Uncertainty and Risk at the Point of Care: Implications of Patient-Generated ECGs and Algorithmic Interpretations for Clinical Decision Making

Wearables enable users to generate electrocardiogram (ECG) data and receive algorithmic rhythm interpretations. While cardiologists increasingly use this data, little is known about how point-of-care clinicians perceive and anticipate using it. These clinicians are the main point of contact for many patients and determine access to further investigations and specialists. We conducted vignette-based interviews with 33 primary and emergency care clinicians to explore how they make sense of patient-generated ECG data and which factors shape anticipated use in decision making. We found that patient-generated data introduces diagnostic uncertainty, shaped by: legitimacy concerns, interpretation challenges, the influence of the wider clinical context on trust and confidence, and the balancing of patient risk against professional risk. This duality of risk often overrode earlier considerations, determining how clinicians responded to patient-generated data. We discuss design opportunities for uncertainty and risk-aware technology that can support the adoption of patient-generated data in everyday clinical practice.