Strategy for EArly Recognition of Cancer, COPD & Heart Failure in the Emergency Department

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 an artificial intelligence (AI) computer programme can help doctors diagnose heart and lung problems from chest x-rays. The computer programme is made by Harrison.ai. It is approved for use in the United Kingdom (UK), United States of America (US) and the European Union (EU). Studies have been carried out previously to make sure it is safe to use and that it can detect signs of heart and lung problems.

Many people who come to ED have a chest x-ray. Chest x-rays can show signs of heart or lung problems, which might be causing a patient's symptoms. All doctors can interpret chest x-rays. However, doctors who specialise in interpreting scans (radiologists) also provide an expert report for chest x-rays, describing what they have found. It can take a long time for chest x-ray reports to come back. Sometimes, doctors might miss signs of heart or lung problems.

We want to see if using a computer programme to help doctors interpret chest x-rays could lead to more patients getting an accurate diagnosis. We want to compare how many people are diagnosed with heart or lung problems (Chronic obstructive pulmonary disease [COPD], heart failure or lung cancer) for the first time when doctors have access to the computer programme results, in comparison to when they don't.

Patients older than 18 who have a chest x-ray in ED will be included.

Patients with chest x-rays flagged by the computer programme for heart failure or COPD will be invited to an outpatient clinic for further assessment post-discharge, providing they have not been referred for testing or had testing previously.

All patients with chest x-rays flagged for lung cancer will be reviewed and acted on by the study radiologist.

The study consists of 1) a retrospective component; 2) a prospective live trial; 3) a qualitative evaluation of acceptability to patients and clinicians, and 4) a health economic analysis.

Inclusion criteria

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 criteria

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