Characteristics and paramedic management of patients enrolled in a novel assess, see, treat and refer palliative care clinical pathway: A retrospective descriptive cohort study
Bibliographic record
Abstract
Introduction: Patients with palliative care needs seek support from paramedics in instances of unexpected worsening of symptoms associated with their primary diagnosis, but often do not desire conveyance to an emergency department. Despite this, up to one-quarter of patients with palliative care needs will experience an avoidable admission to the emergency department. British Columbia Emergency Health Services, in collaboration with Canadian Virtual Hospice and regional health authorities, developed the Palliative Care Assess, See, Treat and Refer (ASTaR) Clinical Pathway, with palliative clinical practice guidelines and education to support paramedics minimising avoidable admissions to emergency departments. Aim: To describe the paramedic management of patients enrolled in the palliative care ASTaR clinical pathway, supported by paramedic-specific education and clinical practice guidelines. Methods: This study was a retrospective descriptive cohort study of the first 100 patients enrolled by paramedics in the palliative care ASTaR clinical pathway following its introduction in October, 2019. Results: The median age of patients was 78 years (IQR 70–88), they were more often male ( n = 58) and in a private residence at the time of 911 call ( n = 91). Calls for assistance were in the work week ( n = 73), but often out of business hours ( n = 61). Primary care paramedics provided the majority of care ( n = 64), most frequently contacting paramedic specialists for clinical advice ( n = 32, 47%). The most common patient complaints were dyspnoea ( n = 25), altered conscious state ( n = 16), mobility assistance ( n = 14), and pain ( n = 13), with pharmaceutical intervention required in less than half of cases. Conclusion: Paramedics continue to play a critical role in supporting patients with palliative care needs, particularly during out-of-hours periods. When supported by robust clinical practice guidelines and integrated systems of care, this cohort study demonstrates that paramedics may be able to manage the requirements of patients with palliative care needs and their family, friends, and carers, beyond clinical care and conveyance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".