COVID-19 HOSPITALIZATION PROBLEM DESCRIPTION

In this paper, the group uses the following system to depict a patient’s hospitalization process due to COVID-19. First, the patient arrives into the system. The patient will either be admitted to the hospital or rejected. Patient admission to the hospital is based on severity. Due to limited hospital resources, only the patients who are at the highest risk will be admitted. Admission is also dependent on if there is space in the Emergency Department (ED) and enough resources available for the patient. After Admission, patients are given a series of lab tests and initial treatments to determine the severity of the disease. During the triage process step, the patient’s tests and vital measurements are reviewed in order to decide whether the patient should be sent to the ICU or a regular impatient bed. The ICU is reserved for the most severe cases of COVID-19 in which patients require ventilators to help their breathing and constant monitoring by hospital staff.

Once the patient is assigned a bed, they may not remain there for the entirety of their hospital stay. If their disease worsens, they may move from a regular impatient bed to an ICU bed. While if a patient in an ICU bed begins to improve, they may be moved to a regular impatient bed for the remainder of their stay. This is so the limited ICU beds and resources can be reserved for only the patients who really need it. Although in reality patients may move multiple times between an ICU bed and a regular impatient bed, for simplicity purposes in our model we will assume that patients will only move once between the two. For example, if a patient moves from an ICU bed to a regular impatient bed, our model assumes that they will remain in a regular impatient bed until they leave the system.

A patient may leave the system through death or recovery and discharge. Death may occur in patients either in the ICU or in regular impatient beds. Recovery and discharge can similarly occur in patients located in either beds.

With the creation of this model, the group aims to find the average waiting time for a patient who requires an ICU bed and the average waiting time for a patient who requires a regular impatient bed. Using this information, we can determine the optimal amount of ICU beds and regular impatient beds required to fully serve all COVID-19 patients seeking treatment at this particular ED. Decision makers will be able to use this model to make high level decisions about hospital resource allocation in order to minimize COVID-19 deaths by serving as many patients as possible.