Industrial Injury Hospitalizations Billed to Payers Other Than Workers' Compensation: Characteristics and Trends by State
Bibliographic record
Abstract
OBJECTIVE: To describe characteristics of industrial injury hospitalizations, and to test the hypothesis that industrial injuries were increasingly billed to non-workers' compensation (WC) payers over time. DATA SOURCES: Hospitalization data for 1998-2009 from State Inpatient Databases, Healthcare Cost and Utilization Project, and Agency for Healthcare Research and Quality. STUDY DESIGN: Retrospective secondary analyses described the distribution of payer, age, gender, race/ethnicity, and injury severity for injuries identified using industrial place of occurrence codes. Logistic regression models estimated trends in expected payer. PRINCIPAL FINDINGS: There was a significant increase over time in the odds of an industrial injury not being billed to WC in California and Colorado, but a significant decrease in New York. These states had markedly different WC policy histories. Industrial injuries among older workers were more often billed to a non-WC payer, primarily Medicare. CONCLUSIONS: Findings suggest potentially dramatic cost shifting from WC to Medicare. This study adds to limited, but mounting evidence that, in at least some states, the burden on non-WC payers to cover health care for industrial injuries is growing, even while WC-related employer costs are decreasing-an area that warrants further research.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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; both teacher heads agree on what is shown here.
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".