医院感染实时监控系统病例预警策略的评价研究  

Early warning strategy for cases by real-time healthcare-associated infection surveillance system

作　　者：姚希[1] 贾建侠[1] 赵艳春[1] 任军红[1] 赵秀莉[1] 胡美华[1] 张然[1] 彭雪儿 李六亿[1] YAO Xi;JIA Jian-xia;ZHAO Yan-chun;REN Jun-hong;ZHAO Xiu-li;HU Mei-hua;ZHANG Ran;PENG Xue -er;LI Liu-yi(Department of Healthcare -associated Infection Control,Peking University First Hospital,Beijing 100034,China)

机构地区：[1]北京大学第一医院感控处,北京100034

出　　处：《中国感染控制杂志》2019年第4期326-330,共5页Chinese Journal of Infection Control

摘　　要：目的通过评价医院感染实时监控系统(简称"院感系统")病例预警策略的准确性和效率,为预警策略改进提出科学建议。方法通过调查某三级甲等综合医院2017年全年院感系统产生的医院感染预警信息及最终确认情况,计算医院感染预警灵敏度、医院感染预警阳性预测值和感染预警阳性预测值,评价其准确性及效率。结果该院2017年确认的医院感染832例次,其中院感系统有效预警的医院感染715例次,灵敏度为85.94%。全年院感系统共预警8 468例,其中感染病例为2 817例,感染病例数预警阳性预测值为33.27%,医院感染病例为772例,医院感染病例数预警阳性预测值为9.12%。全年院感系统共预警14 857条,其中确认为感染的4 135条,感染预警阳性预测值为27.83%,确认为医院感染的1 199条,医院感染预警阳性预测值为8.07%。结论院感系统是识别医院感染病例的重要技术手段,在病例识别的特异性及效率上还有待提高,另外预警感染高风险病例能力还需加强。Objective To evaluate the accuracy and efficiency of early warning strategy for cases by real-time healthcare-associated infection(HAI)surveillance system(HAISS),and propose scientific suggestion for the improvement of early warning strategy.Methods By investigating the early warning information and final confirmation of HAI generated by HAISS in a tertiary first-class general hospital in 2017,the sensitivity and positive predictive value of early warning of HAI as well as positive predictive value of early warning of infection were calculated to evaluate the accuracy and efficiency of early warning.Results 832 cases of HAI were confirmed in this hospital in 2017,715 cases were HAI effectively warned by HAISS,with a sensitivity of 85.94%.A total of 8 468 cases were warned by HAISS in the whole year,2 817 were infection cases,positive predictive value of early warning of infection cases was 33.27%,772 cases were HAI,and positive predictive value of early warning of HAI cases was 9.12%.There were 14 857 early warnings in HAISS in the whole year,of which 4 135 were confirmed as infection,positive predictive value of early warning of infection was 27.83%,1 199 were confirmed as HAI,positive predictive value of early warning of HAI was 8.07%.Conclusion HAISS is an important technical mean for identifying HAI cases,specificity and efficiency of case identification need to be improved,the ability of early warning for high-risk infection cases need to be strengthened.

关 键 词：医院感染 实时监控系统 预警 准确性 灵敏度 阳性预测值 诊断效能 

分 类 号：R181.32[医药卫生—流行病学]