Resource Use in the Last 6 Months of Life Among Patients With Heart Failure in Canada
Bibliographic record
Abstract
BACKGROUND: Heart failure (HF) is a debilitating and chronic condition associated with significant morbidity and mortality. However, much less is known about end-of-life (EOL) costs among patients with HF. METHODS: To examine trends in resource use and costs during the last 6 months of life among elderly patients with HF, we evaluated data regarding all patients 65 years or older with HF who died between January 1, 2000, to December 31, 2006, in Alberta, Canada, and examined costs associated with all-cause hospitalizations, intensive care, emergency department visits, outpatient visits, physician office visits, and outpatient drugs in the 180 days before death. Overall costs and predictors of costs to the health care system were also examined. RESULTS: The study population included 33,144 patients with HF who died. The mean age at death was 83 years. The clinical profile of patients changed during the study period, with an increasing comorbidity burden over time. Between 2000 and 2006, the percentage of patients hospitalized during the last 6 months of life decreased from 84% to 76% (P<.01); and the percentage dying in hospital decreased from 60% to 54% (P<.01). In 2006, the average EOL cost was $27,983 in Canadian dollars. In multivariate analyses, increasing age was inversely associated with EOL costs and comorbid conditions were associated with higher costs. CONCLUSIONS: Resource use in the last 6 months of life among patients with HF in Alberta is changing, with a reduction in hospitalizations, in-hospital deaths, and an increase in the use of outpatient services. However, EOL costs are substantial and continue to increase.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 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".