Administrative Data Fail to Accurately Identify Cases of Healthcare-Associated Infection

objective. 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 ad-ministrative data and by targeted active surveillance. results. 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%. conclusions. The positive predictive value of identifying HAI cases by targeted active surveillance is very high. Additional investigatio