Clinician views on how clinical decision support systems can help diagnose asthma in primary care: a qualitative study

Luke Daines*, Eddie Donaghy, Anne Canny, Victoria Murray, Leo Campbell, Carol Stonham, Andrew Bush, Brian McKinstry, Heather Milne, David Price, Aziz Sheikh, Hilary Pinnock

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output


Asthma can be difficult to diagnose in primary care. Clinical decision support systems (CDSS) can assist clinicians when making diagnostic decisions, but the perspectives of intended users need to be incorporated into the software if the CDSS is to be clinically useful. Therefore, we aimed to understand health professional views on the value of an asthma diagnosis CDSS and the barriers and facilitators for use in UK primary care.


We recruited doctors and nurses working in UK primary care who had experience of assessing respiratory symptoms and diagnosing asthma. Qualitative interviews were used to explore clinicians’ experiences of making a diagnosis of asthma and understand views on a CDSS to support asthma diagnosis. Interviews were audio-recorded, transcribed verbatim and analyzed thematically.


16 clinicians (nine doctors, seven nurses) including 13 participants with over 10 years experience, contributed interviews. Participants saw the potential for a CDSS to support asthma diagnosis in primary care by structuring consultations, identifying relevant information from health records, and having visuals to communicate findings to patients. Being evidence based, regularly updated, integrated with software, quick and easy to use were considered important for a CDSS to be successfully implemented. Experienced clinicians were unsure a CDSS would help their routine practice, particularly in straightforward diagnostic scenarios, but thought a CDSS would be useful for trainees or less experienced colleagues.


To be adopted into clinical practice, clinicians were clear that a CDSS must be validated, integrated with existing software, and quick and easy to use.
Original languageEnglish
JournalJournal of Asthma
Early online date7 Nov 2023
Publication statusE-pub ahead of print - 7 Nov 2023

Keywords / Materials (for Non-textual outputs)

  • Asthma
  • Diagnosis
  • Primary Care
  • Clinical Decision Support Systems
  • Qualitative Study


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