The Effect of the Massachusetts Healthcare Reform on the Uninsured Rate of the Orthopaedic Trauma Population
Bibliographic record
Abstract
BACKGROUND: The 2006 Massachusetts Healthcare Reform (MHR) has resulted in health coverage for 98.1% of residents in Massachusetts. The purpose of this study was to evaluate the effect of MHR on the actual rate of uninsured individuals in the orthopaedic trauma population in the largest metropolitan area of Massachusetts. We also sought to measure the change in uncompensated care following the implementation of MHR. METHODS: We performed a retrospective review of all patients treated by the orthopaedic trauma services at three of the four level-I trauma centers in Boston from 2003 to 2010. The primary study cohort consisted of all uninsured patients, while the remaining patients were considered to have insurance. The study population was divided into two groups to compare the uninsured rate before and after MHR. Patients from 2006 to 2007 were excluded from the analysis to allow for an enrollment period in subsidized health insurance. RESULTS: A total of 16,338 patients with extremity and pelvic fractures and dislocations were treated from 2003 to 2010. There was a significant decrease in the uninsured rate from 23.8% to 14.4% following MHR (p < 0.001). The post-MHR risk of being uninsured is approximately 0.6 times the pre-MHR risk, with a 95% confidence interval of 0.56 to 0.65. There was also a reduction in the proportion of uncompensated care from 16.7% to 11.5% after MHR. CONCLUSIONS: There was an estimated 40% reduction in risk of uninsured individuals in the orthopaedic trauma population in the metropolitan Boston area following MHR. Despite a significant improvement, these results reveal a rate of uninsured individuals fivefold greater than currently reported by the state of Massachusetts and the U.S. government.
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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 | 0.003 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".