Application of Active Mining to Prevention of Medical Incidents and Accidents

医疗事件和事故的报告已被储存，以供分析和预防。本研究旨在开发一个系统，通过使用主动挖掘技术来分析存储的数据，并澄清这些事件背后隐藏的因素。2005年，我们开发了一个数据仓库系统，以电子方式存储事故报告。在本财年，基于存储的数据，我们应用了几种数据挖掘方法，存储的数据和相关的数据，从医院信息系统（HIS）提取如下。在2006年上半年，我们开发了一个数据仓库服务器，它将事件数据与从HIS中提取的与事件相关的数据相结合。2006年下半年，对数据仓库服务器中的数据采用了数据挖掘方法。分析结果如下：（1）在大学医院进行和登记的约7000起行动中，有120起被登记为医疗事故，每月10起。因此，发生医疗事故的概率最多为1比20000。(2)患者的年龄是发生意外的主要因素之一。(3)诊断科室与事件关联度不高。虽然数据是不平衡的，几个有趣的结果被观察到从提取的模式。

Reports on medical incidents and accidents have been stored for their analysis and prevention. This study aims at developing a system to analyze stored data by using active mining technology and to clarify the hidden factors behind these incidents. In 2005, we developed a data-warehouse system which stores incident reports electronically. In this fiscal year, based on the stored data, we apply several data mining methods to stored data and the data related with incidents, extracted from hospital information system (HIS) as follows. In the upper half of 2006, we developed a data-warehouse server which combines incident data with data related with incidents, which are extracted from HIS. In the latter half of 2006, data mining methods were applied to data in the data-warehouse server. The results obtained from this analysis are the following: (1) While about 7000 actions are performed and registered in the university hospital, 120 cases were registered as medical incidents, 10 cases a month. Thus, the probability of medical accidents is at most 1 to 20000. (2) Age of a patient is one of the principal factor for accidents. (3) diagnosis departments are not so related with incidents. Although data is imbalanced, several interesting results were observed from extracted patterns.