Simulation optimization of an emergency department by modeling human errors

Emergency department (ED) is considered as one of the most critical elements in healthcare systems. This paper describes a simulation optimization of an emergency department in a general hospital in Iran by modeling human error. Human error is defined as combination of committed errors by nurses and technicians. In this study three types of errors are evaluated including repeated venipuncture, unsafe transportation and sampling errors. These errors are considered in simulation model. Seventy appropriate scenarios approved by experts in ED are defined to assess various alternatives. Scenarios are examined and evaluated by stochastic data envelopment analysis (SDEA). Then, the optimum scenarios are identified. In this study, expense cost, number of nurses and physicians are considered as inputs whilst patient duration, queue length, and number of three different committed errors are considered as outputs of SDEA and DEA model. The results show that addition of nurse and physician in ED would reduce the human errors, patient duration and queue length. Then, proposed approach is validated and verified by statistical test. Finally, queue length is identified as the most important indicator through sensitivity analysis. To the best of our knowledge this is the first paper that examines human errors in a general hospital by simulation, DEA, and SDEA approaches. Moreover, human errors are classified based on skill, rule, and knowledge (SRK) based behavior to help decision makers in order to improve the quality of care for this particular ED.