The focus of this study will be to conduct a prospective, randomized controlled trial (RCT) at Cape Regional Medical Center (CRMC), Oroville Hospital (OH), and UCSF Medical Center (UCSF) in which a Gram type infection-specific algorithm will be applied to EHR data for the detection of severe sepsis. For patients determined to have a high risk of severe sepsis, the algorithm will generate automated voice, telephone notification to nursing staff at CRMC, OH, and UCSF. The algorithm's performance will be measured by analysis of the primary endpoint, time to antibiotic administration. The secondary endpoint will be reduction in the administration of unnecessary antibiotics, which includes reductions in secondary antibiotics and reductions in total time on antibiotics.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
DIAGNOSTIC
Masking
TRIPLE
The InSight algorithm which draws information from a patient's electronic health record (EHR) to predict the onset of severe sepsis, and in this study will be customized to differentiate between various Gram-type infections.
Change in time to antibiotic administration
Change in time period between diagnosis of Gram infection and administration of antibiotics to treat infection
Time frame: Through study completion, an average of 8 months
Change in administration of unnecessary antibiotics
Changes in amount of secondary antibiotics administered
Time frame: Through study completion, an average of 8 months
Change in administration of unnecessary antibiotics
Changes in total hours spent on antibiotics
Time frame: Through study completion, an average of 8 months
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