A fuzzy inference system for preventing ambulance diversion in emergency departments

The hospital emergency department (ED) is an extremely important area of the hospital and serves a diverse patient population. The population that utilizes the ED is of varying acuity levels, varying illnesses, different demographics, and different ages. The objective of this research is to construct a fuzzy inference system that performs as a decision support system to eliminate ambulance diversion in the ED. This system takes information or input factors from the ED and recommends a certain percentage of lower acuity patients to divert from the ED to outpatient clinics or primary care physicians. The systems were validated against the baseline values for need for diversion and the error was calculated. The queue network performed much better than the simulation model fuzzy inference system when MSE was compared. The error for the queue network FIS was relatively low and it performed well across most of the data range.