Healthcare Delivery in a Hospital Emergency Department

Joseph Twagilimana (University of Louisville, USA)
Copyright: © 2010 |Pages: 304
EISBN13: 9781609603083|DOI: 10.4018/978-1-61520-723-7.ch013
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The outcome of interest in this study is the length of stay (LOS) at a Hospital Emergency Department (ED). The Length of stay depends on several independent clinical factors such as treatments, patient demographic characteristics, hospital, as well as physicians and nurses. The present study attempts to identify these variables by analyzing clinical data provided by electronic medical records (EMR) from an emergency department. Three analysis methodologies were identified as appropriate for this task. First, data mining techniques were applied, and then generalized linear models and Time series followed. In spite of the fact that Data Mining and Statistics share the same objective, which is to extract useful information from data, they perform independently of each other. In this case, we show how the two methodologies can be integrated with potential benefits. We applied decision trees to select important variables and used these variables as input in the other models.
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