Changes in Use of Autologous and Prosthetic Postmastectomy Reconstruction after Medicaid Expansion in New York State
Bibliographic record
Abstract
BACKGROUND: With Medicaid expansion beginning in 2014, it is important to understand the effects of access to reconstructive services for new beneficiaries. The authors assessed changes in use of breast cancer reconstruction for Medicaid beneficiaries after expansion in New York State in 2001. METHODS: The authors used the State Inpatient Database for New York (1998 to 2006) for all patients aged 19 to 64 years who underwent breast reconstruction. An interrupted time series design with linear regression modeling evaluated the effect of Medicaid expansion on the proportion of breast reconstruction patients that were Medicaid beneficiaries. RESULTS: The proportion of breast reconstructions provided to Medicaid beneficiaries increased by 0.28 percent per quarter after expansion (p < 0.001), resulting in a 5.5 percent increase above predicted trajectory without expansion. This corresponds to a population-adjusted increase of 1.8 Medicaid cases per 1 million population per quarter. On subgroup analysis, there was no significant increase in the proportion of autologous reconstructions (p = 0.4); however, the proportion of prosthetic reconstructions for Medicaid beneficiaries had a significant increase of 0.41 percent per quarter (p < 0.001), resulting in a 7.5 percent cumulative increase. This indicates that 135 additional prosthetic reconstruction operations were provided to Medicaid beneficiaries within 5 years of expansion. CONCLUSIONS: Surgeons increased the volume of breast reconstructions provided to Medicaid beneficiaries after expansion. However, there are disparities between autologous and prosthetic reconstruction. If Medicaid expansion is to provide comprehensive care, with adequate access to all reconstructive options, these disparities must be addressed.
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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 | 0.001 | 0.001 |
| 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".