ACCEPT v1.0
Research type
Research Study
Full title
A mixed methods study to assess the clinical effectiveness and acceptability of qER artificial intelligence software to prioritise CT Head interpretation.
IRAS ID
313507
Contact name
M H Shuaib
Contact email
Sponsor organisation
Guys and St Thomas NHS Foundation Trust
Duration of Study in the UK
1 years, 4 months, 31 days
Research summary
Non-Contrast Computed Tomography (NCCT) of the head is the most common imaging method used to assess patients attending the Emergency Department (ED) with a wide range of significant neurological presentations including trauma, stroke, seizure and reduced consciousness. Rapid review of the images supports clinical decision-making including treatment and onward referral.
Radiologists, those reporting scans, often have significant backlogs and are unable to prioritise abnormal images of patients with time critical abnormalities. Similarly, identification of normal scans would support patient turnover in ED with significant waits and pressure on resources.
To address this problem, Qure.AI has worked to develop the market approved qER algorithm, which is a software program that can analyse CT head to identify presence of abnormalities supporting workflow prioritisation.
This study will trial the software in 4 NHS hospitals across the UK to evaluate the ability of the software to reduce the turnaround time of reporting scans with abnormalities that need to be prioritised.
REC name
East Midlands - Leicester Central Research Ethics Committee
REC reference
23/EM/0108
Date of REC Opinion
12 May 2023
REC opinion
Favourable Opinion