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Health policy and services, Business and Management.
Non-linear processes within complex systems are difficult to predict. Using discrete event simulation (DES) models can be helpful for presenting the uncertainty level embedded within these processes. However, the interpretations of the resulting outcomes can be challenging to analyze. This is evident when experimenting with simulation models, and therefore requires the adaptation of existing models. Introducing cyclic entities such as interconnected resources to the simulation model adds a new level of complexity to the model. In practical cases, decision makers often demand a model that enables them to make quick decisions with less complexity involved. However, these individuals still want to be assured of a high degree of accuracy in the results. This article demonstrates how an analytical representation of complex DES models can be developed in order to facilitate prompt yet effective solutions for decision makers. This analytical representation provides a brief overview of the simulation results by using the staff scheduling and nurses’ utilization approaches. Results of the effective use of DES model and managers feedback are encouraging.
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