数据挖掘技术在药品不良反应监测中的应用进展  

Application progress of data mining technology in adverse drug reaction monitoring

作　　者：高嵩 高月娟 朱仁英 王莉莉 修艳丽 毕琳瑜 GAO Song;GAO Yue-juan;ZHU Ren-ying;WANG Li-li;XIU Yan-li;BI Lin-yu(School of Nursing,Mudanjiang Medical University,Heilongjiang Province,Mudanjiang 157011,China;Department of Medicine,Hongqi Hospital Affiliated to Mudanjiang Medical University,Heilongjiang Province,Mudanjiang 157011,China;Department of Nursing,Hongqi Hospital Affiliated to Mudanjiang Medical University,Heilongjiang Province,Mudanjiang 157011,China)

机构地区：[1]牡丹江医学院护理学院,黑龙江牡丹江157011 [2]牡丹江医学院附属红旗医院药学部,黑龙江牡丹江157011 [3]牡丹江医学院附属红旗医院护理部,黑龙江牡丹江157011

出　　处：《中国当代医药》2021年第26期31-35,共5页China Modern Medicine

基　　金：黑龙江省牡丹江市科学技术计划项目(Z2018s058)。

摘　　要：数据挖掘技术现已被广泛应用于药品不良反应监测之中,药品不良反应的监测由来已久,结合数据挖掘技术来进行更准确有效的监测已经成为当今的热点问题。其方法众多,包括其在自发呈报系统下的药品不良反应监测的方法,诸如频数法、贝叶斯法、关联规则、聚类分析、决策树、主成分分析等以及主动监测的一些方法。本文将总结上述有关的方法在药品不良反应监测的应用现状及进展,以期为药品不良反应监测提供有意义的指导。Data mining technology has been widely used in the monitoring of adverse drug reactions in the era of big data.The monitoring of adverse drug reactions has a long history.Combined with data mining technology to carry out more accurate and effective monitoring has become a hot issue today.There are many methods of adverse drug reaction monitoring,including frequency method,Bayesian method,association rule,cluster analysis,decision tree,principal component analysis,and active monitoring methods developed in recent years.In this paper,the application status and progress of the above methods in adverse drug reaction monitoring will be summarized in order to provide meaningful guidance for adverse drug reaction monitoring.

关 键 词：数据挖掘 药品不良反应监测 自发呈报系统 主动监测 

分 类 号：R994.11[医药卫生—毒理学]