Predictions and Application of Queueing Analysis: A Case of Regional Hospital Limbe, Cameroon

In this work, we apply queue analysis and the prediction of waiting time at the Regional Hospital Limbe (RHL). The main purpose of the work was to be able to make mathematical sense of a real-life scenario concerning queues (waiting lines) and to try to come up with models for performance measurement and improvement. This can be achieved using queueing theory concepts, composed of queueing models that provide some operational insights because of their analytical nature. The observations included studying patient arrival and waiting times, together with doctor service times. The results show the busy departments in the hospital, busy days, and busy times. Long waiting times were found to exist mainly in general practitioner (GP) and specialist consultations. The queueing concept was applied to only one service segment, GP consultation. Although strong scientific conclusions cannot be made on the queuing models obtained due to inefficient data, the value of this work lies mainly in the methodology and proposal of different operating systems that can be adopted. Furthermore, some predictions were made using machine learning to see how long a patient can wait in a queue for service, the model predicting with an average of 10 minutes and 53 seconds of error.