Role of the nurse practitioner in providing palliative care in long-term care homes
Bibliographic record
Abstract
AIM: The purpose of this study, which was part of a large national case study of nurse practitioner (NP) integration in long-term care (LTC), was to explore the NP role in providing palliative care in LTC. METHODS: Using a qualitative descriptive design, data was collected from five LTC homes across Canada using 35 focus groups and 25 individual interviews. In total, 143 individuals working in LTC participated, including 9 physicians, 20 licensed nurses, 15 personal support workers, 19 managers, 10 registered nurse team managers or leaders, 31 allied health care providers, 4 NPs, 14 residents, and 21 family members. The data was coded and analysed using thematic analysis. FINDINGS: NPs provide palliative care for residents and their family members, collaborate with other health-care providers by providing consultation and education to optimise palliative care practices, work within the organisation to build capacity and help others learn about the NP role in palliative care to better integrate it within the team, and improve system outcomes such as accessibility of care and number of hospital visits. CONCLUSIONS: NPs contribute to palliative care in LTC settings through multifaceted collaborative processes that ultimately promote the experience of a positive death for residents, their family members, and formal caregivers.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".