Leal Jenine R, Gregson Daniel B, Church Deirdre L, Henderson Elizabeth A, Ross Terry, Laupland Kevin B
Department of Community Health Sciences, University of Calgary, 3280 Hospital Drive NW, TRW Building, Rm 3D10, Calgary, AB, Canada T2N 4Z6; Division of Microbiology, Calgary Laboratory Services, 9-3535 Research Road NW, Calgary, AB, Canada T2L 2K8.
Division of Microbiology, Calgary Laboratory Services, 9-3535 Research Road NW, Calgary, AB, Canada T2L 2K8; Department of Medicine, Health Sciences Centre, University of Calgary, Foothills Campus, 3330 Hospital Drive NW, Calgary, AB, Canada T2N 4N1; Department of Pathology and Laboratory Medicine, Diagnostic & Scientific Centre, 9-3535 Research Road NW, Calgary, AB, Canada T2L 2K8.
Can J Infect Dis Med Microbiol. 2016;2016:2935870. doi: 10.1155/2016/2935870. Epub 2016 Jun 7.
Background. Electronic surveillance systems (ESSs) that utilize existing information in databases are more efficient than conventional infection surveillance methods. The objective was to assess an ESS for bloodstream infections (BSIs) in the Calgary Zone for its agreement with traditional medical record review. Methods. The ESS was developed by linking related data from regional laboratory and hospital administrative databases and using set definitions for excluding contaminants and duplicate isolates. Infections were classified as hospital-acquired (HA), healthcare-associated community-onset (HCA), or community-acquired (CA). A random sample of patients from the ESS was then compared with independent medical record review. Results. Among the 308 patients selected for comparative review, the ESS identified 318 episodes of BSI of which 130 (40.9%) were CA, 98 (30.8%) were HCA, and 90 (28.3%) were HA. Medical record review identified 313 episodes of which 136 (43.4%) were CA, 97 (30.9%) were HCA, and 80 (25.6%) were HA. Episodes of BSI were concordant in 304 (97%) cases. Overall, there was 85.5% agreement between ESS and medical record review for the classification of where BSIs were acquired (kappa = 0.78, 95% Confidence Interval: 0.75-0.80). Conclusion. This novel ESS identified and classified BSIs with a high degree of accuracy. This system requires additional linkages with other related databases.
背景。利用数据库中现有信息的电子监测系统(ESSs)比传统的感染监测方法更高效。目的是评估卡尔加里地区用于血流感染(BSIs)的ESS与传统病历审查的一致性。方法。ESS通过链接区域实验室和医院管理数据库中的相关数据并使用设定的定义来排除污染物和重复分离株而开发。感染被分类为医院获得性(HA)、医疗保健相关社区起病性(HCA)或社区获得性(CA)。然后将从ESS中随机抽取的患者样本与独立的病历审查进行比较。结果。在选择进行比较审查的308名患者中,ESS识别出318例BSI发作,其中130例(40.9%)为CA,98例(30.8%)为HCA,90例(28.3%)为HA。病历审查识别出313例发作,其中136例(43.4%)为CA,97例(30.9%)为HCA,80例(25.6%)为HA。在304例(97%)病例中,BSI发作是一致的。总体而言,ESS与病历审查在BSI获得地点分类方面的一致性为85.5%(kappa = 0.78,95%置信区间:0.75 - 0.80)。结论。这种新型ESS对BSI进行识别和分类具有高度准确性。该系统需要与其他相关数据库进行更多链接。