Strategy for EArly Recognition of Cancer, COPD & Heart Failure in the Emergency Department
NHS Greater Glasgow and Clyde
17,000 participants
May 25, 2026
INTERVENTIONAL
Conditions
Summary
SEARCH-ED is a research study which is running in Emergency Department (ED) of the Queen Elizabeth University Hospital. The aim of the study is to find out if using a computer programme can help doctors diagnose heart and lung problems from chest x-rays. We want to compare how many people are diagnosed with heart or lung problems for the first time when doctors have access to the computer programme results, in comparison to when they don't.
Eligibility
Inclusion Criteria15
- Unconsented Use of Harrison CXR Algorithm in Emergency Department (ED):
- Frontal Chest X-Ray (CXR) (AP or PA) acquired in the Queen Elizabeth University Hospital (QEUH) ED
- Patients aged 18 or over
- Appropriate meta data (DICOM) to allow for Harrison CXR processing and secondary capture report provision.
- Patient Focus Groups:
- Aged 18 or over
- Able to provide written, informed consent in English.
- Clinician Focus Groups:
- Aged 18 or over
- Able to provide written, informed consent in English.
- Working as a doctor, advanced nurse practitioner or advanced clinical practitioner in ED, radiology or downstream medical specialties
- For post-implementation focus groups only, must have at least 4 months experience of working with Harrison CXR algorithm.
- Diagnostic Clinic:
- Patients without terminal illness or advanced frailty
- Usual healthcare provider based in NHS GGC
Exclusion Criteria8
- Applies to use of unconsented CXRs:
- \- Patient has requested that they are removed from the study, or has objected to the use of AI in their routine clinical care and this has been subsequently upheld by the health board.
- Applies to invitation to combined diagnostic clinic:
- Patients not available to follow up, including patients i.e. whose the patient's usual care (or onward care following index admission) is out-with NHS GGC.
- Patients who have been referred to palliative care for end-stage disease, or patients with severe frailty (i.e. bedbound) will not be invited to the combined diagnostic clinic
- For Patient and Clinician Focus Groups:
- Unable to provide informed written consent in English
- Aged <18
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Interventions
The Harrison.ai CXR module is an AI-driven clinical decision support tool that is designed to augment clinical interpretation of CXRs. It is a Class IIb CE-marked device which is able to detect up to 124 findings on a CXR.
Locations(1)
View Full Details on ClinicalTrials.gov
For the most up-to-date information, visit the official listing.
NCT07391280