PP14.002 Final destination: a focus on the preferred place of death in a palliative homecare service
Bibliographic record
Abstract
Background In developed countries, patients receiving Palliative Homecare (PHC) service are more likely to discuss care preferences and fulfilment of preferred place of death (PPOD). Amid Singapore’s aging society, the Ministry of Health (MOH) is boosting palliative care in the community to enable more people to demise in their PPOD. A 2014 Lien Foundation survey on death attitudes found that over three-fourths of Singaporeans prefer home death, yet only a quarter of deaths in 2020 occurred at home. In comparison, Singapore Hospice Council (SHC) found that 55% of patients referred to PHC were able to die at home. This retrospective study aims to determine the rates of Advance Care Planning (ACP) discussion in a homecare setting, its associated rates of fulfilled PPOD, and possible reasons for unfulfilled PPOD. Methods De-identified data of 402 patients from Dover Park Hospice (DPH) homecare who demised between January and December 2022 were reviewed. 12 patients were excluded due to inconclusive data. Data of 390 patients were analysed for completed ACP discussion initiated by the homecare team, and the fulfilment of PPOD. Results ACP was initiated by the homecare team for 373 (95.6%) of 390 patients. Only 2 (0.5%) patients declined or were not ready, while the remaining 15 (3.9%) demised before the initial home visit. PPOD was fulfilled for 344 (92.2%) patients, of which 249 (72.4%) patients managed to demise at home. Conclusions Majority of patients receiving PHC have ACP discussions, which may be attributed to consistent interactions and rapport between patients and the homecare team. The rates of fulfilled PPOD home deaths are higher than the national average (72.4% vs 55%), which suggests homecare patients and families referred to PHC are well-supported at the end-of-life. Hence, building the capacity to provide PHC service in the community may improve fulfilled PPOD rates.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".