General practice palliative care: patient and carer expectations, advance care plans and place of death—a systematic review
Bibliographic record
Abstract
BACKGROUND: With an increasing ageing population in most countries, the role of general practitioners (GPs) and general practice nurses (GPNs) in providing optimal end of life (EoL) care is increasingly important. OBJECTIVE: To explore: (1) patient and carer expectations of the role of GPs and GPNs at EoL; (2) GPs' and GPNs' contribution to advance care planning (ACP) and (3) if primary care involvement allows people to die in the place of preference. METHOD: Systematic literature review. DATA SOURCES: Papers from 2000 to 2017 were sought from Medline, Psychinfo, Embase, Joanna Briggs Institute and Cochrane databases. RESULTS: From 6209 journal articles, 51 papers were relevant. Patients and carers expect their GPs to be competent in all aspects of palliative care. They valued easy access to their GP, a multidisciplinary approach to care and well-coordinated and informed care. They also wanted their care team to communicate openly, honestly and empathically, particularly as the patient deteriorated. ACP and the involvement of GPs were important factors which contributed to patients being cared for and dying in their preferred place. There was no reference to GPNs in any paper identified. CONCLUSIONS: Patients and carers prefer a holistic approach to care. This review shows that GPs have an important role in ACP and that their involvement facilitates dying in the place of preference. Proactive identification of people approaching EoL is likely to improve all aspects of care, including planning and communicating about EoL. More work outlining the role of GPNs in end of life care is required.
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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 | 0.009 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".