Queuing Analysis of Patient Flow in the Outpatient Department Offederal Medical Centre, Keffi: an M/m/c Model Approach
Year: 2026
Type: article
Abstract: Public hospitals in developing nations, including Nigeria, face problems with their outpatient departments due to extended patient waiting time. This research applies queuing theory to analyse patient flow through the Outpatient Department (OPD) of the Federal Medical Centre, Keffi, using observational data. Patient arrivals and consultation times were modelled as an M/M/c queuing system with varying numbers of doctor servers. Key performance measures estimated include average queue length, average waiting time in the queue, average number in the system, average time in the system, and system utilization. Goodness-of-fit tests were conducted to validate the model assumptions. The results showed that both inter-arrival and service times follow an exponential distribution, confirming the suitability of the M/M/c framework. The findings indicate that the OPD system is unstable when operated with one or two doctors, leading to long queues and waiting times. With three doctors, the system operates at critical capacity and remains sensitive to fluctuations in patient arrivals. The introduction of a fourth doctor results in system improvement, reducing the average queue length to 1.53 patients and the average waiting time to 5 minutes, while lowering system utilization to 0.75. Graphical analysis confirms reductions in the number of patients in the system and total system time under the four-doctor configuration, indicating a smoother and more efficient patient flow. The study demonstrates that staffing is crucial for reducing outpatient waiting times and improving service delivery. It provides evidence that M/M/c queuing models can support hospital managers in optimizing healthcare services in resource-constrained environments.
Institution: Federal University Lafia
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W7166315631