Methods for Detecting Malfunctions in Clinical Decision Support Systems

摘要：

　　Clinical decision support systems,when used effectively,can improve the quality of care.However,such systems can malfunction,and these malfunctions can be difficult to detect.In this poster,we describe four methods of detecting and resolving issues with clinical decision support: 1)statistical anomaly detection,2)visual analytics and dashboards,3)user feedback analysis,4)taxonomization of failure modes/effects.

关键词： Expert Systems Electronic Health Records Safety

作者: Adam Wright Trang T.Hickman Dustin McEvoy Skye Aaron Joan S.Ash Jan Marie Andersen Rachel Ramoni Milos Hauskrecht Peter Embi Richard Schreiber Dean F.Sittig David W.Bates

作者单位: Brigham and Womens Hospital,Boston,MA;Harvard Medical School,Boston,MA;Partners HealthCare,Boston,M Brigham and Womens Hospital,Boston,MA;Partners HealthCare,Boston,MA Oregon Health and Science University,Portland,OR Partners HealthCare,Boston,MA;Harvard School of Dental Medicine,Boston,MA University of Pittsburgh,Pittsburgh,PA Ohio State University,Columbus,OH Holy Spirit Hospital,Danville,PA University of Texas Health Sci. Center,Houston,TX

会议类型: 国际会议

会议名称: 第十六届世界医药健康信息学大会((MEDINFO2017)、第二届世界医药健康信息学华语论坛(WCHIS 2017)、第15届全国医药信息学大会(CMIA 2017)

会议地点: 苏州

会议语种:英文

页码: 1385-1385

在线出版日期: 2017-08-21（万方平台首次上网日期，不代表论文的发表时间）