Introduction: Daily patient volume in emergency departments (ED) varies considerably between days and sites. Although studies have attempted to define "high-volume" days, no standard definition exists. Furthermore, it is not clear whether the frequency of high-volume days, by any definition, is related to the size of an ED. We aimed to determine the correlation between ED size and the frequency of high-volume days for various volume thresholds, and to develop a measure to identify high-volume days.
Methods: We queried retrospective patient arrival data including 1,682,374 patient visits from 32 EDs in 12 states between July 1, 2018-June 30, 2019 and developed linear regression models to determine the correlation between ED size and volume variability. In addition, we performed a regression analysis and applied the Pearson correlation test to investigate the significance of median daily volumes with respect to the percent of days that crossed four volume thresholds ranging from 5-20% (in 5% increments) greater than each site's median daily volume.
Results: We found a strong negative correlation between ED median daily volume and volume variability (R2 = 81.0%; P < 0.0001). In addition, the four regression models for the percent of days exceeding specified thresholds greater than their daily median volumes had R2 values of 49.4%, 61.2%, 70.0%, and 71.8%, respectively, all with P < 0.0001.
Conclusion: We sought to determine whether smaller EDs experience high-volume days more frequently than larger EDs. We found that high-volume days, when defined as days with a count of arrivals at or above certain median-based thresholds, are significantly more likely to occur in lower-volume EDs than in higher-volume EDs. To the extent that EDs allocate resources and plan to staff based on median volumes, these results suggest that smaller EDs are more likely to experience unpredictable, volume-based staffing challenges and operational costs. Given the lack of a standard measure to define a high-volume day in an ED, we recommend 10% above the median daily volume as a metric, for its relevance, generalizability across a broad range of EDs, and computational simplicity.