Boarding Inpatients in the Emergency Department Increases Discharged Patient Length of Stay

Background

Boarding of inpatients in the Emergency Department (ED) has been widely recognized as a major contributor to ED crowding and a cause of adverse outcomes. We hypothesize that these deleterious effects extend to those patients who are discharged from the ED by increasing their length of stay (LOS).

Study Objectives

This study investigates the impact of boarding inpatients on the ED LOS of discharged patients.

Methods

This retrospective, observational, cohort study investigated the association between ED boarder burden and discharged patient LOS over a 3-year period in an urban, academic tertiary care ED. Median ED LOS of 179,840 discharged patients was calculated for each quartile of the boarder burden at time of arrival, and Spearman correlation coefficients were used to summarize the relationship. Subgroup analyses were conducted, stratified by patient acuity defined by triage designation, and hour of arrival.

Results

Overall median discharged patient ED LOS increased by boarder burden quartile (205 [95% confidence interval (CI) 203–207], 215 [95% CI 214–217], 221 [95% CI 219–223], and 221 [95% CI 219–223] min, respectively), with a Spearman correlation of 0.25 between daily total boarder burden hours and median LOS. When stratified by patient acuity and hour of arrival (11:00 a.m.–11:00 p.m.), LOS of medium-acuity patients increased significantly by boarder burden quartile (252 [95% CI 247–255], 271 [95% CI 267–275], 285 [95% CI 95% CI 278–289], and 309 [95% CI 305–315] min, respectively) with a Spearman correlation of 0.18.

Conclusion

In this retrospective study, increasing boarder burden was associated with increasing LOS of patients discharged from the ED, with the greatest effect between 11:00 a.m. and 11:00 p.m. on medium-acuity patients. This relationship between LOS and ED capacity limitation by inpatient boarders has important implications, as ED and hospital leadership increasingly focus on ED LOS as a measure of efficiency and throughput.     

Emergency Department Surge Capacity: Recommendations of the Australasian Surge Strategy Working Group

For more than a decade, emergency medicine (EM) organizations have produced guidelines, training, and leadership for disaster management. However, to date there have been limited guidelines for emergency physicians (EPs) needing to provide a rapid response to a surge in demand. The aim of this project was to identify strategies that may guide surge management in the emergency department (ED). A working group of individuals experienced in disaster medicine from the Australasian College for Emergency Medicine Disaster Medicine Subcommittee (the Australasian Surge Strategy Working Group) was established to undertake this work. The Working Group used a modified Delphi technique to examine response actions in surge situations and identified underlying assumptions from disaster epidemiology and clinical practice. The group then characterized surge strategies from their corpus of experience; examined them through available relevant published literature; and collated these within domains of space, staff, supplies, and system operations. These recommendations detail 22 potential actions available to an EP working in the context of surge, along with detailed guidance on surge recognition, triage, patient flow through the ED, and clinical goals and practices. The article also identifies areas that merit future research, including the measurement of surge capacity, constraints to strategy implementation, validation of surge strategies, and measurement of strategy impacts on throughput, cost, and quality of care.     

Supplemented Triage and Rapid Treatment (START) Improves Performance Measures in the Emergency Department

Background: Emergency Department (ED) crowding is well recognized, and multiple studies have demonstrated its negative effect on patient care. Study Objectives: This study aimed to assess the effect of an intervention, Supplemented Triage and Rapid Treatment (START), on standard ED performance measures. The START program complemented standard ED triage with a team of clinicians who initiated the diagnostic work-up and selectively accelerated disposition in a subset of patients. Methods: This retrospective before–after study compared performance measures over two 3-month periods (September–November 2007 and 2008) in an urban, academic tertiary care ED. Data from an electronic patient tracking system were queried over 12,936 patients pre-intervention, and 14,220 patients post-intervention. Primary outcomes included: 1) overall length of stay (LOS), 2) LOS for discharged and admitted patients, and 3) the percentage of patients who left without complete assessment (LWCA). Results: In the post-intervention period, patient volume increased 9% and boarder hours decreased by 1.3%. Median overall ED LOS decreased by 29 min (8%, 361 min pre-intervention, 332 min post-intervention; p < 0.001). Median LOS for discharged patients decreased by 23 min (7%, 318 min pre-intervention, 295 min post-intervention; p < 0.001), and by 31 min (7%, 431 min pre-intervention, 400 min post-intervention) for admitted patients. LWCA was decreased by 1.7% (4.1% pre-intervention, 2.4% post-intervention; p < 0.001). Conclusions: In this study, a comprehensive screening and clinical care program was associated with a significant decrease in overall ED LOS, LOS for discharged and admitted patients, and rate of LWCA, despite an increase in ED patient volume.     

Likelihood of Reroute During Ambulance Diversion Periods in Central Maryland

Objectives. To determine the proportion of patients rerouted during ambulance diversion periods andfactors associated with reroute. Methods. A retrospective cohort design was used to examine reroute practices of prehospital providers in central Maryland in 2000. Ambulance transport anddiversion data were merged to identify transports that occurred during diversion periods. The proportion of patients rerouted when the closest hospital was on diversion was determined. Generalized estimating equation modeling identified patient, transport, andhospital factors that influenced the likelihood of reroute. Results. Central Maryland hospitals were on diversion 25% of the time in 2000, although it varied by hospital (range of 1–34%). There were 128,165 transports during the study period, of which 18,633 occurred when the closest hospital was on diversion. Of these, only 23% were rerouted. More than half of all transports during a diversion period (53%) occurred when multiple neighboring hospitals were also on diversion. The factors that influenced the likelihood of reroute the most were hospital-related factors. Large volume hospitals andhospitals that spent more time on diversion were less likely to have transports rerouted to them. Conclusions. Rerouted transports more frequently go to lower volume, less busy hospitals. However, only a small proportion of patients were rerouted. Prehospital providers have limited options because often when one hospital is on diversion, other nearby hospitals are as well. Although ambulance diversion may be an important signal of hospital distress, in this region it infrequently resulted in its intended outcome, rerouting patients to less crowded facilities.