Comparing performance of primary care clinicians in the interpretation of SPIROmetry with or without Artificial Intelligence Decision support software (SPIRO-AID): a protocol for a randomised controlled trial
William D-C Man,
Winston Banya,
Rachael A Evans,
Karl P Sylvester,
Nicholas S Hopkinson,
A Toby Prevost,
Jennifer Harvey,
Marko Topalovic,
David A Scott,
Stephanie JC Taylor,
Ethaar El-Emir,
Ian Jarrold,
Gillian Doe,
Nannette Spain,
George D Edwards,
Karolien Van Orshoven,
Anthony P Sunjaya,
Samantha S Kon
Affiliations
William D-C Man
2 Respiratory Medicine, Royal Brompton and Harefield Hospitals, London, UK
Winston Banya
2 Respiratory Medicine, Royal Brompton and Harefield Hospitals, London, UK
Rachael A Evans
1 NIHR Biomedical Research Centre, University of Leicester, Leicester, UK
Karl P Sylvester
5 Cambridge Respiratory Physiology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
Nicholas S Hopkinson
1 National Heart and Lung Institute, Imperial College London, London, UK
A Toby Prevost
8 Nightingale-Saunders Clinical Trials and Epidemiology Unit, King`s College London, London, UK
Jennifer Harvey
2 Harefield Respiratory Research Group, Royal Brompton & Harefield Hospitals, Guy’s and St Thomas’ NHS Foundation Trust, UK, London, UK
Marko Topalovic
3 ARTIQ, Leuven, Belgium
David A Scott
7 Southampton Health Technology Assessments Centre, University of Southampton, Southampton, UK
Stephanie JC Taylor
9 Wolfson Institute of Population Health, Queen Mary University of London, London, UK
Ethaar El-Emir
2 Harefield Respiratory Research Group, Royal Brompton & Harefield Hospitals, Guy’s and St Thomas’ NHS Foundation Trust, UK, London, UK
Ian Jarrold
12 Asthma and Lung UK, London, UK
Gillian Doe
1 NIHR Biomedical Research Centre, University of Leicester, Leicester, UK
Nannette Spain
CREATE-ILD Patient and Public Involvement Group, Guy`s and St Thomas` NHS Foundation Trust, London, UK
George D Edwards
2 Harefield Respiratory Research Group, Royal Brompton & Harefield Hospitals, Guy’s and St Thomas’ NHS Foundation Trust, UK, London, UK
Karolien Van Orshoven
3 ARTIQ, Leuven, Belgium
Anthony P Sunjaya
2 Harefield Respiratory Research Group, Royal Brompton & Harefield Hospitals, Guy’s and St Thomas’ NHS Foundation Trust, UK, London, UK
Samantha S Kon
2 Harefield Respiratory Research Group, Royal Brompton & Harefield Hospitals, Guy’s and St Thomas’ NHS Foundation Trust, UK, London, UK
Introduction Spirometry is a point-of-care lung function test that helps support the diagnosis and monitoring of chronic lung disease. The quality and interpretation accuracy of spirometry is variable in primary care. This study aims to evaluate whether artificial intelligence (AI) decision support software improves the performance of primary care clinicians in the interpretation of spirometry, against reference standard (expert interpretation).Methods and analysis A parallel, two-group, statistician-blinded, randomised controlled trial of primary care clinicians in the UK, who refer for, or interpret, spirometry. People with specialist training in respiratory medicine to consultant level were excluded. A minimum target of 228 primary care clinician participants will be randomised with a 1:1 allocation to assess fifty de-identified, real-world patient spirometry sessions through an online platform either with (intervention group) or without (control group) AI decision support software report. Outcomes will cover primary care clinicians’ spirometry interpretation performance including measures of technical quality assessment, spirometry pattern recognition and diagnostic prediction, compared with reference standard. Clinicians’ self-rated confidence in spirometry interpretation will also be evaluated. The primary outcome is the proportion of the 50 spirometry sessions where the participant’s preferred diagnosis matches the reference diagnosis. Unpaired t-tests and analysis of covariance will be used to estimate the difference in primary outcome between intervention and control groups.Ethics and dissemination This study has been reviewed and given favourable opinion by Health Research Authority Wales (reference: 22/HRA/5023). Results will be submitted for publication in peer-reviewed journals, presented at relevant national and international conferences, disseminated through social media, patient and public routes and directly shared with stakeholders.Trial registration number NCT05933694.
