Effect of a Sepsis Prediction Algorithm on Patient Mortality, Length of Stay, and Readmission

Dascena0 sites75,147 target enrollmentJanuary 2017

ConditionsSevere Sepsis

Overview

Phase: Not Applicable
Intervention: Not specified
Conditions: Severe Sepsis
Sponsor: Dascena
Enrollment: 75147
Primary Endpoint: In-hospital mortality
Status: Completed
Last Updated: 6 years ago

Overview Investigators Eligibility Criteria Outcomes Similar Trials

Overview

Brief Summary

In this clinical outcomes analysis, the effect of a machine learning algorithm for severe sepsis prediction on in-hospital mortality, hospital length of stay, and 30-day readmission was evaluated.

Detailed Description

Materials and Methods: Clinical outcomes evaluation performed on a multiyear, multicenter clinical data set of real-world data containing 75,147 patient encounters from nine hospitals. Mortality, hospital length of stay, and 30-day readmission analysis performed for 17,758 adult patients who met two or more Systemic Inflammatory Response Syndrome (SIRS) criteria at any point during their stay.

Registry

clinicaltrials.gov

Start Date

January 2017

End Date

June 2018

Last Updated

6 years ago

Study Type

Interventional

Sex

All

Investigators

Sponsor

Dascena

Responsible Party

Sponsor

Eligibility Criteria

Inclusion Criteria

•All patients over the age of 18 presenting to the emergency department or admitted to an inpatient unit at the participating facilities were automatically included for clinical outcomes analysis