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Healthcare Delivery in a Hospital Emergency Department

Healthcare Delivery in a Hospital Emergency Department

Joseph Twagilimana
Copyright: © 2010 |Pages: 30
ISBN13: 9781615207237|ISBN10: 1615207236|ISBN13 Softcover: 9781616922535|EISBN13: 9781615207244
DOI: 10.4018/978-1-61520-723-7.ch013
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MLA

Twagilimana, Joseph. "Healthcare Delivery in a Hospital Emergency Department." Cases on Health Outcomes and Clinical Data Mining: Studies and Frameworks, edited by Patricia Cerrito, IGI Global, 2010, pp. 275-304. https://doi.org/10.4018/978-1-61520-723-7.ch013

APA

Twagilimana, J. (2010). Healthcare Delivery in a Hospital Emergency Department. In P. Cerrito (Ed.), Cases on Health Outcomes and Clinical Data Mining: Studies and Frameworks (pp. 275-304). IGI Global. https://doi.org/10.4018/978-1-61520-723-7.ch013

Chicago

Twagilimana, Joseph. "Healthcare Delivery in a Hospital Emergency Department." In Cases on Health Outcomes and Clinical Data Mining: Studies and Frameworks, edited by Patricia Cerrito, 275-304. Hershey, PA: IGI Global, 2010. https://doi.org/10.4018/978-1-61520-723-7.ch013

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Abstract

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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