Clinical performance of an automated systemic inflammatory response syndrome (sirs) / organ dysfunction alert: a system-based patient safety project

Abstract

Objective: We have employed our electronic medical record (EMR) in an effort to identify patients at the onset of severe sepsis through an automated analysis that identifies simultaneous occurrence of systemic inflammatory response syndrome (SIRS) and organ dysfunction. The purpose of this study was to determine the positive predictive value of this alert for severe sepsis and other important outcomes in hospitalized adults. Design: Prospective cohort. Setting: Banner Good Samaritan Medical Center, Phoenix AZ. Patients: Forty adult inpatients who triggered alert logic within our EMR indicating simultaneous occurrence of SIRS and organ dysfunction. Interventions: Interview of bedside nurse and chart review within six hours of alert firing to determine the clinical event that triggered each alert. Results: Eleven of 40 patients (28%) had a major clinical event (immediately life-threatening illness) associated with the alert firing. Severe sepsis or septic shock accounted for four of these – yielding a positive predictive value of 0.10 (95%CI: 0.04-0.23) of the alert for detection of severe sepsis. The positive predictive value of the alert for detection of major clinical events was 0.28 (95%CI: 0.16-0.43), and for detecting either a major or minor clinical event was 0.45 (95%CI: 0.31-0.60). Twenty-two of 40 patients (55%) experienced a false alert. Conclusions: Our first-generation SIRS/organ dysfunction alert has a low positive predictive value for severe sepsis, and generates many false alerts, but shows promise for the detection of acute clinical events that require immediate attention. We are currently investigating refinements of our automated alert system which we believe have potential to enhance patient safety.