An overview of pharmacist roles in palliative care: a worldwide comparison
Bibliographic record
Abstract
Background.In order to fulfil the complex needs of terminally ill patients, palliative care demands an inter-professional collaborative network, including doctors, nurses, dieticians and social workers.Pharmacists in particular are essential members of this team, given the level of reliance on medications in this setting.The purpose of this review is to identify roles and services performed by palliative care pharmacists in dedicated palliative care settings worldwide and to map these findings against the Advanced Pharmacy Practice Framework.Material and methods.Quasi-systematic review.Search strategy: Google Scholar, Medline/PubMed, Scopus and Embase were searched utilizing selected MeSH terms.Results.A total of 24 sources of information were included in the review.This literature was collected from a range of countries, predominantly from the USA, UK and Australia with singular reports from Mexico, Japan, Qatar, Canada, Poland and Sweden.The literature identifies that pharmacist roles in palliative care are varied and quite extensive.Roles that were specifically tailored to the palliative setting included: aggressive symptom management (in particular pain control), deprescribing, advising on the use of complementary and alternative therapies, extemporaneous compounding of non-standard dosage forms and maintaining a timely supply of medications.Pharmacists in the UK, USA, Canada and Australia were found to perform an advanced level of practice (as their reported roles fulfilled the criteria of the majority of the domains in the APPF).However, pharmacists in other countries, in particular Mexico and Poland, did not present such an extensive scope of practice. Conclusion.The literature identifies that there are differences in the types of palliative pharmacist practice between countries, which may have varying levels of impact upon patient outcomes.As pharmacists can make significant contributions to palliative care, it is important to encourage the benchmarking of practice across different clinical settings and countries to promote a consistent and equitable practice.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".