Early Machine-Human Interface around Sepsis Severity Identification: From Diagnosis to Improved Management?

Objective: To investigate the statistical measures of the performance of 2 interventions: a) early sepsis identification by a computerized sepsis "sniffer" algorithm (CSSA) in the emergency department (ED) and b) human decision to activate a multidisciplinary early resuscitation sepsis and shock response team (SSRT).

Methods: This study used a prospective and historical cohort study design to evaluate the performance of two interventions.

Intervention: A computerized sepsis sniffer algorithm (CSSA) to aid in early diagnosis and a multidisciplinary sepsis and shock response team (SSRT) to improve patient care by increasing compliance with Surviving Sepsis Campaign (SSC) bundles.