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.

• Duration of admission during index hospitalisation [Срок оценки: 12 months]
• Time to initiation of guideline-based, long-term therapy for Chronic obstructive pulmonary disease (COPD) and Heart Failure. [Срок оценки: 12 months]
• Time to diagnostic testing for Heart Failure, COPD and lung cancer (echocardiography, spirometry, CT). [Срок оценки: 12 months]
• Time to inpatient or outpatient specialist review and confirmation of lung cancer, COPD or Heart Failure [Срок оценки: 12 months]
• Acceptability of AI-supported interpretation of Chest X-Ray for Emergency Department clinicians pre and post intervention using Theoretical Framework of Acceptability (TFA) [Срок оценки: Baseline and 12 months]
• Readmission rate within 90 days [Срок оценки: 3 months]
• Proportion of patients with new diagnosis of lung cancer detected by an AI-Chest X-Ray algorithm [Срок оценки: 12 months]
• Proportion of patients with new diagnosis of COPD detected by an AI-Chest X-Ray algorithm [Срок оценки: 12 months]
• Proportion of patients with clinically-confirmed known diagnosis of lung cancer, Heart Failure and COPD detected by an AI-Chest X-Ray algorithm [Срок оценки: 12 months]
• Percentage of Chest X-Rays not identified by an AI-CXR algorithm that have a subsequent diagnosis of Heart Failure, COPD or lung cancer within 6 months of index imaging (Emergency Department Chest X-Ray). [Срок оценки: 6 months]
• Statistical analysis of model performance e.g. sensitivity, specificity, positive and negative predictive value [Срок оценки: 12 months]