<p>Cost-effectiveness of the COPD Patient Management European Trial home-based disease management program</p>
Bibliographic record
Abstract
Purpose: Efficient management of COPD represents an international challenge. Effective management strategies within the means of limited health care budgets are urgently required. This analysis aimed to evaluate the cost-effectiveness of a home-based disease management (DM) intervention vs usual management (UM) in patients from the COPD Patient Management European Trial (COMET). Methods: Cost-effectiveness was evaluated in 319 intention-to-treat patients over 12 months in COMET. The analysis captured unplanned all-cause hospitalization days, mortality, and quality-adjusted life expectancy. Costs were evaluated from a National Health Service perspective for France, Germany, and Spain, and in a pooled analysis, and were expressed in 2015 Euros (EUR). Quality of life was assessed using the 15D health-related quality-of-life instrument and mapped to utility scores. Results: Home-based DM was associated with improved mortality and quality-adjusted life expectancy. DM and UM were associated with equivalent direct costs (DM reduced costs by EUR -37 per patient per year) in the pooled analysis. DM was associated with lower costs in France (EUR -806 per patient per year) and Spain (EUR -51 per patient per year), but higher costs in Germany (EUR 391 per patient per year). Evaluation of cost per death avoided and cost per quality-adjusted life year (QALY) gained showed that DM was dominant (more QALYs and cost saving) in France and Spain, and cost-effective in Germany vs UM. Nonparametric bootstrapping analysis, assuming a willingness-to-pay threshold of EUR 20,000 per QALY gained, indicated that the probability of home-based DM being cost-effective vs UM was 87.7% in France, 81.5% in Spain, and 75.9% in Germany. Conclusion: Home-based DM improved clinical outcomes at equivalent cost vs UM in France and Spain, and in the pooled analysis. DM was cost-effective in Germany with an incremental cost-effectiveness ratio of EUR 2,541 per QALY gained. The COMET home-based DM intervention could represent an attractive alternative to UM for European health care payers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".