The role of palliative care nurse practitioner in promoting end-of-life care in residential care facilities
Bibliographic record
Abstract
Background and objective: The neglect of older people at the end of life in residential care documented in the Australian Royal Commission into Aged Care and Quality and Safety mandates urgent solutions to improve care. This integrative literature review aimed to explore the potential role of the palliative care nurse practitioner (PC-NP) in promoting quality end of life in residential care.Methods: Databases Medline, Emcare, PsychINFO and CINAHL were searched from January 2010 to April 2022. Full text of primary articles meeting inclusion criteria encompassing residents living in residential care settings, the role of the PC-NP in supporting quality dying were obtained and independently screened to determine final studies for review. Findings were thematically analysed. Two reviewers independently extracted data and assessed level of evidence and quality ratings for both quantitative and qualitative studies.Results: Of 12 articles meeting eligibility criteria, four specifically focused on the PC-NP or the palliative care nurse in residential care, seven examined the generic nurse practitioner role, and one the aged care nurse role in supporting palliative care. Themes common to all roles including positive patient outcomes, advance care planning, hospital avoidance, staff education and enhanced communication with families. Themes specific to the PC-NP included meeting end-of-life needs, end-of-life prescribing, and enhancing the role of the General Practitioner.Conclusions: Although reflected in only a handful of studies, this integrative review has provided preliminary insights into potential contributions of the PC-NP to quality end-of-life care for residential care 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 | 0.013 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".