Trial of Artificial Intelligence for Chest Radiography (ACER)
June 11, 2024 updated by: Charlene Liew, Duke-NUS Graduate Medical School
Artificial Intelligence for Chest Radiography: Impact on Economics, Patient Outcomes and Radiology Service Delivery
Randomized Clinical Trial of the impact of Chest radiograph AI-assisted triage and report generation upon clinical outcomes and an economic analysis of impact of AI decision support on radiology service delivery.
Study Overview
Status
Not yet recruiting
Conditions
Intervention / Treatment
Detailed Description
Randomized, prospective selection of patients. Control group involves radiologists reporting chest radiographs as per reference standard clinical workflow Intervention group involves radiologists assisted with AI reporting an AI-triaged worklist of chest radiographs using an AI report generation tool Clinical outcomes on patients are studied at pre-determined study endpoints, including time to discharge from the hospital and re-admission rates.
Economic analysis on cost-avoidance from man-hours saved from report generation and triage.
Study Type
Interventional
Enrollment (Estimated)
10000
Phase
- Not Applicable
Participation Criteria
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
Eligibility Criteria
Ages Eligible for Study
- Child
- Adult
- Older Adult
Accepts Healthy Volunteers
Yes
Description
Inclusion Criteria:
- All patients attending radiography to have chest radiographs during the study period
Exclusion Criteria:
- age below 14
- deceased before discharge
- chest radiograph performed in non-standard projections
Study Plan
This section provides details of the study plan, including how the study is designed and what the study is measuring.
How is the study designed?
Design Details
- Primary Purpose: Diagnostic
- Allocation: Randomized
- Interventional Model: Parallel Assignment
- Masking: None (Open Label)
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
|---|---|
|
No Intervention: Control Arm
Chest radiographs reported with AI assistance
|
|
|
Active Comparator: AI assisted
AI assisted detection, triage and reporting of CXR
|
Artificial intelligence triage and reporting system
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Report generation time
Time Frame: 12 months
|
Time for radiologist to produce each individual CXR report
|
12 months
|
|
Turnaround Time
Time Frame: 12 months
|
Time from patient arrival at radiography department to time for clinical team to receive report
|
12 months
|
|
Time to discharge
Time Frame: 12 months
|
Time from patient arrival at radiography department to time to discharge from hospital
|
12 months
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
30-day patient readmission rate
Time Frame: 12 months
|
Rate of readmission of patient to hospital after discharge within 30 days
|
12 months
|
Collaborators and Investigators
This is where you will find people and organizations involved with this study.
Sponsor
Study record dates
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.
Study Major Dates
Study Start (Estimated)
October 1, 2024
Primary Completion (Estimated)
September 1, 2025
Study Completion (Estimated)
December 1, 2025
Study Registration Dates
First Submitted
June 4, 2024
First Submitted That Met QC Criteria
June 11, 2024
First Posted (Actual)
June 13, 2024
Study Record Updates
Last Update Posted (Actual)
June 13, 2024
Last Update Submitted That Met QC Criteria
June 11, 2024
Last Verified
June 1, 2024
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- 2023/2280
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
NO
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
No
Studies a U.S. FDA-regulated device product
No
product manufactured in and exported from the U.S.
No
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.