Development of a Novel Electronic Surveillance System for Monitoring of Bloodstream Infections
Development of a Novel Electronic Surveillance System for Monitoring of Bloodstream Infections
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DOI：
10.1086/653207
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发表时间：
2010-07-01
影响因子：
4.5
通讯作者：
Laupland, Kevin B.
中科院分区：
文献类型：
--
作者：
Leal, Jenine;Gregson, Daniel B.;Laupland, Kevin B.
背景利用数据库中现有信息的电子监测系统（ESS）比传统的感染监测方法更有效。开发一种用于监测血流感染（BSI）的ESS，并评估从ESS获得的数据是否与传统手动病历审查获得的数据一致。通过连接区域实验室和医院管理数据库的数据，开发了一个ESS。制定并应用了排除代表污染和重复发作的BSI发作的定义。感染被分类为医院感染、医疗保健相关的社区发病感染或社区获得性感染。对于随机抽样的发作，ESS中的数据与独立病历审查获得的数据进行比较。从306例感染患者的记录中，ESS确定了323例BSI事件，其中107例（33%）被归类为医疗保健相关的社区感染，108例（33%）被归类为社区获得性感染，107例（33%）被归类为医院感染，1例（0.3%）不能分类。相比之下，通过使用病历审查确定了310起事件，其中116起（37%）被归类为医疗保健相关的社区发病感染，95起（31%）为社区获得性感染，99起（32%）为医院感染。对于302次BSI，ESS的结果与传统的手动病历审查结果一致。在通过使用ESS识别的另外21例不一致事件中，通过使用病历审查，17例（81%）被归类为代表皮肤污染物分离。在通过病历审查进一步确定的另外8起不一致事件中，大多数被归类为疾病的重复或多微生物事件。根据采集位置分类，ESS结果与病历审查结果之间总体一致率为85%（kappa = 0.78;标准误，kappa = 0.04）。我们的新ESS允许BSI发作被识别和分类具有高度的准确性。该系统需要在其他队列和环境中进行验证。感染控制医院流行病学2010; 31（7）：740-747
BACKGROUND. Electronic surveillance systems (ESSs) that utilize existing information in databases are more efficient than conventional infection surveillance methods.OBJECTIVE. To develop an ESS for monitoring bloodstream infections (BSIs) and assess whether data obtained from the ESS were in agreement with data obtained by traditional manual medical-record review.METHODS. An ESS was developed by linking data from regional laboratory and hospital administrative databases. Definitions for excluding BSI episodes representing contamination and duplicate episodes were developed and applied. Infections were classified as nosocomial infections, healthcare-associated community-onset infections, or community-acquired infections. For a random sample of episodes, data in the ESS were compared with data obtained by independent medical chart review.RESULTS. From the records of the 306 patients whose infections were selected for comparative review, the ESS identified 323 episodes of BSI, of which 107 (33%) were classified as healthcare-associated community-onset infections, 108 (33%) were classified as community-acquired infections, 107 (33%) were classified as nosocomial infections, and 1 (0.3%) could not be classified. In comparison, 310 episodes were identified by use of medical chart review, of which 116 (37%) were classified as healthcare-associated community-onset infections, 95 (31%) as community-acquired infections, and 99 (32%) as nosocomial infections. For 302 episodes of BSI, there was concordance between the findings of the ESS and those of traditional manual chart review. Of the additional 21 discordant episodes that were identified by use of the ESS, 17 (81%) were classified as representing isolation of skin contaminants, by use of chart review. Of the additional 8 discordant episodes further identified by use of chart review, most were classified as repeat or polymicrobial episodes of disease. There was an overall 85% agreement between the findings of the ESS and those of chart review (kappa = 0.78; standard error, kappa = 0.04) for classification according to location of acquisition.CONCLUSION. Our novel ESS allows episodes of BSI to be identified and classified with a high degree of accuracy. This system requires validation in other cohorts and settings. Infect Control Hosp Epidemiol 2010; 31(7):740-747