Sherman Eileen R, Heydon Kateri H, St John Keith H, Teszner Eva, Rettig Susan L, Alexander Sharon K, Zaoutis Theoklis Z, Coffin Susan E
Department of Infection Prevention and Control, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.
Infect Control Hosp Epidemiol. 2006 Apr;27(4):332-7. doi: 10.1086/502684. Epub 2006 Mar 29.
Some policy makers have embraced public reporting of healthcare-associated infections (HAIs) as a strategy for improving patient safety and reducing healthcare costs. We compared the accuracy of 2 methods of identifying cases of HAI: review of administrative data and targeted active surveillance.
DESIGN, SETTING, AND PARTICIPANTS: A cross-sectional prospective study was performed during a 9-month period in 2004 at the Children's Hospital of Philadelphia, a 418-bed academic pediatric hospital. "True HAI" cases were defined as those that met the definitions of the National Nosocomial Infections Surveillance System and that were detected by a trained infection control professional on review of the medical record. We examined the sensitivity and the positive and negative predictive values of identifying HAI cases by review of administrative data and by targeted active surveillance.
We found similar sensitivities for identification of HAI cases by review of administrative data (61%) and by targeted active surveillance (76%). However, the positive predictive value of identifying HAI cases by review of administrative data was poor (20%), whereas that of targeted active surveillance was 100%.
The positive predictive value of identifying HAI cases by targeted active surveillance is very high. Additional investigation is needed to define the optimal detection method for institutions that provide HAI data for comparative analysis.
一些政策制定者已接受医疗保健相关感染（HAIs）的公开报告，将其作为提高患者安全和降低医疗成本的一项策略。我们比较了两种识别HAI病例的方法的准确性：行政数据审查和目标性主动监测。
设计、地点和参与者：2004年在费城儿童医院进行了一项为期9个月的横断面前瞻性研究，该医院是一家拥有418张床位的学术性儿科医院。“真正的HAI”病例定义为符合国家医院感染监测系统定义且经训练有素的感染控制专业人员在审查病历后检测到的病例。我们通过行政数据审查和目标性主动监测来检查识别HAI病例的敏感性以及阳性和阴性预测值。
我们发现通过行政数据审查识别HAI病例的敏感性（61%）和通过目标性主动监测识别HAI病例的敏感性（76%）相似。然而，通过行政数据审查识别HAI病例的阳性预测值较低（20%），而目标性主动监测的阳性预测值为100%。
通过目标性主动监测识别HAI病例的阳性预测值非常高。需要进一步调查，为提供HAI数据进行比较分析的机构确定最佳检测方法。
