Optimization of the Design and Operation of a Healthcare Facility: The COVID-19 Case

Abstract

As witnessed by the 1st wave of the Corona Virus, COVID-19 has overwhelmed hospitals worldwide and exhausted valuable resources such as bed capacities, medical equipment, personal protective equipment (PPE) stocks and healthcare personnel. These factors imposed unforeseen challenges on the design, operation and control of healthcare treatment systems. Logistical and operational inefficiencies are detrimental during pandemics and are amongst the biggest reasons why healthcare systems fail to minimize death rates and spreads of pandemics. In the inevitable chance of future pandemics, or in the chance of repeated waves of the COVID-19 virus and mutagenic variants, countries and healthcare systems must pursue ways to predict the growth and spread of the virus, implement strategies to contain it, and prepare their facilities and resources accordingly. Mitigating operational inefficiencies by learning from COVID-19 is necessary to be better prepared in the future and save many lives and economic resources. The main goal of this study is the development of an optimized healthcare treatment network by using epidemiology curves to predict future influxes of COVID-19 patients, and then to optimize the In-Patient (IP) and Intensive Care Unit (ICU) bed capacities in a hospital facility, and finally to determine required levels of personal protective equipment. Our model seeks to determine the optimized bed capacity based on the flow of patients, by distinguishing them in terms of medical severity and allocating patients in the best possible manner in an existing or installed healthcare facility with a fixed limited capacity. Considering the different dates of hospital admission and discharge of patients from 2020’s 1st wave of COVID-19 and the upcoming expected influx of patients, we will be able to determine the bed space availability at any given future date. This will enable us to prescribe innovative solutions engineered to increase the capacity, responsiveness, and preparedness of healthcare systems infrastructure and management. In a post-optimization step, the results of the flow of patients will also allow us to determine the number of staffing required for the expected patients, and consecutively the amount of PPE required to be used by those staff as well. This optimization will allow medical corporations to a) design and operate healthcare treatment systems and b) determine and allocate required resources in a time of crisis to withstand a medical surge.

Date of Award	2021
Original language	American English
Awarding Institution	HBKU College of Science and Engineering