Design and operation of healthcare facilities using batch-lines: the COVID-19 case in Qatar

In the wake of the COVID-19 pandemic, hospitals worldwide have been overwhelmed and deprived of valuable resources such as bed capacities, medical equipment, personal protection equipment (PPE) stocks, and personnel. These factors imposed unforeseen challenges in the healthcare treatment systems. Mitigating inefficiencies by learning from COVID-19 is necessary to be better prepared to save lives and conserve resources. The main goal of this study is the development of an optimized healthcare treatment network by using predicted epidemiology curves to determine influxes of patients and bed capacities in a hospital facility for both in-patient (IP) wards (oxygen outlets) and intensive care units (ICU). Our model considers flows of patients by distinguishing them in terms of medical severity for their optimal allocation in an existing or installed healthcare facility treated as batch-lines (batch-processes in lines) with time-varying yields of a number of patients per day of treatment. Considering the hospital's admission and discharge of patients from 2020’s 1^st wave of COVID-19 in Qatar, we determine the bed space availability at any given future date for a hospital facility. This enables the prescription of engineered solutions to increase the capacity, responsiveness, and preparedness of healthcare systems infrastructure and management.