A sepsis early warning predictive algorithm, InSight, has been developed and validated on a large, diverse patient cohort. In this prospective study, the ability of InSight to predict severe sepsis patients is investigated. Specifically, InSight is compared with a well established severe sepsis detector in the UCSF electronic health record (EHR).
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
SCREENING
Masking
NONE
Enrollment
142
Upon receiving an InSight alert, healthcare provider follows standard practices in assessing possible (severe) sepsis and intervening accordingly.
Upon receiving information from the severe sepsis detector in the UCSF electronic health record, healthcare provider follows standard practices in assessing possible (severe) sepsis and intervening accordingly.
UCSF Moffit-Long Hospital
San Francisco, California, United States
Hospital length of stay
Time frame: Through study completion, an average of 45 days
In-hospital mortality
Time frame: Through study completion, an average of 45 days
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