Performance analysis of a university hospital blood laboratory via discrete event simulation

Abstract

Due to its simplicity and efficiency, blood testing has become a crucial step in the diagnosis of a variety of diseases. In this study, a university hospital blood laboratory was modeled by discrete event simulation to analyze processes and bottleneck operations. To reflect the actual processes in the simulation model, theoretical statistical distributions and statistical data analysis were utilized. Two alternative systems, which consist of process analysis solutions and resource alteration decisions, are proposed, and the current and the proposed systems are modeled and compared with each other statistically. According to the results, the proposed system performs significantly better than the other systems. The simulation reveals that alternative scenarios could decrease the throughput time with respect to the current system.