Healthcare cost attributable to bronchiolitis: A population-based cohort study
Bibliographic record
Abstract
OBJECTIVE: To determine 1-year attributable healthcare costs of bronchiolitis. METHODS: Using a population-based matched cohort and incidence-based cost analysis approach, we identified infants <12 months old diagnosed in an emergency department (ED) or hospitalized with bronchiolitis between April 1, 2003 and March 31, 2014. We propensity-score matched infants with and without bronchiolitis on sex, age, income quintile, rurality, co-morbidities, gestational weeks, small-for-gestational-age status and pre-index healthcare cost deciles. We calculated mean attributable 1-year costs using a generalized estimating equation model and stratified costs by age, sex, income quintile, rurality, co-morbidities and prematurity. RESULTS: We identified 58,375 infants with bronchiolitis (mean age 154±95 days, 61.3% males, 4.2% with comorbidities). Total 1-year mean bronchiolitis-attributable costs were $4,313 per patient (95%CI: $4,148-4,477), with $2,847 (95%CI: $2,712-2,982) spent on hospitalizations, $610 (95%CI: $594-627) on physician services, $562 (95%CI: $556-567)] on ED visits, $259 (95%CI: $222-297) on other healthcare costs and $35 ($27-42) on drugs. Attributable bronchiolitis costs were $2,765 (95%CI: $2735-2,794) vs $111 (95%CI: $102-121) in the initial 10 days post index date, $4,695 (95%CI: $4,589-4,800) vs $910 (95%CI: $847-973) in the initial 180 days and $1,158 (95%CI: $1,104-1213) vs $639 (95%CI: $599-679) during days 181-360. Mean 1-year bronchiolitis costs were higher in infants <3 months old [$5,536 (95%CI: $5,216-5,856)], those with co-morbidities [$17,530 (95%CI: $14,683-20,377)] and with low birthweight [$5,509 (95%CI: $4,927-6,091)]. CONCLUSIONS: Compared to no bronchiolitis, bronchiolitis incurs five-time and two-time higher healthcare costs within the initial and subsequent six-months, respectively. Most expenses occur in the initial 10 days and relate to hospitalization.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".