Triage is the initial clinical prioritizing process in the emergency departments (EDs), and hence is a crucial decision making (DM) process. In order to improve the DM in healthcare systems, many researchers have implemented different tools and models from various fields. Likewise, this paper presents the use of utility theory in healthcare, more specifically in improving triage DM, productivity, and reducing the cognitive load on the triage nurse in EDs. The inherent uncertainty in this problem was the reason behind choosing the utility theory to solve the problem of sorting patients in EDs. In this paper, patients are ranked based on emergency severity index (ESI) and three descriptive variables: age, gender and pain level. A clinical data set of twenty one patients, from Susquehanna Health’s Williamsport Hospital, is used to build the overall utility function. Then, the Spearman’s rank correlation comparison method is applied to investigate the relevance among variables. High association is found between the overall utility ranking and the individual ESI utility ranking. On the other hand, there is no statistically significant association between the overall utility ranking and the utility ranking of other attributes individually, which attests to the varying levels of importance in the variable set.