A Rapid Diagnostic of Risk in Hospitalized Patients Using Machine Learning

NAActive, not recruitingINTERVENTIONAL
Enrollment

30,000

Participants

Timeline

Start Date

December 31, 2024

Primary Completion Date

December 31, 2026

Study Completion Date

December 31, 2026

Conditions
SepsisSepticemiaRespiratory FailureHemodynamic InstabilityCOVID-19Cardiac ArrestClinical Deterioration
Interventions
DEVICE

eCARTv5 clinical deterioration monitoring

eCART is a predictive analytic used for the identification of acute clinical deterioration built upon more than a decade of ongoing scientific research and chronicled in numerous peer-reviewed publications. eCART draws upon readily available patient data from the EHR, rapidly quantifies disease severity, and predicts the likelihood of critical illness onset.

OTHER

Standard of care control

Standard of care is the health system's clinical best practices and workflows for identifying high-risk patients for clinical deterioration, including other tools already built into the electronic health record (EHR). Hospitals that do not implement eCARTv5 will be compared as a control against hospitals that do implement eCARTv5.

Trial Locations (3)

33759

BayCare Health System, Clearwater

53792

University of Wisconsin Health, Madison

06510

Yale New Haven Health System, New Haven

All Listed Sponsors
collaborator

Biomedical Advanced Research and Development Authority

FED

collaborator

University of Chicago

OTHER

collaborator

BayCare Health System

OTHER

collaborator

University of Wisconsin, Madison

OTHER

collaborator

Yale University

OTHER

lead

AgileMD, Inc.

INDUSTRY