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A Study of Emergency Department AI Prediction Impact

Sponsor
Mayo Clinic (Other)
Overall Status
Enrolling by invitation
CT.gov ID
NCT05683899
Collaborator
(none)
400
Enrollment
1
Location
8.9
Anticipated Duration (Months)
44.9
Patients Per Site Per Month

Study Details

Study Description

Brief Summary

The purpose of this study is to evaluate the impact of an AI admission prediction tool on the number of preventable hospital admissions, emergency department (ED) length of stay, when the predictions are displayed only to a dedicated ED triage team. Also, to evaluate user perceptions of the AI tool among the triage team users and medical officer of the day users. Additionally, to evaluate any impact of the AI tool on the number of interventions performed by the triage team, and to evaluate the impact of the tool on time-to-admission after an admission order is placed.

Condition or Disease Intervention/Treatment Phase

    Study Design

    Study Type:
    Observational
    Anticipated Enrollment :
    400 participants
    Observational Model:
    Cohort
    Time Perspective:
    Prospective
    Official Title:
    Evaluation of Emergency Department AI Prediction Algorithm
    Actual Study Start Date :
    Jan 3, 2023
    Anticipated Primary Completion Date :
    Oct 1, 2023
    Anticipated Study Completion Date :
    Oct 1, 2023

    Arms and Interventions

    Arm Intervention/Treatment
    Group A

    141 days with AI scores displayed
    Group B

    141 days with AI scores not displayed

    Outcome Measures

    Primary Outcome Measures

    1. Hospital Admissions [282 days]

      Number of avoidable admissions prevented as a fraction of all ED patients in a day, specifically, the number of patients who were seen by the SAPPHIRE triage team and discharged home

    Eligibility Criteria

    Criteria

    Ages Eligible for Study:
    18 Years and Older
    Sexes Eligible for Study:
    All
    Accepts Healthy Volunteers:
    Yes
    Inclusion Criteria:

    • For the survey component, any HIM clinician that works a shift in the triage area, ED physicians, and the medical officer of the day will be included.

    • For length of stay data, adult patients registered in the Mayo Clinic-Rochester St. Mary's Emergency Department will be included.

    Exclusion Criteria:

    • For the survey, clinicians not working a triage shift during the study period will be excluded.

    • For the length of stay analysis, only adult ED patients will be included, who do not triaged to the behavioral health/psychiatry pathway, nor patients who are triaged to the Emergency Department observation pathway.

    Contacts and Locations

    Locations

    Site City State Country Postal Code
    1 Mayo Clinic Minnesota Rochester Minnesota United States 55905

    Sponsors and Collaborators

    • Mayo Clinic

    Investigators

    • Principal Investigator: Alexander Ryu, MD, Mayo Clinic

    Study Documents (Full-Text)

    None provided.

    More Information

    Additional Information:

    Publications

    None provided.
    Responsible Party:
    Alexander J. Ryu, Principal Investigator, Mayo Clinic
    ClinicalTrials.gov Identifier:
    NCT05683899
    Other Study ID Numbers:
    • 22-011319
    First Posted:
    Jan 13, 2023
    Last Update Posted:
    Feb 2, 2023
    Last Verified:
    Jan 1, 2023
    Individual Participant Data (IPD) Sharing Statement:
    No
    Plan to Share IPD:
    No
    Studies a U.S. FDA-regulated Drug Product:
    No
    Studies a U.S. FDA-regulated Device Product:
    No
    Keywords provided by Alexander J. Ryu, Principal Investigator, Mayo Clinic
    AI Prediction Algorithm
    Emergency Department
    Additional relevant MeSH terms:
    Emergencies

    Study Results

    No Results Posted as of Feb 2, 2023