Palliative care consultation teams in long-term care: a descriptive retrospective cohort study
Bibliographic record
Abstract
PURPOSE: Given the wide prevalence of advanced illness and frailty among residents in long-term care (LTC), a palliative approach to care can support comfort and quality of life. Yet, significant gaps exist with the provision of palliative care in LTC settings. We aim to describe a palliative care consultation team designed to address this need. METHODS: A single-centre retrospective cohort study was conducted at a LTC home in Toronto, Ontario, Canada. We included residents referred to the palliative care consultation team between February 1, 2021, to February 1, 2023, with at least six-months of follow-up time. We used a descriptive quantitative approach to examine access to the palliative care consultation team, changes to advance care plans, and hospital transfers. RESULTS: Eighty-seven residents were referred and seen by the palliative care consultation team. The mean age was 85 years, 71.3% were female, and 48.3% had three to four comorbidities. Most residents were seen once (55.2%). Among residents that died (n = 53), 41.5% were referred with greater than three months of survival time. Among residents that had advance care plans documenting "Transfer to Hospital" (n = 41) and "Full Code" status (n = 17), 53.7% adjusted to "Do Not Transfer" and 76.5% to "Do Not Resuscitate" orders, respectively. The hospitalisation rate was one per 1000 resident-year. CONCLUSIONS: At this LTC home, palliative care consultation teams represented an important service to improve the provision of palliative care particularly around facilitating advance care planning discussions. The findings of this study may inform further research on palliative care interventions for LTC residents.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".