Department of Medical Microbiology and Infectious Diseases, Erasmus University Medical Centre, Rotterdam, the Netherlands.
Albert Schweitzer Hospital, Dordrecht, the Netherlands.
Euro Surveill. 2019 Mar;24(13). doi: 10.2807/1560-7917.ES.2019.24.13.1800177.
BackgroundSurveillance of hospital-acquired infections (HAI) often relies on point prevalence surveys (PPS) to detect major deviations in the occurrence of HAI, supplemented with incidence measurements when more detailed information is needed. In a 1,320-bed university medical centre in the Netherlands, we evaluated an electronically assisted surveillance system based on frequently performed computer-assisted PPS (CAPPS).AimThe primary goals were to evaluate the performance of this method to detect trends and to determine how adjustments in the frequency with which the CAPPS are performed would affect this performance. A secondary goal was to evaluate the performance of the algorithm (nosocomial infection index (Nii)) used.MethodsWe analysed the data of 77 hospital-wide PPS, performed over a 2-year period (2013 and 2014) and including 25,056 patients.ResultsSix trends with statistical significance were detected. The probability to detect such trends rapidly decreased when PPS are performed at a lower frequency. The Nii and its dynamics strongly correlated with the presence of HAI.ConclusionPerforming computer-assisted, high frequency hospital-wide PPS, is a feasible method that will detect even subtle changes in HAI prevalence over time.
医院获得性感染(HAI)的监测通常依赖于现患率调查(PPS)来发现 HAI 发生的重大偏差,并在需要更详细信息时辅以发病率测量。在荷兰的一家拥有 1320 张床位的大学医学中心,我们评估了一种基于频繁进行的计算机辅助 PPS(CAPPS)的电子辅助监测系统。
该方法的主要目标是评估其检测趋势的性能,并确定调整 CAPPS 的执行频率如何影响这种性能。次要目标是评估所使用的算法(医院感染指数(Nii))的性能。
我们分析了 2013 年和 2014 年期间进行的为期 2 年的 77 次全院性 PPS 的数据,共包括 25056 名患者。
检测到 6 个具有统计学意义的趋势。当 PPS 的执行频率较低时,检测到这些趋势的可能性迅速降低。Nii 及其动态与 HAI 的存在强烈相关。
进行计算机辅助、高频率的全院 PPS 是一种可行的方法,可以检测到 HAI 患病率随时间的变化,即使是细微的变化。