Lung Cancer, Pneumonia
Conditions
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
Artificial intelligence triage and reporting system
Sponsors
Study design
Eligibility
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
| Measure | Time frame | Description |
|---|---|---|
| Report generation time | 12 months | Time for radiologist to produce each individual CXR report |
| Turnaround Time | 12 months | Time from patient arrival at radiography department to time for clinical team to receive report |
| Time to discharge | 12 months | Time from patient arrival at radiography department to time to discharge from hospital |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| 30-day patient readmission rate | 12 months | Rate of readmission of patient to hospital after discharge within 30 days |