文章基本信息

标题：Enhancing Biosurveillance Specificity Using PraedicoTM, A Next Generation Application
本地全文：下载
作者：Alireza Vahdatpour ; Cynthia A. Lucero-Obusan ; Chris Lee 等
期刊名称：Online Journal of Public Health Informatics
电子版ISSN：1947-2579
出版年度：2016
卷号：8
期号：1
语种：English
出版社：University of Illinois at Chicago
摘要：We evaluated the specificity of Praedico Biosurveillance, a next generation biosurveillance application leveraging multiple detection algorithms, big data and machine learning, for VA outpatient syndromic surveillance alerting during the period of June 2014 thru May 2015, and compared it to the Electronic Surveillance System for the Early Notification of Community-Based Epidemics (ESSENCE). Praedicoâ„¢ Biosurveillance generated alerts were significantly lower compared to ESSENCE generated alerts across all major syndromic syndromes and demonstrated higher sensitivity to seasons (i.e., ILI activity in winter). Reducing alerting fatigue would enhance specificity of computer-generated alerts, promoting more usage and gradual improvement in the algorithm's output.