Guideline-concordant inhaled medication use in COPD: a systematic review of definitions used in administrative health data
Bibliographic record
Abstract
Background: Assessments of guideline-discordant use of maintenance inhaled therapies for COPD in administrative health data are common but restricted by lack of patient characteristics. We systematically reviewed definitions of guideline-concordant and guideline-discordant maintenance inhaled medication use applied to administrative health data. Methods: We searched MEDLINE and Embase from January 2000 to September 2024 for studies that 1) used administrative health data to identify adults with COPD who were prescribed long-acting bronchodilators (LABDs) or inhaled corticosteroids (ICS) for outpatient treatment; 2) defined maintenance inhaled medication use as guideline-concordant and/or guideline-discordant at the patient level. We developed standardised definitions for claims data aligned with management recommendations and conducted a meta-analysis to assess the proportion of patients with guideline-concordant and guideline-discordant medication use. Results: We screened 4578 records and included 20 studies. There were 22 unique definitions of guideline-concordance or discordance, based on the Global Initiative for Chronic Obstructive Lung Disease (GOLD) recommendations. The most common measurements were 1) guideline-discordant ICS use (n=10); 2) guideline-concordant LABDs use (n=8); and 3) guideline-concordant ICS use, focusing on ICS alone (n=4) regardless of LABDs or with LABDs (n=6). Given that acute exacerbations of COPD (AECOPD) was the most commonly used criterion and aligned with recommendations, we developed an AECOPD risk-based definition. Pooled analysis showed 50% guideline-concordant LABDs use and 45% guideline-discordant ICS use across populations. Conclusions: Definitions of guideline-concordant LABDs use and guideline-discordant ICS use in administrative health data are largely congruent with GOLD. AECOPD risk-based definitions provide a generalisable approach for assessing guideline-concordance in administrative data.
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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 | 0.023 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.000 | 0.003 |
| 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 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".