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Trial of Artificial Intelligence for Chest Radiography

Artificial Intelligence for Chest Radiography: Impact on Economics, Patient Outcomes and Radiology Service Delivery

Status
Not yet recruiting
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT06456203
Acronym
ACER
Enrollment
10000
Registered
2024-06-13
Start date
2024-10-31
Completion date
2025-12-31
Last updated
2024-06-13

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Lung Cancer, Pneumonia

Keywords

Radiology, artificial intelligence, triage, radiography

Brief summary

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.

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.

Interventions

DIAGNOSTIC_TESTAI

Artificial intelligence triage and reporting system

Sponsors

Duke-NUS Graduate Medical School
Lead SponsorOTHER

Study design

Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
DIAGNOSTIC
Masking
NONE

Eligibility

Sex/Gender
ALL
Age
14 Years to 130 Years
Healthy volunteers
Yes

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

Design outcomes

Primary

MeasureTime frameDescription
Report generation time12 monthsTime for radiologist to produce each individual CXR report
Turnaround Time12 monthsTime from patient arrival at radiography department to time for clinical team to receive report
Time to discharge12 monthsTime from patient arrival at radiography department to time to discharge from hospital

Secondary

MeasureTime frameDescription
30-day patient readmission rate12 monthsRate of readmission of patient to hospital after discharge within 30 days

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026