One-year treatment costs of trauma care in the USA
Bibliographic record
Abstract
Although injuries are a leading cause of morbidity and mortality in the USA, few prior studies exist on the costs of trauma care. This article estimates treatment costs of care for 12 months following injury. Primary and secondary data were collected on over 5000 moderate-to-severely injured patients 18-84 years of age discharged from 69 US hospitals. Acute and post-acute costs of care were estimated from a combination of data sources: UB92 hospital bills, patient surveys, medical record abstracts, and where available, Medicare claims. Key analysis variables were demographic characteristics, insurance status and nature and severity of injury. Mean 1-year cost per patient of trauma care in our population was $75,210. On average, 58% of cost was accounted for by the index hospitalization. Total 1-year treatment cost of adult major trauma in the USA was conservatively estimated to be US$27 billion annually (2005).
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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 | 0.000 |
| 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) | 0.001 | 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 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".