Palliative care nursing roles in the acute inpatient setting: A scoping review
Bibliographic record
Abstract
AIM: This study aimed to explore the many roles of palliative care (PC) nurses in addressing the needs of patients with life-limiting illnesses in the acute inpatient setting in New Zealand. METHODS: A scoping review was undertaken, informed by the Joanna Briggs Institute guidelines and utilizing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. In December 2024, a comprehensive search using Pubmed, Scopus, and CINAHL was conducted for peer-reviewed articles published in English between the years 2014 and 2024, with full text available, that focused on PC nursing in the acute setting in New Zealand, Australia, Canada, Ireland, or the United Kingdom. These countries were chosen because their health care systems are similar. Citation searches were undertaken. Grey literature from New Zealand hospitals was also searched. RESULTS: After selection, 25 pieces of literature were eligible for the review. Nine key areas were found where PC nurses and teams play key roles in the ongoing management of patients and their coordination of care within the last months to last days of life in the acute inpatient setting. The areas were care-coordination, communication facilitation, decision-making, goals and expectations, discharge planning, physical symptom management, holistic symptom management, finances, environment, education, and rapid review. The findings suggest that PC nurses in the acute setting are no longer involved in single episodes of symptom management and ward-based end-of-life nursing, but are responsible for multiple facets of care, facilitated across several different services. SIGNIFICANCE OF RESULTS: Understanding the complex roles involved in PC nursing can impact the health care outcomes of patients with a life-limiting illness. The scoping review can help inform future staffing requirements and the skill mix and knowledge levels required to provide timely and appropriate PC in the acute environment in New Zealand hospitals.
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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 | 0.017 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.013 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.003 |
| 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".