Tackling the demand for emergency department services: there are no silver bullets
Bibliographic record
Abstract
A concern among ED service providers is that patient volumes and acuity are outpacing resources, prompting them to find ways to improve efficiency to meet service demands. In this issue of the Journal, Leung and colleagues1 introduce physician navigators as a novel strategy to increase emergency physician efficiency at a regional hospital in Ontario. The role of the navigator is to provide the ED physician with clerical support and assist in other organisational tasks, and their use led to an improvement in patient turnover at the study centre. The results of this study are intuitive. A physician is limited in what he or she can do at any one time, and thus, some tasks must be completed serially. The availability of a navigator means that the physician can delegate non-clinical tasks so that he or she can effectively do two things at once. Thus, improved time-related outcomes are in keeping with the clinical process change instituted in this study. However, the physician is only part of the barrier to ED flow. Delays in registration and triage, or in other programmes such as radiology, laboratory and inpatient units may also …
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.050 | 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 teacher head, 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".