Comparison of Health Care Utilization at the End of Life Among Patients With Cancer in Alberta, Canada, Versus Washington State
Bibliographic record
Abstract
PURPOSE: Aggressive care at the end of life (EOL) can lead to unnecessary suffering and health care costs for patients with cancer. Despite geographic proximity and cultural similarities, we hypothesize that EOL care is more intense in the United States multipayer system versus the Canadian single-payer system. We compared health care utilization at EOL among patients with cancer in Alberta, Canada, with those in Washington state in the United States. METHODS: Adult patients with American Joint Committee on Cancer stage II to IV solid tumors who died between 2014 and 2016 in Alberta and between 2015 and 2017 in Washington were identified from regional population-based cancer registries linked to treatment and hospitalization records (Alberta) and health claims from major regional insurance plans (Washington). The proportion of patients receiving chemotherapy and having multiple emergency department (ED) visits, or intensive care unit (ICU) admissions in the last 30, 60, and 90 days of life (DOL) in Alberta and Washington were determined and compared using two-sample z-test and multivariable logistic regression (α = .006 after Bonferroni correction). RESULTS: Of patients, 11,177 in Alberta and 12,807 in Washington were included. Patients were similar in age (median, 71 v 72 year), with more patients in Washington with no comorbidities. More patients in Washington were treated with chemotherapy (12.6% v 6.6%; adjusted OR [aOR], 2.74), had multiple ED visits (16.2% v 12.1%; aOR, 1.40), and ICU admissions (23.7% v 3.9%; aOR, 14.27) in the last 30 DOL. Utilization was also higher in Washington in the last 60 and 90 DOL and among those with stage IV disease and those age 65 years and older. CONCLUSION: Utilization of chemotherapy, ED visits, and ICU admissions near EOL was higher in Washington versus Alberta. Future studies to characterize drivers of aggressive EOL care may help improve cancer care for patients in the United States and Canada.
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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) | 0.000 | 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".