Place of death in populations potentially benefiting from palliative care: a population-level study in 14 countries
Bibliographic record
Abstract
Background The majority of people dying from chronic diseases prefer to die at home, yet many die in hospitals. Cross-national population-level studies on the place of death are scarce although they can provide important evidence to guide the development and evaluation of public health policies for end-of-life care. We compared the place of death of populations potentially benefiting from palliative care in nine European and five non-European countries, and examined to what extent country-variation in the place of death is related to socio-demographic characteristics, cause of death and healthcare supply measures. Methods Death certificate data for all deaths of 2008 in Belgium, England, Wales, France, Italy, Mexico, Netherlands, New Zealand, Canada, Czech Republic, Hungary, South Korea, USA and Spain (Andalusia) with an underlying cause of death corresponding to the minimal palliative care subset (Rosenwax et al. 2005) were linked with regional healthcare statistics (N = 2,220,997). The main outcome measure was the place of death as registered on the death certificate. As the entire population was studied it was not needed to compute confidence intervals. Results People in potential need of palliative care died at home in 13% (Canada) to 53% (Mexico) of cases, in hospital in 25% (Netherlands) to 85% (South Korea) of cases, and in a long-term care institution in 1% (South Korea) to 35% (Netherlands) of cases. The large differences across countries in the proportion of people dying at home rather than in hospital were only partly explained by differences in age, sex, marital status, cause of death, and the density of hospital beds, long-term care beds and general practitioners per region of residence of the deceased. Conclusions Country differences in place of death in a population potentially benefiting from palliative care persisted after adjustment for differences in clinical and socio-demographic factors and measures of healthcare supply. The variation between countries may be attributable to different palliative and end-of-life care policies and practices. Key messages Based on data from 14 countries we found that among people in potential need of palliative care 13% (Canada) to 51% (Mexico) died at home and 25% (Netherlands) to 85% (South Korea) died in hospital. Differences between the 14 countries in the place of death persisted after adjustment for cause of death and socio-demographic and healthcare supply factors.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".