Persistent socioeconomic inequalities in location of death and receipt of palliative care: A population-based cohort study
Bibliographic record
Abstract
BACKGROUND: Providing equitable care to patients in need across the life course is a priority for many healthcare systems. AIM: To estimate socioeconomic inequality trends in the proportions of decedents that died in the community and that received palliative care within 30 days of death (including home visits and specialist/generalist physician encounters). DESIGN: Cohort study based on health administrative data. Socioeconomic position was measured by area-level material deprivation. Inequality gaps were quantified annually and longitudinally using the slope index of inequality (absolute gap) and relative index of inequality (relative gap). SETTING/PARTICIPANTS: A total of 729,290 decedents aged ⩾18 years in Ontario, Canada from 2009 to 2016. RESULTS: In 2016, the modelled absolute gap (corresponding 95% confidence interval) between the most- and least-deprived neighbourhoods in community deaths was 4.0% (2.9-5.1%), which was 8.6% (6.2-10.9%) of the overall mean (46.6%). Relative to 2009, these inequalities declined modestly. Inequalities in 2016 were evident for palliative home visits (6.8% (5.8-7.8%) absolute gap, 26.3% (22.5-30.0%) relative gap) and for physician encounters (6.8% (5.7-7.9%) absolute gap, 13.2% (11.0-15.3%) relative gap), and widened from 2009 for physician encounters only on the absolute scale. Inequalities varied considerably across disease trajectories (organ failure, terminal illness, frailty, and sudden death). CONCLUSION: Key measures of end-of-life care are not achieved equally across socioeconomic groups. These data can be used to inform policy strategies to improve delivery of palliative and end-of-life services.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | high |
| grok | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | high |
| opus | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | medium |
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 | 0.001 |
| 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, unvalidatedLabeled directly by 3 models reading the full record.
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".