Direct healthcare costs associated with a multi-component COPD exacerbation prevention management intervention
Bibliographic record
Abstract
Background: Healthcare costs attributed to COPD have been estimated at $4.7 trillion globally in the next 30 years.With the global burden of COPD rising, identification of interventions that might lead to healthcare cost savings is an imperative.Although many studies report the effect of COPD selfmanagement interventions on patient outcomes and healthcare utilization, little data describes their effect on healthcare costs.Methods: Using data linkage and established case costing methods with provincial Canadian health databases, we established public healthcare costs (acute and community) for the twelve months following randomization for the 462 participants enrolled in our randomised controlled trial of the Program of Integrated Care for Patients with Chronic Obstructive Pulmonary Disease and Multiple Comorbidities (PIC COPD+).Results: Total median (IQR) in-hospital costs in the 12 months follow up for all (intervention and control) 462 trial participants were CAN$4,769 ($417 to $16,834) (equivalent to USD$3,566 ($312 to $12,588).Total costs incurred in the community were higher at $8,011 ($4,749 to $13,831) (equivalent to USD$5,990 ($4,749 to $10,342).Controlling for sex, income quintile, Johns Hopkins Aggregated Diagnosis Groups score, and living in an urban locality, we found lower community healthcare costs but no differences in acute care costs for participants receiving our multi-component COPD exacerbation prevention management intervention compared to usual care.Conclusions: Controlling for important confounders we found lower public community healthcare costs but no difference in acute healthcare costs with our multi-component COPD exacerbation prevention management intervention compared to usual care.Community healthcare costs were almost double those incurred compared to acute healthcare costs.Given this finding, although most COPD exacerbation management interventions generally focus on reducing the use of acute care, interventions that enable health care cost savings in the community require further exploration.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".