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首页> 外文会议>Proceedings of the Fourth China-Japan-Korea joint symposium on medical informatics(CJKMI'02) >Analysis of Healthcare Quality Indicator using Data Mining and Decision Support System
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Analysis of Healthcare Quality Indicator using Data Mining and Decision Support System

机译：数据挖掘与决策支持系统对医疗质量指标的分析

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摘要

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 8,405 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 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 decision support system should be well integrated with the hospital OCS (Order Communication System) to support concurrent review.
机译：这项研究提出了使用数据挖掘来制定质量改进策略的医疗质量指标分析。具体来说，根据2000年12月1日至2001年1月31日从研究医院出院的8405名患者，使用决策树方法进行数据挖掘，确定了影响住院死亡率的重要因素。住院时间，疾病类别，出院部门和年龄组。从收益表中确定了目标人群在住院医疗质量指标中的最佳范围。此外，开发了决策支持系统，以使用Visual Basic 6.0分析和监视质量指标的趋势。系统中还包括质量改进活动的指南和教程。将来，应分析其他质量指标以有效支持整个医院范围内的持续质量改进（CQI）活动，并且决策支持系统应与医院OCS（订单沟通系统）很好地集成在一起，以支持并发审核。

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