Optimal grouping for a nuclear magnetic resonance scanner by means of an open queueing model

Abstract

In this paper we analyze how a nuclear magnetic resonance scanner can be managed more efficiently, simultaneously improving patient comfort (in terms of total time spent in the system) and increasing availability in case of emergency calls. By means of a superposition approach, all relevant data on the arrival and service process of different patient types are transformed into a general single server, single class queueing model. The objective function consists of the weighted average patient lead time, which is a multi-dimensional convex function of the different patient group sizes. The ''optimal'' patient group sizes are determined by means of a dedicated optimization routine. The model does not only provide a valuable aid for planning purposes, but also allows to model customer service. It is illustrated by means of real life data, obtained from the Virga Jesse Hospital (Hasselt, Belgium).