Volume and Acuity of Emergency Department Visits Prior To and After COVID-19
Bibliographic record
Abstract
BACKGROUND: There are scant data regarding the change in volume and acuity of patients presenting to emergency departments (EDs) after Coronavirus Disease 2019 (COVID-19), compared with the pre-COVID-19 era. OBJECTIVE: To determine ED volumes and triage acuity prior to and after COVID-19. METHODS: We determined the volume of patients presenting to four large EDs affiliated with general, cardiac, cancer, and obstetrics hospitals, and the acuity of presenting illness (using the Canadian Triage Acuity Scale [CTAS]) for March and April 2020 and compared them with the same months in 2019 and January 2020. Together, these facilities see over 80% of the ED visits in Qatar. The first COVID-19 patient in Qatar was diagnosed on February 29, 2020. RESULTS: A total of 192,157 ED visits were recorded during the study period. There was a 20-43% overall drop in number of ED visits, with significant variability across hospitals. The Heart Hospital experienced the sharpest decline (33-89%), and the National Center for Cancer Care and Research experienced the least decline in volumes. The decline was observed across all CTAS levels, with the largest decline observed in individuals presenting with CTAS 1 and 2 (26-69% decline month by month). No increase in overall number of deaths or crude mortality rate was observed in the COVID-19 era, according to national statistics. CONCLUSIONS: Sharp declines in ED visits and the triage acuity seen in both general and specialty hospitals raise the concern that severely ill patients may not be seeking timely care, and a surge may be expected once current restrictions on movement are lifted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".