Objectives. The time emergency department (ED) patients spend from presentation to admittance is known as their length of stay (LOS). This study aimed to quantify the inpatient occupancy rate (InptOcc)/ED LOS relationship and develop a methodology for identifying resource-allocation triggers using InptOcc-LOS association-curve inflection points. Methods. This study was conducted over 200 consecutive days at a 700-bed hospital with an annual ED census of approximately 50,000 using multivariate spline (piecewise) regression to model the InptOcc/LOS relationship while adjusting for confounding covariates. Nonlinear modeling was used to assess for InptOcc/LOS associations and determine the inflection point where InptOcc profoundly impacted LOS. Results. At lower InptOcc, there was no association. Once InptOcc reached ≥88%, there was a strong InptOcc/LOS association; each 1% InptOcc increase predicted a 16-minute (95% CI, 12–20 minutes) LOS prolongation, while the confounder-adjusted analysis showed each 1% InptOcc increase >89% precipitating a 13-minute (95% CI, 10–16 minutes) LOS prolongation. Conclusions. The study hospital’s InptOcc was a significant predictor of prolonged ED LOS beyond the identified inflection point. Spline regression analysis identified a clear inflection point in the InptOcc-LOS curve that potentially identified a point at which to optimize inpatient bed availability to prevent increased costs of prolonged LOS. 1. Background One of the most important emergency department (ED) operations parameters is the time that patients who are ultimately admitted to the hospital spend in the ED from presentation to transfer to a hospital bed. This parameter, the ED length of stay for admitted patients (hereafter, LOS), has both direct and indirect importance. LOS’ intrinsic importance is related to the fact that shorter LOS translates into improved effective ED care capacity: more patients can be seen in a given timeframe if patient LOS is decreased. In addition to its intrinsic importance, LOS is also important for indirect reasons (e.g., improved patient satisfaction, lower morbidity/mortality, and overall costs of care) [1, 2]. A recent overview of the literature addressing ED operations and performance measures concluded that LOS and related time frames were the most recommended performance measures to follow quality, efficiency, and sustainability of ED operations . A critical consideration of LOS is its impact on the rate of patients who left-without-being-seen (LWBS). Previous work has confirmed that at our hospital (as is the case at
S. W. Liu, S. H. Thomas, J. A. Gordon, A. G. Hamedani, and J. S. Weissman, “A pilot study examining undesirable events among emergency department-boarded patients awaiting inpatient beds,” Annals of Emergency Medicine, vol. 54, no. 3, pp. 381–385, 2009.
C. M. S？rup, P. Jacobsen, and J. L. Forberg, “Evaluation of emergency department performance—a systematic review on recommended performance and quality-in-care measures,” Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine, vol. 21, no. 1, article 62, 2013.
M. Kennedy, C. E. MacBean, C. Brand, V. Sundararajan, and D. M. Taylor, “Review article: leaving the emergency department without being seen,” Emergency Medicine Australasia, vol. 20, no. 4, pp. 306–313, 2008.
M. McHugh, K. J. Van Dyke, E. Howell, F. Adams, D. Moss, and J. Yonek, “Changes in patient flow among five hospitals participating in a learning collaborative,” Journal for Healthcare Quality, vol. 35, pp. 21–29, 2013.
V. W. Tsai, G. Q. Sharieff, J. T. Kanegaye, L. A. Carlson, and J. Harley, “Rapid medical assessment: improving pediatric emergency department time to provider, length of stay, and left without being seen rates,” Pediatric Emergency Care, vol. 28, no. 4, pp. 354–356, 2012.
S. K. Polevoi, J. Jewel Shim, C. E. McCulloch, B. Grimes, and P. Govindarajan, “Marked reduction in length of stay for patients with psychiatric emergencies after implementation of a comanagement model,” Academic Emergency Medicine, vol. 20, no. 4, pp. 338–343, 2013.
J. Jweinat, P. Damore, V. Morris, R. D'Aquila, S. Bacon, and T. J. Balcezak, “The safe patient flow initiative: a collaborative quality improvement journey at Yale-New Haven Hospital,” Joint Commission Journal on Quality and Patient Safety/Joint Commission Resources, vol. 39, pp. 447–459, 2013.
B. Ortiga, A. Salazar, A. Jovell, J. Escarrabill, G. Marca, and X. Corbella, “Standardizing admission and discharge processes to improve patient flow: a cross sectional study,” BMC Health Services Research, vol. 12, no. 1, article 180, 2012.
M. Abir, M. M. Davis, P. Sankar, A. C. Wong, and S. C. Wang, “Design of a model to predict surge capacity bottlenecks for burn mass casualties at a large academic medical center,” Prehospital and Disaster Medicine, vol. 28, no. 1, pp. 23–32, 2013.
R. D. Kearns, K. M. Conlon, A. L. Valenta et al., “Disaster planning: the basics of creating a burn mass casualty disaster plan for a burn center,” Journal of Burn Care and Research, vol. 35, no. 1, pp. e1–e13, 2013.
S. Braithwaite, B. Friedman, R. Mutter, and M. Handrigan, “Microsimulation of financial impact of demand surge on hospitals: the H1N1 influenza pandemic of fall 2009,” Health Services Research, vol. 48, no. 2, pp. 735–752, 2013.
D. A. Bradt, P. Aitken, G. FitzGerald, R. Swift, G. O'Reilly, and B. Bartley, “Emergency department surge capacity: recommendations of the Australasian surge strategy working group,” Academic Emergency Medicine, vol. 16, no. 12, pp. 1350–1358, 2009.