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

Abstract

In this work, we applied queue analysis and the predictions of waiting times at Regional Hospital Limbe (RHL) in Cameroon. The main purpose of the work was to be able to make mathematical sense of a real-life scenario that concerned queues (waiting lines) and try to come up with models for performance measurements and improvements; this could be achieved by using queueing theory concepts that were composed of queueing models that provided some operational insights because of their analytical nature. The observations included studying patient arrival and waiting times, along with doctor service times; the results showed busy departments in the hospital, busy days, and busy times. Long waiting times were mainly found to exist 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 that were obtained due to inefficient data, the value of this work lies mainly in the methodologies and proposals of different operating systems that could be adopted. Furthermore, some predictions were made using machine learning to see how long a patient could wait in a queue for service; the model predictions had an average of 10 minutes and 53 seconds of error.