Predictive algoRithm for EValuation and Intervention in SEpsis (PREVISE)

Dascena

Status: Completed

Conditions: Severe Sepsis; Septic Shock; Sepsis

Treatments: Other: Severe Sepsis Prediction; Other: Severe Sepsis Detection

Study type: Interventional

Funder types: Other; Industry

Identifiers

NCT03235193

1097090-1

Details and patient eligibility

About

In this prospective study, the ability of a machine learning algorithm to predict sepsis and influence clinical outcomes, will be investigated at Cabell Huntington Hospital (CHH).

Enrollment: 2,296 patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• All adult patients visiting the emergency department, or admitted to the participating intensive care unit (ICU) wards of Cabell Huntington Hospital will be eligible.

Exclusion criteria

• All patients younger than 18 years of age will be excluded.

Trial design

Primary purpose: Diagnostic

Allocation: Non-Randomized

Interventional model: Factorial Assignment

Masking: None (Open label)

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2,296 participants in 2 patient groups

With InSight

Experimental group

Description:

Healthcare provider receives an alert from InSight for patients trending towards severe sepsis. Healthcare provider also receives information from the severe sepsis detector in the CHH electronic health record.

Treatment:

Other: Severe Sepsis Prediction

Other: Severe Sepsis Detection

Without Insight

Active Comparator group

Description:

Healthcare provider does not receive any alerts from InSight. Healthcare provider receives information from the severe sepsis detector in the CHH electronic health record.

Treatment:

Other: Severe Sepsis Detection