376 Crowding is the Strongest Predictor of Left Without Being Seen Risk in a Pediatric Emergency Department

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Emergency Department (ED) patients who leave without being seen (LWBS) are associated with adverse safety, medico-legal, patient experience, and financial consequences. While patient-level risk of LWBS has been previously tied to demographic and acuity-related factors, there is limited research linking this to ED crowding scales in the pediatric setting. The objective of this study was to determine the association between LWBS risk and two crowding scales, the National Emergency Department Overcrowding Score (NEDOCS) and occupancy rate, in the pediatric ED setting. We performed a retrospective observational study on administrative and electronic health record (EHR) data for the ED of a single quaternary care children’s hospital. The hospital saw just over 50,000 ED visits in 2019 and is verified as a Level 1 Trauma Center. All patients who presented during the 14-month study period (March 2, 2018 through May 2, 2019) were included. NEDOCS and occupancy rate were calculated for each 15-minute interval and matched to patient arrival time. We performed multiple logistic regression analyses to demonstrate the relationship between patient-level LWBS risk and NEDOCS, as well as LWBS risk and occupancy rate, controlling for demographic and acuity-related characteristics drawn from the pre-arrival state. We performed a dominance analysis using McFadden’s pseudo-R2 in order to determine the relative importance of our crowding metrics in the logistic regression models. A total of 54,890 patient encounters were included in this analysis, 1.22% of whom LWBS. Odds ratio for LWBS risk per 10-point increase in NEDOCS at individual time of arrival was 1.30 (95% CI 1.27-1.33). Odds ratio for LWBS per 10% increase in occupancy rate at individual time of arrival was 1.23 (95% CI 1.21-1.25). Area under the curve was 86.8% (95% CI 85.6%-87.9%) for the NEDOCS model and 86.6% for the occupancy rate model (95% CI 85.4%-87.8%). There was no statistically significant difference between the AUC of the two models (p-value 0.19). Dominance analysis revealed that in each model, the most important variable out of 11 studied was its respective crowding metric; NEDOCS accounted for 55.6% of predicted variance in LWBS rate in the first model while occupancy rate accounted for 53.9% of the predicted variance in LWBS in the second model. Time of day, emergency severity index, and insurance type were the next most important variables for both models, representing 10.7%, 10.2%, and 9.7%, respectively, of predicted variance in LWBS in the NEDOCS model. In this single-center study, ED crowding was the single most important factor that determined a patient’s likelihood of LWBS in the pediatric ED, accounting for over half of predicted variance. This highlights the importance of mitigating operational stress in the ED in order to deliver safe and reliable care. Previous studies have attempted to determine which crowding metric is best suited to measure operational stress in the ED; here we offer additional evidence that the simple measure of occupancy rate is non-inferior to NEDOCS, at least in the pediatric setting. Because occupancy rate and NEDOCS are available in real time, both could serve as a monitor for individual LWBS risk.