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Analysis of healthcare quality indicator using data mining and decision support system

Authors
 Young M Chae  ;  Hye S Kim  ;  Seung H Ho  ;  Hyun J Park  ;  Kwan C Tark 
Citation
 EXPERT SYSTEMS WITH APPLICATIONS, Vol.24(2) : 167-172, 2003 
Journal Title
 EXPERT SYSTEMS WITH APPLICATIONS 
ISSN
 0957-4174 
Issue Date
2003
MeSH
Continuous quality improvement ; Data mining ; Decision support system
Keywords
Continuous quality improvement ; Data mining ; Decision support system
Abstract
This study presents an analysis of healthcare quality indicators using data mining for developing quality improvement strategies. Specifically, important factors influencing the inpatient mortality were identified using a decision tree method for data mining based on 8405 patients who were discharged from the study hospital during the period of December 1, 2000 and January 31, 2001. Important factors for the inpatient mortality were length of stay, disease classes, discharge departments, and age groups. The optimum range of target group in inpatient healthcare quality indicators were identified from the gains chart. In addition, a decision support system (DSS) was developed to analyze and monitor trends of quality indicators using Visual Basic 6.0. Guidelines and tutorial for quality improvement activities were also included in the system. In the future, other quality indicators should be analyzed to effectively support a hospital-wide continuous quality improvement (CQI) activity and the DSS should be well integrated with the hospital order communication system (OCS) to support concurrent review.
Full Text
http://www.sciencedirect.com/science/article/pii/S0957417402001392
DOI
10.1016/S0957-4174(02)00139-2
Appears in Collections:
4. Graduate School of Public Health (보건대학원) > Graduate School of Public Health (보건대학원) > 1. Journal Papers
Yonsei Authors
Chae, Young Moon(채영문)
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/113732
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