Modeling Emergency Department crowding: Restoring the balance between demand for and supply of emergency medicine

Abstract

Emergency Departments (EDs) worldwide are confronted with rising patient volumes causing significant strains on both Emergency Medicine and entire healthcare systems. Consequently, many EDs are in a situation where the number of patients in the ED is temporarily beyond the capacity for which the ED is designed and resourced to manage-a phenomenon called Emergency Department (ED) crowding. ED crowding can impair the quality of care delivered to patients and lead to longer patient waiting times for ED doctor's consult (time to provider) and admission to the hospital ward. In Singapore, total ED attendance at public hospitals has grown significantly, that is, roughly 5.57% per year between 2005 and 2016 and, therefore, emergency physicians have to cope with patient volumes above the safe workload. The purpose of this study is to create a virtual ED that closely maps the processes of a hospital-based ED in Singapore using system dynamics, that is, a computer simulation method, in order to visualize, simulate, and improve patient flows within the ED. Based on the simulation model (virtual ED), we analyze four policies: (i) co-location of primary care services within the ED, (ii) increase in the capacity of doctors, (iii) a more efficient patient transfer to inpatient hospital wards, and (iv) a combination of policies (i) to (iii). Among the tested policies, the co-location of primary care services has the largest impact on patients' average length of stay (ALOS) in the ED. This implies that decanting non-emergency lower acuity patients from the ED to an adjacent primary care clinic significantly relieves the burden on ED operations. Generally, in Singapore, there is a tendency to strengthen primary care and to educate patients to see their general practitioners first in case of non-life threatening, acute illness.

Fig 1. Evolution of population size and total ED attendance in Singapore from 2005 to 2016.

Fig 2. Patient arrivals over the course of a peak day and a ‘quiet’ day in a hospital-based ED in Singapore.

Fig 3. Overall structure of patient processing in a hospital-based ED in Singapore.

Fig 4. Overall model structure of an ED in Singapore.

Fig 5. Registration and triage sub-model.

Fig 6. Critical care area sub-model.

Fig 7. Ambulatory care area sub-model.

Fig 8. Observation ward and discharge area sub-model.

Fig 9. Isolation area sub-model.