The role of a rapid assessment zone/pod on reducing overcrowding in emergency departments: a systematic review
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: To evaluate the effectiveness of a rapid assessment zone (RAZ) to mitigate emergency department (ED) overcrowding. METHODS: Electronic databases, controlled trial registries, conference proceedings, study references, experts in the field and correspondence with authors were used to identify potentially relevant studies. Intervention studies, in which a RAZ was used to influence length of stay, physician initial assessment and patients left without being seen, were included. Mean differences were calculated and reported with corresponding 95% CIs; individual statistics are presented as RR with associated 95% CI. RESULTS: From 14 446 potentially relevant studies, four studies were included in the review. The quality of one study was appraised as moderately high; others were rated as weak. Two studies showed that a RAZ was associated with a reduction of 20 min (95% CI: -47.2 to 7.2) in the ED length of stay; in one non-randomised clinical trial (RCT), a 192 min reduction was reported (95% CI: -211.6 to -172.4). Physician initial assessment showed a reduction of 8.0 min; 95% CI: -13.8 to -2.2 in the RCT and a reduction of 33 min (95% CI: -42.3 to -23.6) and 18 min (95% CI: -22.2 to -13.8) respectively were found in two non-RCTs. There was a reduction in the risk of patient leaving without being seen (RCT: RR=0.93, 95% CI: 0.77 to 1.12; non-RCT: RR =0.68, 95% CI: 0.63 to 0.73). CONCLUSIONS: Although the results are consistent, and low acuity patients seem to benefit the most from a RAZ, the available evidence to support its implementation is limited.
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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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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 it