Recruitment

Recruitment Status
Not yet recruiting
Estimated Enrollment
Same as current

Summary

Conditions
Sepsis
Type
Interventional
Phase
Not Applicable
Design
Allocation: RandomizedIntervention Model: Single Group AssignmentMasking: Double (Participant, Investigator)Primary Purpose: Prevention

Participation Requirements

Age
Between 18 years and 110 years
Gender
Both males and females

Description

A means to identify patients before they become ill may improve the effectiveness of established therapies.Epic's electronic medical record (Epic systems, Verona, WI) contains a surveillance tool that uses predictive analytics to identify patients at risk of becoming septic four hours after the aler...

A means to identify patients before they become ill may improve the effectiveness of established therapies.Epic's electronic medical record (Epic systems, Verona, WI) contains a surveillance tool that uses predictive analytics to identify patients at risk of becoming septic four hours after the alert becomes active. This affords the opportunity to intervene sooner, but it remains unclear what the best course of action should be in a population at risk of sepsis, only some of which may go on to develop the illness. We propose an automatic intervention, consisting of enhanced monitoring, that is tied to the alert. No therapeutics will be mandated. Instead, additional monitoring information will lead to faster diagnosis and therapy, and improved clinical outcomes.

Tracking Information

NCT #
NCT03473769
Collaborators
Not Provided
Investigators
Principal Investigator: Mark Nunnally, MD NYU Langone Health