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http://dx.doi.org/10.5762/KAIS.2013.14.7.3400

Length of stay in PACU among surgical patients using data mining technique  

Yoo, Je-Bog (Samsung Medical Center)
Jang, Hee Jung (Division of Nursing Science, Hallym University)
Publication Information
Journal of the Korea Academia-Industrial cooperation Society / v.14, no.7, 2013 , pp. 3400-3411 More about this Journal
Abstract
The data mining is a new approach to extract useful information through effective analysis of huge data in numerous fields. This study was analyzed by decision making tree model using Clementine C&RT(Classification & Regression Tree, CART) as data mining technique. We utilized this data mining technique to analyze medical record of 1,500 people. Whole data were assorted by length of stay in PACU and divided into 3 groups. The result extracted by C5.0 decision tree method showed that important related factors for lengh of stay in PACU are type of operation, preoperative EKG abnormality, anesthetics, operative duration, age.
Keywords
Post-anesthesia nursing; Length of stay; Data mining;
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Times Cited By KSCI : 8  (Citation Analysis)
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