Effect of a physician assistant on quality and efficiency metrics in an emergency department
Bibliographic record
Abstract
<h3>Abstract</h3> <h3>Objective</h3> To determine the effect of a physician assistant (PA) working in a secondary care hospital emergency department (ED) on the overall performance of the ED. <h3>Design</h3> A retrospective review of ED data from April 1, 2017, to September 30, 2017. <h3>Setting</h3> Belleville General Hospital, a secondary care hospital, ED in Ontario. <h3>Participants</h3> A physician assistant, 13 emergency physicians, and 7 family physicians. <h3>Main outcome measures</h3> Overall ED performance was evaluated using metrics from the Ontario Ministry of Health and Long-Term Care: rate of patients who left without being seen, provider initial assessment time at the 90th percentile, and the average provider initial assessment time for all patients over a 6-month period. <h3>Results</h3> In the PA group, there was a lower average daily left without being seen rate (3.4% vs 5.2%; <i>P</i> < .001), a lower provider initial assessment time at the 90th percentile (3.9 hours vs 4.5 hours; <i>P</i> < .001), a lower average provider initial assessment time (114.83 minutes vs 139.46 minutes; <i>P</i> < .001), and a lower average length of stay (313.85 minutes vs 348.91 minutes; <i>P</i> < .001). <h3>Conclusion</h3> This study suggests that a PA has a statistically significant positive effect on the overall performance of an ED. Future studies should examine the effect of a PA on quality of care and hospital funding.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".