Actively Recruiting
Strategy for Early Recognition of Cancer, COPD, and Heart Failure in the Emergency Department
Led by NHS Greater Glasgow and Clyde · Updated on 2026-06-01
17000
Participants Needed
1
Research Sites
N/A
Total Duration
On this page
Sponsors
N
NHS Greater Glasgow and Clyde
Lead Sponsor
U
University of Glasgow
Collaborating Sponsor
AI-Summary
What this Trial Is About
Researchers are evaluating whether using an artificial intelligence (AI) computer program can help doctors diagnose heart and lung problems from chest x-rays in the Emergency Department (ED) at Queen Elizabeth University Hospital. The study aims to compare the number of patients newly diagnosed with heart or lung conditions such as chronic obstructive pulmonary disease (COPD), heart failure, or lung cancer when doctors have access to AI results versus when they do not. This study includes adults aged 18 and older who have chest x-rays taken in the ED. The study compares two groups: one where doctors receive results from the Harrison.ai Chest X-Ray AI program alongside their usual interpretation, and one where doctors do not have access to the AI results. Patients with chest x-rays flagged for heart failure or COPD by the AI will be invited for further outpatient assessment unless they have had prior testing. Those flagged for lung cancer will be reviewed by a study radiologist. The study consists of multiple components including retrospective review, a live prospective trial, qualitative evaluations, and health economic analysis. Participants will have their chest x-rays analyzed with or without AI support, and those flagged for possible conditions will undergo further assessments. Researchers will track new diagnoses, hospital admission duration, time to treatment or diagnostic testing, specialist reviews, readmission rates, and the acceptance of AI among clinicians. The main outcome is the proportion of patients with a new confirmed diagnosis of heart failure over 12 months. The study will follow participants and collect data for up to a year to evaluate AI's impact on diagnosis and care.
CONDITIONS
Brief Title
Strategy for EArly Recognition of Cancer, COPD & Heart Failure in the Emergency Department
Who Can Participate
Eligibility Criteria
You may qualify if you...
- Frontal chest x-ray (AP or PA) taken in the Queen Elizabeth University Hospital Emergency Department
- Patients aged 18 or older
- Appropriate x-ray metadata available for AI processing
- Able to provide written informed consent in English (for focus groups)
- Working as a doctor or advanced practitioner in relevant departments (for clinician focus groups)
- Patients without terminal illness or advanced frailty (for diagnostic clinic)
- Usual healthcare provider based in NHS Greater Glasgow and Clyde (for diagnostic clinic)
You will not qualify if you...
- Patient has requested removal from the study or objected to AI use in care
- Not available for follow-up within NHS Greater Glasgow and Clyde
- Referred to palliative care for end-stage disease or severely frail (bedbound)
- Unable to provide informed written consent in English
- Under 18 years old
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
Your Study Journey
Duration - 2 to 4 weeks
Participants are screened for eligibility to participate in the trial.
1 visit (in-person)
Duration - Single day
Participants receive a chest x-ray in the Emergency Department, which is interpreted with or without AI support to aid diagnosis of heart and lung conditions.
1 visit (in-person)
Duration - Variable post-discharge period
Participants with chest x-rays flagged for heart failure or COPD by the AI will be invited to an outpatient clinic for further assessment if not previously tested or referred.
1 to 2 outpatient visits depending on findings
Duration - Up to 12 months
Participants are followed for up to 12 months to track new diagnoses and treatment initiation related to heart failure, COPD, and lung cancer.
Follow-up assessments as part of routine care; visit frequency varies
Trial Site Locations
Total: 1 location
1
Queen Elizabeth University Hospital
Glasgow, United Kingdom
Actively Recruiting
Research Team
C
Clea Du Toit
D
Dervla Carroll
How is the study designed?
Study Type
INTERVENTIONAL
Masking
SINGLE
Allocation
NON_RANDOMIZED
Model
PARALLEL
Primary Purpose
DIAGNOSTIC
Number of Arms
2
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