Optimization of Man Power Deployment for Covid-19 Screening in a Tertiary Care Hospital: A Study of Utility of Queuing Analysis

The recent Covid-19 pandemic has burdened the healthcare facilities, especially in the presence of limited infrastructure. We aimed at applying a queuing model to the Covid-19 screening area so as to optimize the screening services and ensuring that no patient is refused the service. The mean arrival time of patients, number of physicians, mean screening time and queue characteristics were observed and entered in the M/M/c/K queuing model using R programming to optimize the number of physicians required in the screening area. Considering the mean arrival of 7 patients in 10 minutes and screening of 3 patients in 10 minutes by 1 physician, 2 physicians were assigned. At this capacity, the probability of saturation of the system was 15% with patient loss rate of 1.05 per 10 minutes. Queuing simulation with 3 physicians reduced the patient loss rate to 0.013 per 10 minutes and a saturation probability of 0.2%. However, an increase of arrival rate from 10 to 20 led to an early saturation of the system. Queuing models offer an opportunity for the healthcare providers and hospital administrators to optimize patient care services, especially in critical areas with an ever-changing situation such as the current pandemic.