Characteristics of Children Enrolled in Medicaid With High-Frequency Emergency Department Use
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Some children repeatedly use the emergency department (ED) at high levels. Among Medicaid-insured children with high-frequency ED use in 1 year, we sought to describe the characteristics of children who sustain high-frequency ED use over the following 2 years. METHODS: Retrospective longitudinal cohort study of 470 449 Medicaid-insured children appearing in the MarketScan Medicaid database, aged 1-16 years, with ≥1 ED discharges in 2012. Children with high ED use in 2012 (≥4 ED discharges) were followed through 2014 to identify characteristics associated with sustained high ED use (≥8 ED discharges in 2013-2014 combined). A generalized linear model was used to identify patient characteristics associated with sustained high ED use. RESULTS: A total of 39 945 children (8.5%) experienced high ED use in 2012, accounting for 25% of total ED visits in 2012. Sixteen percent of these children experienced sustained high ED use in the following 2 years. Adolescents (adjusted odds ratio [aOR]: 1.4 [95% confidence interval: 1.3-1.5]), disabled children (aOR: 1.3 [95% confidence interval: 1.1-1.5]), and children with 3 or more chronic conditions (aOR: 2.1, [95% confidence interval: 1.9-2.3]) experienced the highest likelihood for sustaining high ED use. CONCLUSIONS: One in 6 Medicaid-insured children with high ED use in a single year experienced sustained high levels of ED use over the next 2 years. Adolescents and individuals with multiple chronic conditions were most likely to have sustained high rates of ED use. Targeted interventions may be indicated to help reduce ED use among children at high risk.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".