Contrasting Attitudes Towards Current and Future AI Applications for Computerised Interpretation of ECG: A Clinical Stakeholder Interview Study
Journal:
arXiv
Published Date:
Oct 22, 2024
Abstract
Objectives: To investigate clinicians' attitudes towards current automated
interpretation of ECG and novel AI technologies and their perception of
computer-assisted interpretation. Materials and Methods: We conducted a series
of interviews with clinicians in the UK. Our study: (i) explores the potential
for AI, specifically future 'human-like' computing approaches, to facilitate
ECG interpretation and support clinical decision making, and (ii) elicits their
opinions about the importance of explainability and trustworthiness of AI
algorithms. Results: We performed inductive thematic analysis on interview
transcriptions from 23 clinicians and identified the following themes: (i) a
lack of trust in current systems, (ii) positive attitudes towards future AI
applications and requirements for these, (iii) the relationship between the
accuracy and explainability of algorithms, and (iv) opinions on education,
possible deskilling, and the impact of AI on clinical competencies. Discussion:
Clinicians do not trust current computerised methods, but welcome future 'AI'
technologies. Where clinicians trust future AI interpretation to be accurate,
they are less concerned that it is explainable. They also preferred ECG
interpretation that demonstrated the results of the algorithm visually. Whilst
clinicians do not fear job losses, they are concerned about deskilling and the
need to educate the workforce to use AI responsibly. Conclusion: Clinicians are
positive about the future application of AI in clinical decision-making.
Accuracy is a key factor of uptake and visualisations are preferred over
current computerised methods. This is viewed as a potential means of training
and upskilling, in contrast to the deskilling that automation might be
perceived to bring.
