Hospital bed capacity management during the COVID-19 outbreak using system dynamics: A case study in Amol public hospitals, Iran

Abstract

ABSTRACT Nowadays proper management of hospital resources has played an important role in reducing the economic pressure on hospitals. Unprecedented challenges have arisen for healthcare systems including further resource constraints due to the Covid-19 pandemic. So different countries faced the low capacity of hospitals' resources to admit and care for patients during the crisis. Medical staff, beds and personal protective equipment are among the scarce resources in this period. In this study, the patient flow in public hospitals has been modeled using System Dynamics (SD) simulation to manage the available capacity of intensive care units (ICU) and wards during the COVID-19 period. The model has been implemented in Vensim PLE and verified for public hospitals in Amol, Iran. The results have shown that hospitals face bed shortages in the period coinciding with the growing incidence of COVID-19, being forced to cancel or delay the admission of selected patients and nonemergency surgeries. Different scenarios based on possible strategies for managing hospital bed capacities have been also evaluated. The best strategy is the one in which the allocated bed capacities to COVID-19 patients are altered based on infection rates during different stages of the pandemic, resulting the shortage of beds is postponed the most.