Qualitative Validation of COPD Evidenced Care Pathways in Japan, Canada, England, and Germany: Common Barriers to Optimal COPD Care
Bibliographic record
Abstract
Background: Chronic obstructive pulmonary disease (COPD) is a major cause of morbidity and mortality worldwide. A comprehensive and detailed understanding of COPD care pathways from pre-diagnosis to acute care is required to understand the common barriers to optimal COPD care across diverse health systems. Methods: Country-specific COPD care pathways were created for four high-income countries using international recommendations and country-specific guidelines, then populated with published epidemiological, clinical, and economic data. To refine and validate the pathways, semi-structured interviews using pre-prepared discussion guides and country-specific pathway maps were held with twenty-four primary and secondary care respiratory healthcare professionals. Thematic analysis was then performed on the interview transcripts. Results: The COPD care pathway showed broad consistency across the countries. Three key themes relating to barriers in optimal COPD management were identified across the countries: journey to diagnosis, treatment, and the impact of COVID-19. Common barriers included presentation to healthcare with advanced COPD, low COPD consideration, and sub-optimal acute and chronic disease management. COVID-19 has negatively impacted disease management across the pathway but presents opportunities to retain virtual consultations. Structural factors such as insurance and short duration of appointments also impacted the diagnosis and management of COPD. Conclusion: COPD is an important public health issue that needs urgent prioritization. The use of Evidenced Care Pathways with decision-makers can facilitate evidence-based decision making on interventions and policies to improve care and outcomes for patients and reduce unnecessary resource use and associated costs for the healthcare provider/payer.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".