(untitled) (International Journal of Latest Technology in Engineering Management & Applied Science, 2026)
Public healthcare facilities in India frequently face operational inefficiencies due to high patient inflow and limited medical resources, resulting in prolonged waiting times and congestion. This study presents a queueing theory–based analytical framework to examine patient flow in government hospitals in India, with specific emphasis on outpatient and emergency services. Patient arrivals are modeled as stochastic processes, while service mechanisms are characterized by the availability of medical personnel and service counters. Single-server and multi-server queueing models are employed to evaluate key system performance indicators such as average waiting time, expected queue length, and server utilization. The findings indicate that peak-hour congestion significantly affects service efficiency, whereas off-peak periods exhibit resource underutilization. Numerical results show that strategic reallocation of existing staff and minor modifications in service configuration can lead to substantial reductions in patient waiting time without increasing infrastructure costs. The study demonstrates the effectiveness of operations research techniques in addressing real-world healthcare challenges and offers quantitative decision-support insights for improving operational efficiency in Indian government hospitals.