search
Back to results

Effect of a Sepsis Prediction Algorithm on Clinical Outcomes

Primary Purpose

Severe Sepsis

Status
Completed
Phase
Not Applicable
Locations
Study Type
Interventional
Intervention
InSight
Sponsored by
Dascena
About
Eligibility
Locations
Arms
Outcomes
Full info

About this trial

This is an interventional diagnostic trial for Severe Sepsis focused on measuring Dascena, Patient mortality, Length of stay, Readmissions, Algorithm, Diagnostic, Clinical outcomes

Eligibility Criteria

18 Years - undefined (Adult, Older Adult)All SexesAccepts Healthy Volunteers

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

Exclusion Criteria:

  • Patients under the age of 18

Sites / Locations

    Arms of the Study

    Arm 1

    Arm Type

    Experimental

    Arm Label

    Comparator

    Arm Description

    The comparator arm will involve patients monitored by InSight.

    Outcomes

    Primary Outcome Measures

    In-hospital mortality
    Rate of in-hospital mortality based on SIRS criteria

    Secondary Outcome Measures

    Hospital length of stay
    Duration of hospital length of stay in days based on SIRS criteria
    30-day readmissions
    Rate of patient readmissions within 30 days

    Full Information

    First Posted
    May 17, 2019
    Last Updated
    May 22, 2019
    Sponsor
    Dascena
    search

    1. Study Identification

    Unique Protocol Identification Number
    NCT03960203
    Brief Title
    Effect of a Sepsis Prediction Algorithm on Clinical Outcomes
    Official Title
    Effect of a Sepsis Prediction Algorithm on Patient Mortality, Length of Stay, and Readmission
    Study Type
    Interventional

    2. Study Status

    Record Verification Date
    May 2019
    Overall Recruitment Status
    Completed
    Study Start Date
    January 2017 (Actual)
    Primary Completion Date
    June 2018 (Actual)
    Study Completion Date
    June 2018 (Actual)

    3. Sponsor/Collaborators

    Responsible Party, by Official Title
    Sponsor
    Name of the Sponsor
    Dascena

    4. Oversight

    Studies a U.S. FDA-regulated Drug Product
    No
    Studies a U.S. FDA-regulated Device Product
    No
    Data Monitoring Committee
    No

    5. Study Description

    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.

    6. Conditions and Keywords

    Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
    Severe Sepsis
    Keywords
    Dascena, Patient mortality, Length of stay, Readmissions, Algorithm, Diagnostic, Clinical outcomes

    7. Study Design

    Primary Purpose
    Diagnostic
    Study Phase
    Not Applicable
    Masking
    None (Open Label)
    Enrollment
    75147 (Actual)

    8. Arms, Groups, and Interventions

    Arm Title
    Comparator
    Arm Type
    Experimental
    Arm Description
    The comparator arm will involve patients monitored by InSight.
    Intervention Type
    Diagnostic Test
    Intervention Name(s)
    InSight
    Intervention Description
    Clinical decision support (CDS) system for severe sepsis detection and prediction
    Primary Outcome Measure Information:
    Title
    In-hospital mortality
    Description
    Rate of in-hospital mortality based on SIRS criteria
    Time Frame
    1 year
    Secondary Outcome Measure Information:
    Title
    Hospital length of stay
    Description
    Duration of hospital length of stay in days based on SIRS criteria
    Time Frame
    1 year
    Title
    30-day readmissions
    Description
    Rate of patient readmissions within 30 days
    Time Frame
    1 year

    10. Eligibility

    Sex
    All
    Minimum Age & Unit of Time
    18 Years
    Accepts Healthy Volunteers
    Accepts Healthy Volunteers
    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 Exclusion Criteria: Patients under the age of 18
    Overall Study Officials:
    First Name & Middle Initial & Last Name & Degree
    Ritankar Das, MSc
    Organizational Affiliation
    Dascena
    Official's Role
    Principal Investigator

    12. IPD Sharing Statement

    Citations:
    PubMed Identifier
    32354696
    Citation
    Burdick H, Pino E, Gabel-Comeau D, McCoy A, Gu C, Roberts J, Le S, Slote J, Pellegrini E, Green-Saxena A, Hoffman J, Das R. Effect of a sepsis prediction algorithm on patient mortality, length of stay and readmission: a prospective multicentre clinical outcomes evaluation of real-world patient data from US hospitals. BMJ Health Care Inform. 2020 Apr;27(1):e100109. doi: 10.1136/bmjhci-2019-100109.
    Results Reference
    derived

    Learn more about this trial

    Effect of a Sepsis Prediction Algorithm on Clinical Outcomes

    We'll reach out to this number within 24 hrs