Inclusion of palliative care in health care policy for older people: A directed documentary analysis in 13 of the most rapidly ageing countries worldwide
Bibliographic record
Abstract
BACKGROUND: Palliative care is insufficiently integrated in the continuum of care for older people. It is unclear to what extent healthcare policy for older people includes elements of palliative care and thus supports its integration. AIM: (1) To develop a reference framework for identifying palliative care contents in policy documents; (2) to determine inclusion of palliative care in public policy documents on healthcare for older people in 13 rapidly ageing countries. DESIGN: Directed documentary analysis of public policy documents (legislation, policies/strategies, guidelines, white papers) on healthcare for older people. Using existing literature, we developed a reference framework and data extraction form assessing 10 criteria of palliative care inclusion. Country experts identified documents and extracted data. SETTING: Austria, Belgium, Canada, Czech Republic, England, Japan, Mexico, Netherlands, New Zealand, Singapore, Slovenia, South Korea, Spain. RESULTS: Of 139 identified documents, 50 met inclusion criteria. The most frequently addressed palliative care elements were coordination and continuity of care (12 countries), communication and care planning, care for family, and ethical and legal aspects (11 countries). Documents in 10 countries explicitly mentioned palliative care, nine addressed symptom management, eight mentioned end-of-life care, and five referred to existing palliative care strategies (out of nine that had them). CONCLUSIONS: Health care policies for older people need revising to include reference to end-of-life care and dying and ensure linkage to existing national or regional palliative care strategies. The strong policy focus on care coordination and continuity in policies for older people is an opportunity window for palliative care advocacy.
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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 | 0.102 | 0.206 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.039 | 0.071 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".