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Administrative Data Fail to Accurately Identify Cases of Healthcare‐Associated Infection
Eileen R. Sherman , MS, Kateri H. Heydon , MS, Keith H. St. John , MS, Eva Teszner , BSN, Susan L. Rettig , BSN, Sharon K. Alexander , BSN, Theoklis Z. Zaoutis , MD, MSCE and Susan E. Coffin , MD, MPH
Infection Control and Hospital Epidemiology
Vol. 27, No. 4 (April 2006), pp. 332-337
Published by: Cambridge University Press on behalf of The Society for Healthcare Epidemiology of America
Stable URL: http://www.jstor.org/stable/10.1086/502684
Page Count: 6
You can always find the topics here!Topics: Infections, Surveillance, Hospital administration, Patient surveillance, Billing, Health care administration, Urinary tract infections, Estimate reliability, Hospital admissions, Information classification
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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 administrative 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 investigation is needed to define the optimal detection method for institutions that provide HAI data for comparative analysis.
© 2006 by The Society for Healthcare Epidemiology of America. All rights reserved.