Evidence-Based Algorithms for Diagnosing and Treating Ventilator-Associated Pneumonia

BACKGROUND: Ventilator-associated pneumonia (VAP) is widely recognized as a serious and common complication associated with high morbidity and high costs. Given the complexity of caring for heterogeneous populations in the intensive care unit (ICU), however, there is Still uncertainty regarding how to diagnose and manage VAR OBJECTIVE: We recently conducted a national collaborative aimed at reducing health care-associated infections in ICUs of hospitals operated by the Hospital Corporation of America (HCA). As part of this collaborative, we developed algorithms for diagnosing and treating VAP in mechanically ventilated patients. In the current article, we (1) review the current evidence for diagnosing VAII, (2) describe Our approach for developing these algorithms, and (3) illustrate the utility of the diagnostic algorithms using clinical teaching cases. DESIGN: This was a descriptive study, using data from a national collaborative focused on reducing VAP and catheter-related bloodstream infections. SETTING: The setting of the study was 110 ICUs at 61 HCA hospitals. INTERVENTION: None. *Figures and Appendix can be found online at www.interscience.wiley.com/jhm