An international comparison of costs of end-of-life care for advanced lung cancer patients using health administrative data
Bibliographic record
Abstract
BACKGROUND: Patterns of end-of-life cancer care differ in Canada and the United States; yet little is known about differences in service-specific and overall costs. AIM: The aim of this study was to compare end-of-life costs in Ontario, Canada, and the United States, using administrative health data. DESIGN: Advanced-stage nonsmall cell lung cancer patients who died from cancer at age ⩾ 65.5 years in 2001-2005 were selected from the US Surveillance, Epidemiology, and End Results-Medicare database (N = 16,858) and the Ontario Cancer Registry (N = 8643). We estimated total and service-specific costs (2009 US dollars) in each of the last 6 months of life from the public payer perspectives for short-term and long-term survivors (lived < 180 and ⩾ 180 days post-diagnosis, respectively). Services were defined for comparisons between systems. RESULTS: Mean monthly costs increased as death approached, were higher in short-term than long-term survivors, and were generally higher in the United States than in Ontario until the month before death, when they were similar (long-term survivors: US$10,464 and US$10,094 (p = 0.53), short-term survivors US$14,455 and US$12,836 (p = 0.11), in Surveillance, Epidemiology, and End Results-Medicare and Ontario, respectively). Costs for Medicare hospice and Ontario's palliative care components were similar and increased closer to death. Inpatient hospitalization was the main cost driver with similar costs in both cohorts, despite lower utilization in the United States. The compositions of many services and costs differed. CONCLUSION: Costs for nonsmall cell lung cancer patients were slightly higher in the United States than Ontario until 1 month before death. Administrative data allow exploration and international comparisons of reimbursement policies, health-care delivery, and costs at the end of life.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".