Disparities in the Financial Burden of Children's Healthcare Expenditures
Bibliographic record
Abstract
OBJECTIVE: To examine whether income-related disparities in the burden of children's out-of-pocket health care expenditures have diminished with the expansions in public insurance for children in low-income families. DESIGN: We compared absolute financial burden (out-of-pocket expenditures per child) and relative financial burden (out-of-pocket expenditures per child as a proportion of family income) among children aged 0 to 18 years in 6 poverty level groups using the 1980 National Medical Care Utilization and Expenditure Survey and the 2000 Medical Expenditure Panel Survey. Regression models were used to assess whether disparities in financial burden diminished between 1980 and 2000. RESULTS: There were significant reductions (P<.01) in absolute burden over time for children above 200% of the federal poverty level. Relative financial burden decreased significantly (P<.01) for all of the income groups, ranging from a reduction of 36.49% for those below 100% of the federal poverty level (95% CI, -49.54% to -20.07%) to a reduction of 46.69% for those at or above 300% of the federal poverty level (95% CI, -54.43% to -37.62%). For low-income children, relative financial burden was 49.49% less with public insurance (95% CI, -66.24% to -24.35%) and 79.14% greater with private insurance (95% CI, 9.31% to 193.59%) than relative financial burden for low-income children without insurance. CONCLUSIONS: While the financial burden of children's out-of-pocket health care expenditures has decreased for all of the income groups over time, socioeconomic disparities persist. However, public insurance coverage appears to mitigate the financial burden for low-income children.
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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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".