Provider Visits for Asthma: Potential Barriers for Insured Children
Bibliographic record
Abstract
OBJECTIVE: The barriers to provider visits for asthma in insured children are not well understood. Our objective was to examine the relationship between parent, family, and child attributes and asthma visits in insured children. METHODS: This retrospective, cross-sectional analysis of 2007 Medical Expenditure Panel Survey-Household Component data included insured children 0-17 years old reported to have active asthma. We summed the number of provider visits during which asthma was treated or diagnosed to represent the frequency of asthma visits during the year. Probit models were used to estimate the relationship between parent, family, and child attributes and asthma visits. RESULTS: Seventy percent of the 542 children did not have an asthma visit during the year. Children with parents employed full time were 16 percentage points less likely to have an asthma visit than children whose parents were not working (P=.01). CONCLUSION: Many insured children go more than a year without seeing a provider for their asthma, signaling that insurance is not sufficient to guarantee children will receive asthma monitoring. The attributes related to asthma visits suggest potential barriers that providers might want to consider to increase participation in asthma visits.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.003 | 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".