The direct costs of overdiagnosed asthma in a longitudinal population-based study
Bibliographic record
Abstract
ABSTRACT Objectives A current diagnosis of asthma cannot be objectively confirmed in many patients with physician-diagnosed asthma. Estimates of resource use in overdiagnosed cases of asthma are necessary to measure the burden of overdiagnosis and evaluate strategies to reduce this burden. We assessed the difference in asthma-related healthcare resource use between patients with a confirmed asthma diagnosis and those with asthma ruled out. Design Population-based prospective cohort study. Setting Participants were recruited through random-digit dialling of both landlines and mobile phones in BC, Canada. Participants We included 345 individuals ≥12 years of age with a self-reported physician diagnosis of asthma which was confirmed by a bronchodilator reversibility or methacholine challenge test at the end of the 12-month follow-up. Primary and secondary outcome measures Self-reported annual asthma-related direct healthcare costs (2017 Canadian dollars), outpatient physician visits, and medication use from the Canadian healthcare system perspective. Results Asthma was ruled out in 86 (24.9%) participants. Average annual asthma-related direct healthcare costs for participants with confirmed asthma were $497.9 (SD $677.9), and $307.7 (SD $424.1) for participants with asthma ruled out. In the adjusted analyses, a confirmed diagnosis was associated with higher direct healthcare costs (Relative Ratio [RR]=1.60, 95%CI 1.14-2.22), increased rate of specialist visits (RR=2.41, 95%CI 1.05-5.40) and reliever medication use (RR=1.62, 95%CI 1.09-2.35), but not primary care physician visits (p=0.10) or controller medication use (p=0.11). Conclusions A quarter of individuals with a physician diagnosis of asthma did not have asthma after objective re-evaluation. These participants still consumed a significant amount of asthma-related healthcare resources. The population-level economic burden of asthma overdiagnosis could be substantial. Strengths and limitations of this study Participants were recruited through random sampling of the general population in the province of British Columbia. Asthma diagnosis was confirmed or ruled out using sequential guideline-recommended objective airway tests. Healthcare resource use was self-reported, potential recall bias may have led to reduced accuracy. The study was unable to evaluate the indirect costs of overdiagnosis or the cost-savings from correcting the diagnosis. The generalizability of the results may be limited by regional differences in medical costs and practices.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".