INTRODUCTION

Since the beginning of the COVID-19 pandemic at the start of 2020, hospital resources have been majorly constrained. Although it is more common for patient arrivals with COVID-19 to spend the majority of their hospital stay in regular impatient beds, the ICU is where hospitals are most constrained. The ICU (Intensive Care Unit) serves the most critical hospital patients and provides many with life-saving support through specialized equipment and expertly trained staff [1]. Many severe cases of COVID-19 require the use of ventilators to help patients breathe which are located in the ICU. In addition, severe patients who are at-risk of death require 1-on-1 care and constant tests and surveillance from doctors and staff. This means that in addition to requiring resources such as an ICU hospital bed and equipment, ICU patients require the attention of more nurses and doctors than those in regular impatient beds with less severe COVID-19 conditions [2]. COVID-19 ICU stays are also longer on average for COVID-19 patients than stays in regular impatient beds or stays in the ICU from typical non-COVID-19 ICU patients as it typically takes patients longer to recover from more severe cases of COVID-19. For example, a heart failure or heart attack patient will require an ICU bed and ventilation for an average of 2 days while a COVID-19 patient in the ICU will require the same treatment from anywhere to 8 to 100 days [3]. This also means that the resources in the ICU are used by a single patient for a longer period of time, meaning less resources for new arrivals.

Due to the more expensive and encompassing nature of ICU treatment, hospitals have significantly less ICU beds than impatient regular beds. Typically, a hospital dedicates 10% of its total hospital bed capacity to the ICU, while the rest is dedicated to impatient regular beds [4].

A major issue with overcrowding in ICU’s is that it can result in lower-quality care. As ICU's are stretched thin with a flux of COVID-19 cases, hospital staff must balance more patients and the same number of resources to be divided among an even larger population. Some hospitals have even begun to pull health care workers from other departments who are not trained in ICU protocols to help out.

In the past 20 years, simulation has been an important tool for hospitals as decision support systems. Before COVID-19, simulation models created for hospitals served various purposes such as the optimization of staff scheduling, resource allocation, and the minimization of patient wait times. However, such models are not of use unless the data they are developed from is accurate and representative of real-time hospital processes. The recent growth in use of simulation in the hospital setting can therefore be at least partially due to the improvement in technology and analytics that allows for a high-volume of real-time discrete data for use.

With the outbreak of COVID-19, simulation has been used in several research studies to improve hospital and government responses to the crises. One study by Xinyu Li used discrete simulation to determine the effects of several indicators on the development of the epidemic and seizure of hospital resources [5]. These indicators include the incubation period of the disease, the response speed of hospital detection, disease healing time, and population mobility. This simulation was used to predict the number of isolation beds required from the perspective of population mobility. Another 2020 study conducted by Gary E. Weissman involved the creation of a Monte Carlo simulation of 3 hospitals in order to estimate the timing of COVID-19 case surges and to determine the best and worst case scenarios on hospital capacity. This study was used to aid hospital leaders in making critical decisions about hospital operations and resource allocation during the COVID-19 pandemic [6].

In this paper, the group develops a discrete-event simulation model of an emergency department dealing with COVID-19 treatment of patients. This simulation will be used to assess the system performance of the emergency department, predict future responses, and guide decision making at the management level. We will be considering various hospital resources including nurse and doctor staff, equipment (ventilators), and hospital beds (both regular and ICU). Using anonymous hospital data about COVID-19 patient admittance and through research about typical hospital ICU and regular bed capacities, we were able to accurately capture the treatment process of patients with COVID-19. This typically involves movement between both ICU and regular impatient beds before the patient exits the system through hospital discharge after recovery or through death.