National Emergency Department Overcrowding Scale as a Predictor for Running an In-Situ Simulation

Background In-situ simulation (ISS) is an effective method for training teams and identifying latent safety threats. Operational constraints, such as Emergency Department (ED) overcrowding, can cause simulation cancellation. Cancellation criteria have been proposed; however, there are no objective measures to predict the need to cancel simulations. A reliable cancellation predictor could allow ISS teams to reschedule prior to committing time and resources. The National Emergency Department Overcrowding Scale (NEDOCS) is a ubiquitous index utilized in EDs. We hypothesized that NEDOCS can be an objective and effective predictor of ISS cancellation. Methods This is a retrospective observational cohort study examining the relationships between NEDOCS and ISS cancellations at an urban, quaternary ED where overcrowding is common. We compared the mean NEDOCS for days when ISS was canceled (No Go) vs not canceled (Go). A two-tailed t-test was utilized to compare the means between the Go/No Go groups at ISS Start, ISS Start-minus-one hour, ISS Start-minus-two hours, and ISS Start-minus-eight hours. Results Mean NEDOCS during the study period was 138.1. The maximum NEDOCS was 286.6 There was a statistically significantly higher mean NEDOCS eight hours prior to ISS start time on days when ISS was canceled (160.6 vs 121.4, p=0.011). At one-hour prior and two-hours prior to start time, there was a non-statistically significant trend towards higher mean NEDOCS on cancellation days. The point-biserial Pearson correlation r value between NEDOCS at T-eight hours and Go/No was -0.61. The point-biserial Pearson correlation r value for all times vs Go/No Go was -0.42 (p=0.0006). Conclusion Our data suggests a statistically significant increase in NEDOCS on No Go days compared to Go days for ISS. This association was particularly strong at eight hours prior to start. This suggests that NEDOCS may help identify conditions associated with simulation cancellation the night prior, which may allow for more effective allocation of time and resources.