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  • 标题:Using Emergency Department Data for Detection of a Synthetic Marijuana Outbreak
  • 本地全文:下载
  • 作者:Lourdes W. Yun ; Robert Beum ; Michele Askenazi
  • 期刊名称:Online Journal of Public Health Informatics
  • 电子版ISSN:1947-2579
  • 出版年度:2015
  • 卷号:7
  • 期号:1
  • 语种:English
  • 出版社:University of Illinois at Chicago
  • 摘要:Timely access to Emergency Department (ED) data is crucial for early detection of public health events. In August 2013, ED reported an increase in cases with excited delirium possibly related to synthetic marijuana (SM). We used this event to test BioSense 2.0 data to detect a novel public health event not categorized in the BioSense surveillance library. During the outbreak period (September 4-19, 2013), 21 cases of SM-related cases presented to Denver Health ED and 27 records were identified in the BioSense data. Using chief compliant and chart review as gold standard, this method was 99.6% specific and 44% sensitive.
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