Projected Financial Impact of Noncoverage of Elective Circumcision by Louisiana Medicaid in Boys 0 to 5 Years Old
Bibliographic record
Abstract
PURPOSE: Several states, including Louisiana since 2005, no longer cover elective circumcision under Medicaid programs. The recent AAP (American Academy of Pediatrics) policy statement recognizes the medical benefits of circumcision and recommends the removal of financial barriers to this procedure. Cost savings are a factor in the limitation of circumcision coverage, although to our knowledge the actual cost savings to Medicaid programs have not been reported. We analyzed the number of circumcisions performed before and after the policy change to determine an accurate cost of such procedures and whether the increased procedure expense mitigates the initial savings. MATERIALS AND METHODS: We analyzed the number of neonatal and nonneonatal circumcisions in boys 0 to 5 years old to determine trends during the selected period. A cost model for each procedure was created. Neonatal procedure cost was based on professional fees. Nonneonatal procedure cost was based on professional (surgeon and anesthesia) plus facility fees. The number and cost of procedures were compared before (2002 to 2004) and after (2006 to 2010) the policy change. Linear regression was used to predict future costs. RESULTS: The average annual number and expense of neonatal circumcisions were significantly decreased after the policy change. There was no significant decrease in nonneonatal procedures and expense. Cost per procedure ranged from $88.34 for neonatal to $486.76 for nonneonatal circumcision. Secondary to the increasing number of more costly nonneonatal procedures, the annual expense was predicted to exceed pre-policy levels by 2015. CONCLUSIONS: The number of nonneonatal circumcisions is increasing and such procedures place a higher financial burden on the health care system. As a result, the financial benefits of noncoverage of elective circumcision are decreasing.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".