The Effect of Medicaid Expansion in New York State on Use of Subspecialty Surgical Procedures by Medicaid Beneficiaries and the Uninsured
Bibliographic record
Abstract
BACKGROUND: Understanding the benefits of Medicaid is crucial as states decide whether to expand Medicaid under the Patient Protection and Affordable Care Act. We used the 2001 Medicaid expansion in New York to evaluate changes in use by Medicaid beneficiaries and the uninsured of breast cancer reconstruction, panniculectomy, and lower-extremity trauma management. METHODS: Data for all patients 19 to 64 years old having undergone the selected procedures between 1998 and 2006 were obtained from the State Inpatient Database. We used an interrupted time series using variance weighted least squares regression to evaluate the effect of Medicaid expansion on the probability that Medicaid beneficiaries or uninsured patients received the procedures. We also determined the predicted use had there been no expansion. New York Census data were used for population-adjusted case-volume calculations. RESULTS: Likelihood of Medicaid as the primary payer increased significantly after expansion, 0.34% per quarter (95% CI, 0.28-0.40), without a decrease in uninsured patients receiving these procedures. This resulted in a 7.2% increase in the proportion of Medicaid beneficiaries receiving these procedures, an additional 1.9 Medicaid cases per quarter per 100,000 New York residents. In subgroup analysis, the proportion of Medicaid beneficiaries increased for breast reconstruction (0.28% per quarter; 95% CI, 0.21-0.35) and panniculectomy (0.19% per quarter; 95% CI, 0.1-0.28) without a decrease for the uninsured. Lower-extremity trauma procedures had a decreasing trend in use by uninsured patients with a slight increase for Medicaid beneficiaries (not significant). CONCLUSIONS: Subspecialty surgeons responded to expansion by increasing volume of procedures for Medicaid beneficiaries. This occurred without decline in care for the uninsured, suggesting that Medicaid expansion resulted in increased access for underserved patients. Although more patients received needed care once they had coverage, subgroup analysis identified persistence of additional barriers to use of certain surgical services.
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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 | 0.004 | 0.002 |
| 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 | 0.001 |
| 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".