Psychotropic Medication Use in Children and Youth with Autism Enrolled in Medicaid
Bibliographic record
Abstract
Children with autism frequently present with complex mental health diagnoses and psychotropic medications are often a component of comprehensive biopsychosocial treatment plans for these conditions. The purpose of this study is to provide rates and patterns of psychotropic medication use, and predictors thereof, in children and youth with autism enrolled in Medicaid across the US. This study examined national Medicaid claims from 2008 to 2016 of all children and youth with autism ages 0-21 years enrolled in Medicaid. Psychotropic medication use was examined across several child and youth characteristics, including age, co-occurring mental health conditions, sex, and race and ethnicity. About half of children and youth with autism enrolled in Medicaid had at least one psychotropic prescription in a year, a number that decreased slightly across the study period due to decreases in the prescription of antipsychotics. As new medications for autism or co-occurring conditions are developed and deployed, and as the understanding of the characteristics of the population of children with autism evolves, studying rates of medication usage helps to understand utilization patterns and differences in access to quality care.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".