04 Paramedic perspectives towards gp referral schemes in north west england: a qualitative-observational study
Bibliographic record
Abstract
Background An innovative policy developed and implemented by a UK Ambulance Service allows paramedics to refer patients to the GP Acute Visiting Service scheme. Initial evidence suggests that using this alternate route of care can decrease hospital admission rates, increase bed availability, decrease wait time in A and Es and provide substantial savings for the NHS. However, there are many unrecognised barriers to referral that have not been captured by the quantitative analysis. The goal of this qualitative-observational study was to gain insight into the GP referral scheme from a paramedic’s perspective. Methods We observed eight paramedics throughout full shifts of 8–12 hours. Data was collected using participant demographics, researcher observations and informal semi-structured interviews. All notes were transcribed, coded and analysed using a Grounded Theory approach to identify emerging themes. Results Paramedics expressed a wide range of frustrations with the scheme, identifying the waiting time, the process and a lack of confidence, experience and training as the three major barriers to referrals. They described how they approached patients with the GP referral scheme in mind, identified common characteristics of referrals, described how the triage tool shaped their decision making and shared how they involved the patient in the decision making. They shared too their frustrations with some GP decision making, which they admitted then influenced their future decision making. Finally, they described what motivated them to refer and discussed the lack of awareness and understanding of the scheme’s impact and aims. Conclusions This study provided valuable insight into the paramedic’s perspective of the GP referral scheme. Maximising understanding of the scheme, investigating the GP’s perspective in decision making and ensuring knowledge and accountability of paramedics, GPs and the public were identified as solutions to strengthen and increase referral rates and scheme success.
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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 | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".