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Stakeholder perspectives on contributors to delayed and inaccurate diagnosis of heart disease: a UK-based qualitative study.

Abdullayev, K.; Gorvett, O.; Sochiera, A.; Laidlaw, L.; Chico, T.; Manktelow, M.; Buckley, O.; Condell, J.; Van Arkel, R.; Diaz, V.; Matcham, F.

2023-09-29 cardiovascular medicine
10.1101/2023.09.28.23295847 medRxiv
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ObjectiveThe aim of this study is to understand stakeholder experiences of cardiovascular disease (CVD) diagnosis to support the development of technological solutions that meet current needs. Specifically, we aimed to identify challenges faced by stakeholders in the process of diagnosis of CVD; to identify discrepancies between patient and clinician experiences of CVD diagnosis, and to make recommendations for the requirements of future health technology solutions intended to improve CVD diagnosis. DesignThe qualitative data was obtained using semi-structured focus groups and 1-1 interviews. ParticipantsUK-based individuals (N = 32) with lived experience of diagnosis of CVD (n = 23) and clinicians with experience in diagnosing CVD (n = 9). ResultsThematic analysis of focus groups and interview transcripts produced four key themes related to challenges contributing to delayed or inaccurate diagnosis of CVD: Symptom Interpretation, Patient Characteristics, Patient-Clinician Interactions, and Systemic Challenges. Sub-themes from each theme are discussed in depth. ConclusionsChallenges related to time and communication were greatest for both stakeholder groups, however there were differences in other areas, for example patient experiences highlighted difficulties with the psychological aspects of diagnosis and interpreting ambiguous symptoms, while clinicians emphasised the role of individual patient differences and the lack of rapport in contributing to delays or inaccurate diagnosis. Key takeaways from this qualitative study were summarised into a table of considerations to highlight key areas that require prioritisation for future research aiming to improve the efficiency and accuracy of CVD diagnosis using digital technologies.

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