Ten-year trends in direct costs of asthma: a population-based study
Bibliographic record
Abstract
INTRODUCTION: There is little information on recent trends in the economic burden of asthma. Our objective was to estimate the excess costs of asthma and their trend in British Columbia, Canada, from 2002 to 2011. METHODS: A retrospective cohort of individuals aged 5-55 years was constructed from the provincial administrative health databases, consisting of patients with physician-diagnosed asthma and a propensity-score-matched comparison sample from the general population. Total direct medical costs were calculated as the sum of hospitalizations, outpatient visits and medication costs, adjusted to 2012 Canadian dollars ($). Excess costs were defined as the difference in costs between the asthma and comparison groups. RESULTS: A total of 341 457 individuals (mean age at entry 27.3, 54.1% female) were equally divided into the asthma and comparison groups. Excess costs in patients with asthma were $1028.0 (95% CI $982.7-$1073.4) per patient-year (PY). Medications contributed to the greatest share of excess costs ($471.7/PY), whereas hospitalization and outpatient costs were, respectively, $272.2/PY and $284.1/PY. Only $192.9/PY was attributable to asthma itself. There was a 2.9%/year increase in excess costs (P < 0.001), a combination of asthma-attributable costs declining by 0.8%/year while nonasthma excess costs increasing by 3.8%/year. The most dramatic trend was observed in asthma-related outpatient costs, which decreased by %6.6/year. CONCLUSIONS: A significant share of excess costs in asthma is not attributable to the disease itself. The pattern of costs changed significantly during the study period. The burden of comorbid conditions should be considered in developing evidence-based policies for management of patients with asthma.
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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 | 0.005 |
| Science and technology studies | 0.001 | 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".