Assistant Professor University of Illinois at Urbana-Champaign
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High frequency users (HFU) are a group of patients who visit a hospital emergency department (ED) more than 4 to 10 times per
year. It has been shown that the visits by these patients account for up to 10% of the entire visits while the number of HFU is
only 1% of total population. Previous studies have investigated characteristics of various HFU groups determined by their visit
frequencies. However, the follow up visits after they are identified as HFUs have not been studied. Our research aims to understand
visit patterns of HFUs in the ED and compare demographic and visit characteristics of the patient population between the groups
by visit patterns. This study first shows an innovative way to group HFUs as "Long-term frequent users"(LTFU) and "Short-term
Frequent Users"(STFU) regarding their changing visit patterns. Several machine learning methods are used to identify LTFUs and
their performance is compared.