Matching Capacity to Demand: A Regional Dashboard Reduces Ambulance Avoidance and Improves Accessibility of Receiving Hospitals
Bibliographic record
Abstract
OBJECTIVES: ambulance diversion is a dangerous repercussion of emergency department (ED) crowding and can reflect fragmentation and a lack of coordination in designating optimal patient offload sites for prehospital providers. The objective of this study was to evaluate whether proactive destination selection through the Regional Emergency Patient Access and Coordination (REPAC) program would enhance capacity and ED flow management. METHODS: the REPAC system provides a dashboard that synthesizes real-time capacity and acuity data for all three adult EDs in the city of Calgary, assigning a color code to reflect receiving status. It assigns destination for the next patient transported by emergency medical services (EMS) by categorizing ED sites as having either a favorable (green/yellow) status or unfavorable (orange/red) status. Three time windows were analyzed: a 6-month window prior to REPAC implementation (pre), the first 6-month window immediately following (post1), and the second 6-month period following (post2). Primary outcomes of interest were the proportion of time spent in favorable versus unfavorable status and EMS avoidances for all adult ED sites in the region (percentage of total time with any center on EMS bypass). Information on total number of ED visits, percentage of patients arriving by EMS transports, admission rates, patient acuity (Canadian Triage and Acuity Score), age, and length of stay (LOS) for admitted and discharged patients was collected. The Kruskal-Wallis test was employed for primary outcome analysis. RESULTS: implementation of the REPAC system resulted in an increase in the proportion of total time region hospitals reported favorable status (57.5% vs. 64.1%) pre versus post1, an effect that was accentuated at 1 year (post2, 78.7%; p < 0.001 for both comparisons). There was a concomitant decrease in EMS avoidances as a result of the REPAC system, 4.4% to 1.8% (pre vs. post1), also further improved at 1 year to 0.6% (p < 0.001 for both comparisons). CONCLUSIONS: proactive EMS destination selection through a real-time integrated electronic surveillance system enhances regional capacity and flow management while significantly reducing ambulance diversions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".