Common care practices among effective community-based specialist palliative care teams: a qualitative study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: Evidence has shown that, despite wide variation in models of care, community-based specialist palliative care teams can improve outcomes and reduce acute care use at end of life. The goal of this study was to explore similarities in care practices among effective and diverse specialist teams to inform the development of other community-based teams. METHODS: Interviews with 78 providers and administrators from 11 distinct community-based specialist palliative care teams from Ontario, Canada were conducted. Interviews were audio-recorded, transcribed and analysed using an inductive approach to identify common themes. RESULTS: 3 key themes across all teams emerged. First, the distinct models of care were generally summarised into 3 models: primary care and specialist providers either collaborated by transferring, sharing or consulting in care. Second, teams explicitly or implicitly followed 7 common care practices related to: specialised expertise 24/7; intrateam communication; timeliness; physical symptom and psychosocial-spiritual management; education; peace and fulfilment; and advocacy for patient preferences. Third, all teams emphasised the importance of team building, even more than using clinical tools and processes. CONCLUSIONS: Despite wide variation in models of care among community-based specialist palliative care teams, this large qualitative study identified several common themes in care practices that can guide the development of other teams.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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 it