• Gillian Doe, Stephanie Jc Taylor, Marko Topalovic, Richard Russell, Rachael A Evans, Julie Maes, Karolien Van Orshovon, Anthony Sunjaya, David Scott, A Toby Prevost, Ethaar El-Emir, Jennifer Harvey, Nicholas S Hopkinson, Samantha S Kon, Suhani Patel, Ian Jarrold, Nanette Spain, William D-C Man, and Ann Hutchinson.
• Department of Respiratory Science, University of Leicester, Leicester, UK.
• Br J Gen Pract. 2023 Dec 1; 73 (737): e915e923e915-e923.

BackgroundSpirometry services to diagnose and monitor lung disease in primary care were identified as a priority in the NHS Long Term Plan, and are restarting post-COVID-19 pandemic in England; however, evidence regarding best practice is limited.AimTo explore perspectives on spirometry provision in primary care, and the potential for artificial intelligence (AI) decision support software to aid quality and interpretation.Design And SettingSemi-structured interviews with stakeholders in spirometry services across England.MethodParticipants were recruited by snowball sampling. Interviews explored the pre- pandemic delivery of spirometry, restarting of services, and perceptions of the role of AI. Transcripts were analysed thematically.ResultsIn total, 28 participants (mean years' clinical experience = 21.6 [standard deviation 9.4, range 3-40]) were interviewed between April and June 2022. Participants included clinicians (n = 25) and commissioners (n = 3); eight held regional and/or national respiratory network advisory roles. Four themes were identified: 1) historical challenges in provision of spirometry services; 2) inequity in post- pandemic spirometry provision and challenges to restarting spirometry in primary care; 3) future delivery closer to patients' homes by appropriately trained staff; and 4) the potential for AI to have supportive roles in spirometry.ConclusionStakeholders highlighted historic challenges and the damaging effects of the pandemic contributing to inequity in provision of spirometry, which must be addressed. Overall, stakeholders were positive about the potential of AI to support clinicians in quality assessment and interpretation of spirometry. However, it was evident that validation of the software must be sufficiently robust for clinicians and healthcare commissioners to have trust in the process.© The Authors.

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