Does End-of-Life Care Differ for Anglophones and Francophones? A Retrospective Cohort Study of Decedents in Ontario, Canada
Bibliographic record
Abstract
BACKGROUND: Approximately half of decedents in Ontario, Canada, receive some palliative care, but little is known about the influence of language on the nature of these services. OBJECTIVE: To examine differences between English- and French-speaking residents of Ontario in end-of-life care and outcomes (e.g., health care costs and location of death). DESIGN: A retrospective cohort study using multiple linked databases. SETTING/SUBJECTS: A population-based cohort of decedents in Ontario (2010-2013) who were living in long-term care institutions (i.e., nursing homes) or receiving home care before death (N = 25,759). Data from two regions with higher representations of Francophones were examined, with the final distribution by primary language being 75% Anglophone, 18% Francophone, and 7% other languages. RESULTS: Compared with Anglophones, Francophones were more frequent users of long-term care (47.6% vs. 37.1%) and less frequent users of home care (71.3% vs. 76.3%). In adjusted models, the number of days spent in hospital in the last 90 days of life was similar between Anglophones and Francophones, although the odds of dying in hospital were significantly higher among the latter. The mean total health care cost in the last year of life was slightly lower among French ($62,085) compared with English ($63,814) speakers. CONCLUSIONS: There are statistically significant differences in end-of-life outcomes between linguistic groups in Ontario, namely more institutionalization in long-term care, less home care use and more deaths in-hospital among Francophones (adjusted). Future research is needed to examine the cause of these differences. Strategies to ensure equitable access to quality end-of-life care are required.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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".