Acute care utilization for ambulatory care–sensitive conditions among publicly insured children
Bibliographic record
Abstract
BACKGROUND: Although characteristics of preventable hospitalizations for ambulatory care-sensitive conditions (ACSCs) have been described, less is known about patterns of emergency and other acute care utilization for ACSCs among children who are not hospitalized. We sought to describe patterns of utilization for ACSCs according to the initial site of care and to determine characteristics associated with seeking initial care in an acute care setting rather than in an office. A better understanding of the sequence of health care utilization for ACSCs may inform efforts to shift care for these common conditions to the medical home. METHODS: We performed a retrospective analysis of pediatric encounters for ACSCs between 2017 and 2019 using data from the IBM Watson MarketScan Medicaid database. The database includes insurance claims for Medicaid-insured children in 10 anonymized states. We assessed the initial sites of care for ACSC encounters, which were defined as either acute care settings (emergency or urgent care) or office-based settings. We used generalized estimating equations clustered on patient to identify associations between encounter characteristics and the initial site of care. RESULTS: Among 7,128,515 encounters for ACSCs, acute care settings were the initial site of care in 27.9%. Diagnoses with the greatest proportion of episodes presenting to acute care settings were urinary tract infection (52.0% of episodes) and pneumonia (44.6%). Encounters on the weekend (adjusted odds ratio [aOR] 6.30, 95% confidence interval [CI] 6.27-6.34 compared with weekday) and among children with capitated insurance (aOR 1.55, 95% CI 1.54-1.56 compared with fee for service) were associated with increased odds of seeking care first in an acute care setting. CONCLUSIONS: Acute care settings are the initial sites of care for more than one in four encounters for ACSCs among publicly insured children. Expanded access to primary care on weekends may shift care for ACSCs to the medical home.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".