STOCHASTIC SIMULATION MODEL DEVELOPMENT FOR COVID-19 HOSPITALIZATION

ABSTRACT

In this paper, the group developed a stochastic simulation model for Healthcare System management during the COVID-19 pandemic. The model focuses on the Emergency Department (ED) from the diagnosis of patient arrivals with COVID-19 to the death or discharge of the patient from the hospital. It also considers the fact that once admitted and initial tests are conducted, patients who are assigned to a bed in the Intensive Care Unit (ICU) or a Regular Impatient Bed will often switch between the 2 as their condition improves or worsens. The patients who have the most serious cases of COVID-19 will be placed in ICU beds which are the bottleneck to hospitals effectively saving COID-19 patients due to their low resource capacity. As a result, the model focuses heavily on utilizing ICU beds most effectively. This model was developed with the purpose of aiding Hospitals in minimizing COVID deaths with the optimal allocation of resources with a focus on ICU beds. Our results showed that at least 90 ICU are needed to serve the same amount of arrival for COVID-19 patients without any wait time. Since the model can be applied to a variety of different hospital’s situation, it can be used by hospital manager’s find out their possible capacity and solutions to improve services.