Genetic Algorithm Based Framework For Managing Medical Equipment Replacement

Abstract

Planning of medical equipment management is a complex issue. Many dimensions should be considered in this process. The quality level of the provided service and costs policies are the most influential ones. Recently, hospitals are interested in minimizing the expenditures by optimizing the planning of all activities. Therefore, proper identification of the framework of medical equipment management including which, what, and how is essential. The aim of the paper was to optimize planning of disposal or replacement in addition to review maintenance activity. The management process was performed using genetic algorithm. It is employed as an optimization tool to guide and differentiate both activities. Medical imaging equipment was chosen for this purpose. According to the output of genetic algorithm, adopting maintenance strategy or disposal was selected for each equipment. Key Performance Indicators were suggested for reviewing the adopted maintenance strategies to enhance the overall performance. The model has been applied on 20 pieces of medical imaging equipment including four modalities. Outcomes revealed the robustness of the model in support decision making. Indeed, genetic algorithm proves its ability to maximize the number of equipment require reviewing maintenance strategy, and simultaneously minimize the number of equipment requires disposal effectively.