TY - JOUR
T1 - Spirometry services in England post-pandemic and the potential role of AI support software
T2 - a qualitative study of challenges and opportunities
AU - Doe, Gillian
AU - Taylor, Stephanie J.C.
AU - Topalovic, Marko
AU - Russell, Richard
AU - Evans, Rachael A.
AU - Maes, Julie
AU - Van Orshovon, Karolien
AU - Sunjaya, Anthony
AU - Scott, David
AU - Prevost, A. Toby
AU - El-Emir, Ethaar
AU - Harvey, Jennifer
AU - Hopkinson, Nicholas S.
AU - Kon, Samantha S.
AU - Patel, Suhani
AU - Jarrold, Ian
AU - Spain, Nanette
AU - Man, William D-C
AU - Hutchinson, Ann
N1 - Funding Information:
This study is funded by the National Institute for Health and Care Research (NIHR) through an AI Award in Health and Care (Phase 3 — Application: Grant number AI_ AWARD02204). The study is also supported by the NIHR Leicester Biomedical Research Centre — Respiratory theme. Stephanie JC Taylor is supported by the NIHR Applied Research Collaboration North Thames. Richard Russell is supported by the NIHR Oxford Biomedical Research Centre — Respiratory. Rachael A Evans is supported by an NIHR Clinical Scientist fellowship. The views expressed in this publication are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care.
Publisher Copyright:
©The Authors.
PY - 2023/12
Y1 - 2023/12
N2 - Background Spirometry 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. Aim To 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 setting Semi-structured interviews with stakeholders in spirometry services across England. Method Participants 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. Results In 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. Conclusion Stakeholders 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.
AB - Background Spirometry 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. Aim To 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 setting Semi-structured interviews with stakeholders in spirometry services across England. Method Participants 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. Results In 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. Conclusion Stakeholders 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.
KW - artificial intelligence
KW - chronic obstructive pulmonary disease
KW - primary care
KW - qualitative research
KW - spirometry
KW - trust
UR - http://www.scopus.com/inward/record.url?scp=85178650489&partnerID=8YFLogxK
U2 - 10.3399/BJGP.2022.0608
DO - 10.3399/BJGP.2022.0608
M3 - Article
C2 - 37903639
AN - SCOPUS:85178650489
SN - 0960-1643
VL - 73
SP - e915-e923
JO - British Journal of General Practice
JF - British Journal of General Practice
IS - 737
ER -