Tracking Emergency Department Overcrowding in a Tertiary Care Academic Institution
Why this work is in the frame
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Bibliographic record
Abstract
Despite the release of a national report describing key markers of emergency department (ED) overcrowding, limited linear data using these markers have been published. We sought to report the degree and trends of ED overcrowding in a typical academic hospital and to highlight some of the key markers of ED patient flow and care. We conducted a prospective study in a large Canadian urban tertiary care teaching hospital that receives approximately 55,000 annual adult ED visits. A database captured demographic and real-time process of care data for each patient from 2000 to 2007. Descriptive data are reported using Canadian Triage and Acuity Scale (CTAS) scores. Over the study period, the ED patient visit volume and presentation times remained predictable. Emergent cases (CTAS levels 1-2) doubled from 8 to 16.6%, and urgent cases (CTAS level 3) increased from 40.2 to 50.3%. Moreover, semi-urgent presentations (CTAS level 4) decreased from 42.4 to 28.8%, and non-urgent cases (CTAS level 5) dropped from 9.4 to 4.3%. The median wait time from triage to bed location increased from two minutes (inter-quartile range [IQR] 1, 46) in 2000 to 27 minutes (IQR 2, 110) in 2007, while the median time from bed location to physician remained constant (29 minutes in 2001 versus 28 minutes in 2007). Overall, admissions increased from 20.4 to 23%. Semi-urgent and non-urgent admissions dropped from 11.5 to 7.4% and 3.2 to 1.8%, respectively. Admitted patients "boarding" in the ED increased from 70,955 hours in 2002 to 118,741 hours in 2007, while the number of emergent and urgent patients leaving without being seen increased by more than 400%. ED overcrowding in a tertiary care hospital is primarily a result of access block due to boarding admitted patients, a situation that poses serious risks to the majority of patients who have emergent or urgent conditions that cannot be managed appropriately in the waiting room.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 it