Modeling and optimization of resources in multi-emergency department settings with patient transfer

Centralized Ambulance Diversion Policy Using Rolling-Horizon Optimization Framework to Minimize Patient Tardiness

“…For a two-hospital system, the effect of centralized AD decision was analyzed using queuing theory [ 28 ] or game theory on queuing networks [ 8 ]. For a multi-hospital system having more than three hospitals, the capacity of the hospitals was designed to reduce AD duration from a long-term perspective using linear programming [ 1 ], the centralized AD policies were evaluated using a genetic algorithm and simulation [ 29 ], and several heuristic AD rules were developed and verified through computer simulation [ 30 , 31 ]. In addition, according to the American College of Emergency Physicians (ACEP), each EMS system must develop a cooperative diversion policy designed to identify situations of hospital resources and to regularly review and update the hospital’s diversion status [ 32 ].…”

“…Overcrowding in emergency departments (EDs) has become a primary concern in health system research recently [1][2][3][4], because it causes an increased inpatient mortality rate, cost increase for admitted patients, dissatisfaction of patients due to long waiting time and prolonged pain, violence, and unproductivity of physicians' medical workforce [3,4]. Overcrowding usually occurs when the arrival rates of patients exceed an ED's capacity [1]. However, increasing the ED capacity by adding resources, for example, the number of inpatient beds and medical staff, has limitations in terms of space and budget for many hospitals [5].…”

“…The previous studies on AD decisions were conducted in various environments, and all of them showed that AD decisions can significantly improve the performance of the EMS system from the perspective of factors such as average patient waiting time and congestion [1,14,[27][28][29][30][31]. For a single-hospital system, Ramirez-Nafarrate et al used the Markov decision process assuming the status of a neighboring hospital to be large enough to not be affected by diverted patients, that is, the time to start treatment at the neighboring hospital was assumed to follow a stationary distribution or as a constant [27].…”

Methodological Approaches to Support Process Improvement in Emergency Departments: A Systematic Review

“…Similar objectives were pursued by Bordoloi and Beach [151] who, unlike the previous work, used optimization models encompassing the entire patient journey within the ED. Single OR-based approaches are also extensively used in Ajmi et al [83], Derni et al [87], Leo et al [153], Meng et al [152], Nezamoddini and Khasawneh [154], and Oueida et al [96]. Other non-hybrid methods that have been employed for tackling this ED deficiency are as follows: REACT [91], pivot nursing [92], process redesign [94,156], regression [157,158], nurse navigator [160], Iowa model of evidence-based practice [161], CQI [81,155], and ED dashboard/reporting [98].…”

“…Other contributing studies utilizing regression are available at Hu et al [192] and Van der Veen et al [74]. Less explored single approaches include: agent-based dynamic optimization [83], process redesign [94], Fulbrook et al [160], integer programming [154], SCLP [193], and Iowa model of evidence-base practice [161]. Popovich et al [161] Iowa Model of Evidence-Based Practice Table 5.…”