High use of health services in patients with suboptimal asthma drug regimens: a population‐based assessment in British Columbia, Canada
Bibliographic record
Abstract
BACKGROUND: Despite numerous clinical guidelines on asthma management, patients often receive suboptimal drug therapy. This study identified patients who received suboptimal regimens according to the National Heart, Lung and Blood Institute (NHLBI) Guidelines for the Diagnosis and Management of Asthma in a complete population (residents of British Columbia, Canada) and determined the association between patients' regimens and utilization of healthcare services. METHODS: A total of 65,345 asthma patients were identified using provincial health service utilization data (including all respiratory-related prescription medication dispensings, physician and hospital visits) for the 2009 fiscal year. Patient-specific regimens of inhaled short-acting bronchodilators (SABA) with or without inhaled corticosteroids (ICS) were categorized as optimal or suboptimal. Logistic regression models were used to determine the association between regimen optimality and health service utilization, adjusted for socioeconomic status, prior year hospital and emergency department (ED) visits for asthma. RESULTS: Patients with suboptimal regimens had significantly greater risk of using health services than patients with optimal regimens of SABA and/or ICS. In particular, adolescents with suboptimal regimens were the most likely to have hospital admissions (odds ratio (OR) 3.8; 95% confidence interval (CI) 1.8-7.8), visit the ED (OR 2.2; 95% CI 1.6-3.1) and be high users of family physician services (OR 5.7; 95% CI 4.0-8.1) compared with patients in other age groups. CONCLUSIONS: Suboptimal regimens are associated with significantly high usage of health services. Identifying patients with suboptimal regimens and improving their medication management in accordance with asthma clinical guidelines are likely to result in lower health service utilization.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".