Access to Orthopaedic Care for Children With Medicaid Versus Private Insurance
Bibliographic record
Abstract
BACKGROUND: It has been documented that children insured by Medicaid in California have significantly less access to orthopedic care than children with private insurance. Low Medicaid physician reimbursement rates have been hypothesized to be a major factor. The first objective of this study was to examine whether children insured by Medicaid have limited access to orthopedic care in a national sample. The second objective was to determine if state variations in Medicaid physician reimbursement rates correlate with access to orthopedic care. METHODS: Two-hundred fifty orthopedic surgeon's offices, 5 randomly chosen in each of 50 states, were telephoned. Each office called was asked to answer questions to an anonymous, disclosed survey. The survey asked whether the office accepted pediatric patients, whether they accepted children with Medicaid, and whether they limited the number of children that they accepted with Medicaid, and if so why. Each state sets its own rate of physician reimbursement rates that were collected from individual state Medicaid agencies for 3 different CPT codes. The relationship between acceptance of patients with Medicaid and the individual state's Medicaid reimbursement rate was examined. RESULTS: Children with Medicaid insurance had limited access to orthopedic care in 88 of 230 (38%) offices that treat children, and 18% (41/230) of offices would not see a child with Medicaid under any circumstances. Reimbursement rates for CPT codes widely varied by state: 99243 for an outpatient consultation (range, $20-$176.38), 99213 for an established follow-up outpatient visit (range, $6-$77.76), and 25560 for global treatment of a nondisplaced radius and ulna shaft fracture without manipulation (range, $50-$403.94). There was a statistically significant relationship between access to medical care for Medicaid patients and physician reimbursement rates for all 3 CPT codes. CONCLUSIONS: Children insured with Medicaid have limited access to orthopedic care in this nationwide sample. Medicaid physician reimbursement significantly correlates with patient access to medical care. These data may be of value in the ongoing efforts to improve access to medical care for children on Medicaid. The logical inference from this study is that increasing physician reimbursement rates will improve access. In the authors' opinion, reimbursement rates should be made higher than office overhead to effect meaningful change.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".