Piloting data linkage in a prospective cohort study of a GP referral scheme to avoid unnecessary emergency department conveyance
Bibliographic record
Abstract
BACKGROUND: UK Ambulance services are under pressure to safely stream appropriate patients away from the Emergency Department (ED). Even so, there has been little evaluation of patient outcomes. We investigated differences between patients who are conveyed directly to ED after calling 999 and those referred by an ambulance crew to a novel GP referral scheme. METHODS: This was a prospective study comparing patients from two cohorts, one conveyed directly to the ED (n = 4219) and the other referred to a GP by the on-scene paramedic (n = 321). To compare differences in patient outcomes, we include follow-up data of a smaller subset of each cohort (up to n = 150 in each) including hospital admission, history of long-term illness, previous ED attendance, length of stay, hospital investigations, internal transfers, 30-day re-admission and 10-month mortality. RESULTS: Older individuals, females, and those with minor incidents were more likely to be referred to a GP than conveyed directly to ED. Of those patients referred to the GP, only 22.4% presented at ED within 30 days. These patients were more likely to be admitted then than were those initially conveyed directly to ED (59% vs 31%). Those conveyed to ED had a higher risk of death compared to those who were referred to the GP (HR: 2.59; 95% CI 1.14-5.89), however when analyses were restricted to those who presented at ED within 30 days, there was no difference in mortality risk (HR: 1.45; 95% CI 0.58-3.65). CONCLUSIONS: Despite limited data and a small sample size, there were differences between patients conveyed directly to ED and those who were referred into GP care. Initial evidence suggests that referring individuals to a GP may provide an appropriate and safe alternative path of care. This pilot study demonstrated a need for larger scale, methodologically rigorous study to demonstrate the benefits of alternative conveyance schemes and recommend changes to the current system of urgent and emergency care.
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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 | 0.082 | 0.116 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| 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 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".