTICIPANTS: A total of 37 131 trauma patients were admitted to the five major south Los Angeles trauma centres from the MLK service area between 1999 and 2009. MAIN OUTCOME MEASURES: (1) Number and type of trauma admissions to trauma centres in closest proximity to MLK; (2) inhospital injury mortality of trauma patients after the trauma centre closure. RESULTS: During and after the MLK closure, trauma admissions increased at three of the four nearby hospitals, particularly admissions for gunshot wounds (GSWs). This redistribution of patient load was accompanied by a dramatic change in the payer mix for surrounding hospitals; one hospital's share of uninsured more than tripled from 12.9% in 1999 to 44.6% by 2009. Overall trauma mortality did not significantly change, but GSW mortality steadily and significantly increased after the closure from 5.0% in 2007 to 7.5% in 2009. CONCLUSIONS: Though local hospitals experienced a dramatic increase in trauma patient volume, overall mortality for trauma patients did not significantly change after MLK closed.
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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) | 0.000 | 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".