Modeling CDC Data for Real Time Feature Estimation

Despite the fact that the main objective of an Emergency Department (ED) is to treat seriously ill patients, quality of care degrades due to prolonged waiting time. This paper investigates overcrowding as the main bottleneck in healthcare system performance and addresses patients' dissatisfaction and low quality of EDs' services on wait time. In this paper, we present empirical study, data analytics and application towards answering whether there is a significant correlation between medical immediacy and the length of wait time. This research is based on a series of feature estimation on 27 features extracted from publicly available dataset from Disease Control and Prevention (CDC) to find the extent of their correlation to prolonged wait time. The results suggest that in 2015 more than 63% of EDs visits were related to non-urgent medical issues. Our findings indicate that overcrowding occurs due to the presence of very large number of patients with non-urgent medical problems.