An Intelligent Algorithm for Optimization of Resource Allocation Problem by Considering Human Error in an Emergency Department

Human error is a significant and ever-growing problem in the healthcare sector. In this study, resource allocation problem is considered along with human errors to optimize utilization of resources in an emergency department. The algorithm is composed of simulation, artificial neural network (ANN), design of experiment (DOE) and fuzzy data envelopment analysis (FDEA). It is a multi-response optimization approach to optimize human error, cost, wait time, and patient safety, and productivity. Skill, rule, and knowledge (SRK) based approach is used to model human error. Simulation is applied to determine the relationship between human resource utilization and human error.  It is also used to model SRK behavior. ANN is utilized to predict response variables. FDEA is used to identify the optimum scenario. This is the first study that considers human errors along with resource allocation in the emergency department (ED). Second, it is equipped with verification and validation at each phase. Third, it is a practical approach for emergency departments (EDs).

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