Leal J, Laupland K B
Department of Community Health Sciences, University of Calgary, Calgary Health Region, Calgary, Alberta, Canada.
J Hosp Infect. 2008 Jul;69(3):220-9. doi: 10.1016/j.jhin.2008.04.030. Epub 2008 Jun 11.
Electronic surveillance that utilises information held in databases is more efficient than conventional infection surveillance methods. Validity is not well-defined, however. We systematically reviewed studies comparing the utility of electronic and conventional surveillance methods. Publications were identified using Medline (1980-2007) and bibliographic review. The sensitivity and specificity of electronic compared with conventional surveillance was reported. Twenty-four studies were included. Six studies reported that nosocomial infections could be detected utilising microbiology data alone with good overall sensitivity (range: 63-91%) and excellent specificity (range: 87 to >99%). Two studies used three laboratory-based algorithms for the detection of infection outbreaks yielding variable utility measures (sensitivity, range: 43-91%; specificity, range: 67-86%). Seven studies using only administrative data including discharge coding (International Classification of Diseases, 9th edn, Clinical Modification) and pharmacy data claimed databases had good sensitivity (range: 59-96%) and excellent specificity (range: 95 to >99%) in detecting nosocomial infections. Six studies combined both laboratory and administrative data for a range of infections, and overall had higher sensitivity (range: 71-94%) but lower specificity (range: 47 to >99%) than with use of either alone. Three studies evaluated community-acquired infections with variable results. Electronic surveillance has moderate to excellent utility compared with conventional methods for nosocomial infections. Future studies are needed to refine electronic algorithms further, especially with community-onset infections.
利用数据库中所存信息的电子监测比传统的感染监测方法更高效。然而，其有效性尚无明确界定。我们系统回顾了比较电子监测方法与传统监测方法效用的研究。通过医学文献数据库（1980 - 2007年）检索及文献综述来确定相关出版物。报告了电子监测与传统监测相比的灵敏度和特异度。纳入了24项研究。6项研究报告称，仅利用微生物学数据就能检测到医院感染，总体灵敏度良好（范围：63% - 91%），特异度极佳（范围：87%至>99%）。2项研究使用了三种基于实验室的算法来检测感染暴发，得出了不同的效用指标（灵敏度，范围：43% - 91%；特异度，范围：67% - 86%）。7项仅使用包括出院编码（《国际疾病分类》第9版，临床修订本）和药房数据在内的管理数据的研究称，数据库在检测医院感染方面具有良好的灵敏度（范围：59% - 96%）和极佳的特异度（范围：95%至>99%）。6项研究将实验室数据和管理数据结合用于一系列感染，总体而言，与单独使用其中任何一种数据相比，灵敏度更高（范围：71% - 94%），但特异度较低（范围：47%至>99%）。3项研究评估社区获得性感染，结果各异。与传统方法相比，电子监测在医院感染方面具有中等至极佳的效用。未来需要进一步完善电子算法的研究，尤其是针对社区发病感染的算法。
