Understanding the roles and work of paramedics in primary care: a national cross-sectional survey
Bibliographic record
Abstract
OBJECTIVES: This research aimed to fill a current knowledge gap, namely the current scope of clinical role of paramedics in primary care, in relation to specific constructs such a level of education and clinical experience. SETTING: The survey was distributed to paramedics in primary care across the UK through the College of Paramedics. PARTICIPANTS: A total of 341 surveys were returned (male=215). 90% of responses were from paramedics in England, 1.7% from paramedics in Northern Ireland, 4.6% from paramedics in Scotland and 2.9% from paramedics in Wales. This represents approximately 33% of the primary care paramedic workforce in England and Wales. Estimates for percentages in Northern Ireland and Scotland are unavailable due to the lack of workforce datasets capturing paramedics in primary care. RESULTS: Considerable variation was found in job titles, level of education and provision of clinical supervision of paramedics in primary care. Differing levels of practice were noted, despite guidance documents that attempt to standardise the role. Statistical analysis of quantitative data highlighted that relationships exist between paramedic clinical exposure in primary care, level of education, and ability of independently prescribe medicines and the extent to which clinical presentations are seen and examinations performed. However, free-text responses indicated that challenges in relation to access to further education and clinical supervision to support clinical development resulted in frustration for paramedics who work in this setting. CONCLUSIONS: As well as offering an insight into the demographics of the primary care paramedic work force, there is indication of the clinical scope of role undertaken in this setting. Based on our findings, we recommend changes to education and support, governance and legislation to ensure paramedics employed in primary care can work to achieve the full extent of their professional capability.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".