Effects Of State Insurance Mandates On Health Care Use And Spending For Autism Spectrum Disorder
Bibliographic record
Abstract
Forty-six states and the District of Columbia have enacted insurance mandates that require commercial insurers to cover treatment for children with autism spectrum disorder (ASD). This study examined whether implementing autism mandates altered service use or spending among commercially insured children with ASD. We compared children age twenty-one or younger who were eligible for mandates to children not subject to mandates using 2008-12 claims data from three national insurers. Increases in service use and spending attributable to state mandates were detected for all outcomes. Mandates were associated with a 3.4-percentage-point increase in monthly use and a $77 increase in monthly spending on ASD-specific services. Effects were larger for younger children and increased with the number of years since mandate implementation. These increases suggest that state mandates are an effective tool for broadening access to autism treatment under commercial insurance.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".