Back to resultsTransforming ED Throughput With AI-Driven Clinical Decision Support System (TEDAI)
Primary Purpose
Critical Care, Emergency Treatment, Triage
Status
Completed
Phase
Not Applicable
Locations
Taiwan
Study Type
Interventional
Intervention
AI-assisted models providing diagnosis and prognostic information
Critical treatment
Sponsored by
About this trial
This is an interventional health services research trial for Critical Care focused on measuring Critical Care, Emergency Treatment, Triage, Readmission
Eligibility Criteria
Inclusion Criteria:
- ED patients aged 20 years or older
- Patients were treated by the recruited 16 ED attendings.
Exclusion Criteria:
- Patients aged less than 20 years.
- Patients were not treated by the recruited 16 ED attendings.
Sites / Locations
- National Taiwan University Hospital
Arms of the Study
Arm 1
Arm 2
Arm Type
Active Comparator
Placebo Comparator
Arm Label
AI-assisted
Usual care
Arm Description
AI-assisted models providing diagnosis and prognostic information
usual care without AI-assisted models providing diagnosis and prognostic information
Outcomes
Primary Outcome Measures
ED length of stay
Secondary Outcome Measures
Full Information
NCT ID
NCT05272267
First Posted
February 28, 2022
Last Updated
July 28, 2023
Sponsor
National Taiwan University Hospital
1. Study Identification
Unique Protocol Identification Number
NCT05272267
Brief Title
Transforming ED Throughput With AI-Driven Clinical Decision Support System
Acronym
TEDAI
Official Title
Transforming ED Throughput With AI-Driven Clinical Decision Support System (TEDAI): The Impact on the Delivery of Care and Patient Experience
Study Type
Interventional
2. Study Status
Record Verification Date
July 2022
Overall Recruitment Status
Completed
Study Start Date
August 30, 2022 (Actual)
Primary Completion Date
December 31, 2022 (Actual)
Study Completion Date
April 27, 2023 (Actual)
3. Sponsor/Collaborators
Responsible Party, by Official Title
Sponsor
Name of the Sponsor
National Taiwan University Hospital
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
The aims of this study is to integrate real-time data flow infrastructure between hospital information system and AI models and to conduct a cluster randomized crossover trial to evaluate the efficacy of the AI models in improving patient flow and relieving ED crowding.
6. Conditions and Keywords
Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Critical Care, Emergency Treatment, Triage, Readmission
Keywords
Critical Care, Emergency Treatment, Triage, Readmission
7. Study Design
Primary Purpose
Health Services Research
Study Phase
Not Applicable
Interventional Study Model
Crossover Assignment
Masking
None (Open Label)
Allocation
Randomized
Enrollment
4016 (Actual)
8. Arms, Groups, and Interventions
Arm Title
AI-assisted
Arm Type
Active Comparator
Arm Description
AI-assisted models providing diagnosis and prognostic information
Arm Title
Usual care
Arm Type
Placebo Comparator
Arm Description
usual care without AI-assisted models providing diagnosis and prognostic information
Intervention Type
Other
Intervention Name(s)
AI-assisted models providing diagnosis and prognostic information
Intervention Description
AI-assisted models providing diagnosis and prognostic information in the ED, including triage, ICD coding, chest x ray alerts, critical event alerts, readmission prediction, and post-cardiac arrest prognostication.
Intervention Type
Procedure
Intervention Name(s)
Critical treatment
Intervention Description
Critical treatment of the emergency room
Primary Outcome Measure Information:
Title
ED length of stay
Time Frame
From ED arrival to 3 days after ED discharge. For hospitalized patients with cardiac arrest, the outcome ascertainment continues until hospital discharge.
10. Eligibility
Sex
All
Minimum Age & Unit of Time
20 Years
Accepts Healthy Volunteers
No
Eligibility Criteria
Inclusion Criteria:
ED patients aged 20 years or older
Patients were treated by the recruited 16 ED attendings.
Exclusion Criteria:
Patients aged less than 20 years.
Patients were not treated by the recruited 16 ED attendings.
Overall Study Officials:
First Name & Middle Initial & Last Name & Degree
Dr. Huang
Organizational Affiliation
National Taiwan University Hospital
Official's Role
Study Chair
Facility Information:
Facility Name
National Taiwan University Hospital
City
Taipei
Country
Taiwan
12. IPD Sharing Statement
Learn more about this trial
Transforming ED Throughput With AI-Driven Clinical Decision Support System
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