Acute care costs of patients admitted for management of chronic obstructive pulmonary disease exacerbations: contribution of disease severity, infection and chronic heart failure
Bibliographic record
Abstract
BACKGROUND: In 2003, chronic obstructive pulmonary disease (COPD) accounted for 46% of the burden of chronic respiratory disease in the Australian community. In the 65-74-year-old age group, COPD was the sixth leading cause of disability for men and the seventh for women. AIMS: To measure the influence of disease severity, COPD phenotype and comorbidities on acute health service utilization and direct acute care costs in patients admitted with COPD. METHODS: Prospective cohort study of 80 patients admitted to the Royal Melbourne Hospital in 2001-2002 for an exacerbation of COPD. Patients were followed for 12 months and data were collected on acute care utilization. Direct hospital costs were derived using Transition II, an activity-based costing system. Individual patient costs were then modelled to ascertain which patient factors influenced total direct hospital costs. RESULTS: Direct costs were calculated for 225 episodes of care, the median cost per admission was AU$3124 (interquartile range $1393 to $5045). The median direct cost of acute care management per patient per year was AU$7273 (interquartile range $3957 to $14 448). In a multivariate analysis using linear regression modelling, factors predictive of higher annual costs were increasing age (P= 0.041), use of domiciliary oxygen (P= 0.008) and the presence of chronic heart failure (P= 0.006). CONCLUSION: This model has identified a number of patient factors that predict higher acute care costs and awareness of these can be used for service planning to meet the needs of patients admitted with COPD.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".