Toward Automatic Reporting of Infectious Diseases

摘要：

　　Accurate,complete,and timely disease surveillance data are vital for disease control.We report a national scale effort to automatically extract information from electronic medical records as well as electronic laboratory systems.The extracted information is then transferred to the centers of disease control after a proper confirmation process.The coverage rates of the automated reporting systems are over 50%.Not only is the workload of surveillance greatly reduced,but also reporting is completed in near real-time.From our experiences,a system sustainable strategy,well-defined working plan,and multifaceted team coordination work effectively.Knowledge management reduces the cost to maintain the system.Training courses with hands-on practice and reference documents are useful for LOINC adoption.

关键词： Public Health Surveillance Electronic Health Records Logical Observation Identifiers Names and Codes

作者: Hsiao-Mei Tsao Chi-Ming Chang Jen-Hsiang Chuang Ding-Ping Liu Mei-Lien Pan Da-Wei Wang

作者单位: Institute of Information Science,Academia Sinica,Taipei,Taiwan,China Epidemic Intelligence Center,Centers for Disease Control,Taipei,Taiwan,China Epidemic Intelligence Center,Centers for Disease Control,Taipei,Taiwan,China;Institute of Biomedical

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: 808-812

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）