Code-based syndromic surveillance for influenzalike illness by international classification of diseases, ninth revision
Code-based syndromic surveillance for influenzalike illness by international classification of diseases, ninth revision
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DOI：
10.3201/eid1302.060557
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发表时间：
2007-02-01
影响因子：
11.8
通讯作者：
Pavlin, Julie A.
中科院分区：
文献类型：
--
作者：
Marsden-Haug, Nicola;Foster, Virginia B.;Pavlin, Julie A.
随着禽流感的传播，使用自动数据流快速检测和跟踪人类流感病例的情况有所增加。我们进行了相关性分析，以确定在自动化综合征系统中用于检测流感样疾病(ILI)的国际疾病分类第九版(ICD-9)分组是否与同一人群中的呼吸道病毒实验室检测结果相关(r=0.71或0.86，取决于组)。我们使用时间和信噪比分析来确定最准确地代表ILI趋势的ICD-9代码的两个子集，将来自疾病控制和预防中心的全国哨点ILI监测数据与自动数据进行比较(r=0.97)，发现最敏感的ICD-9代码集用于呼吸道疾病监测。我们的结果展示了一种选择最佳ICD-9代码组的方法，以帮助系统开发人员和卫生官员在日常公共卫生活动中解释类似的数据。
With the spread of avian influenza, use of automated data streams to rapidly detect and track human influenza cases has increased. We performed correlation analyses to determine whether International Classification of Diseases, Ninth Revision (ICD-9), groupings used to detect influenza-like illness (ILI) within an automated syndromic system correlate with respiratory virus laboratory test results in the same population (r = 0.71 or 0.86, depending on group). We used temporal and signal-to-noise analysis to identify 2 subsets of ICD-9 codes that most accurately represent ILI trends, compared nationwide sentinel ILI surveillance data from the Centers for Disease Control and Prevention with the automated data (r = 0.97), and found the most sensitive set of ICD-9 codes for respiratory illness surveillance. Our results, demonstrate a method for selecting the best group of ICD-9 codes to assist system developers and health officials who are interpreting similar data for daily public health activities.