Temporal trends in emergency department volumes and crowding metrics in a western Canadian province: a population-based, administrative data study
Bibliographic record
Abstract
BACKGROUND: Emergency Department (ED) crowding is a pervasive problem, yet there have been few comparisons of the extent of, and contributors to, crowding among different types of EDs. The study quantifies and compares crowding metrics for 16 high volume regional, urban and academic EDs in one Canadian province. METHODS: The National Ambulatory Care Reporting System (NACRS) provided ED presentations by adults to 16 high volume Alberta EDs during April 2010 to March 2015 for this retrospective cohort study. Time to physician initial assessment (PIA), length of stay (LOS) for discharges and admissions were grouped by start hour of presentation and facility. Multiple crowding metrics were created by taking the means, medians (PIA-M, LOS-M), and 90th percentiles of the hourly, ED-specific values. Similarly, proportion left against medical advice (LAMA) and proportion left without being seen (LWBS) were day and ED aggregated. Calculated based on the start of the presentation and the facility and for PIA and LOS. The mean, median, and 90th percentiles for the date and time ED-specific metrics for PIA and LOS were obtained. Summary statistics were used to describe crowding metrics. RESULTS: There were 3,925,457 presentations by 1,420,679 adults. The number of presentations was similar for each sex and the mean age was 46 years. Generally, the three categories of EDs had similar characteristics; however, urban and academic/teaching EDs had more urgent triage scores and a higher percentage of admissions than regional EDs. The median of the PIA-M metric was 1 h23m across all EDs. For discharges, the median of the LOS-M metric was 3h21m whereas the median of the LOS-M metric for admissions was 10h08m. Generally, regional EDs had shorter times than urban and academic/teaching EDs. The median daily LWBS was 3.4% and the median daily LAMA was about 1%. CONCLUSIONS: Emergency presentations have increased over time, and crowding metrics vary considerably among EDs and over the time of day. Academic/teaching EDs generally have higher crowding metrics than other EDs and urgent action is required to mitigate the well-known consequences of ED crowding.
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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 | 0.001 | 0.003 |
| 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".