Seeing and believing: behavioural insights from implementing an artificial intelligence-enabled stethoscope in primary care
Authors: Kelshiker M A , Bachtiger P , Mansell J , Chhatwal K , Almonte M , Alrumayh A , Zaman J , Schmidt A , Plymen C M , Kramer D B , Peters N S 
Published: October 2024

Abstract

Background
• Early detection and treatment of cardiovascular disease (CVD) improves survival, quality of life and health economic outcomes (1)
• Despite evidence of effectiveness, health systems fail to implement technologies for early detection of CVD sustainably, limiting their public health impact (2). This challenge may limit the full potential of artificial intelligence (AI) in healthcare (3).
• An AI-enabled stethoscope can detect reduced left ventricular ejection fraction (LVEF), atrial fibrillation (AF) and structural cardiac murmurs during fifteen seconds of conventional cardiac examination (4)
• The determinants of uptake, sustained use and clinical impact of implementing the AI-stethoscope in primary care are unknown.

Purpose
• To implement the AI-stethoscope in a UK primary care system
• To measure rates of utilisation and their association with potential disease detection
• To characterise the adoption patterns of an AI technology in primary care

Methods
• TRICORDER is a cluster randomised controlled trial and implementation study.
• Clinicians in the intervention arm receive in-person training in use of the AI-stethoscope and are remunerated for this training time.
• Clinicians using the AI-stethoscope in routine care are supported by a clinical guideline and data privacy approvals from the regional health service executive board.
• GP practices are not remunerated for using the AI-stethoscope
• Anonymised utilisation and AI disease detection rates were extracted from the manufacturer’s cloud database from 31st October 2023 to 25th February 2024. We performed linear regression to characterise use over time.

Results
• 59 practices were randomised and onboarded to the intervention arm between 31st October and 3rd December 2023, all using the stethoscope at least once, for a total of 1,555 unique patient examinations (3,253 total recordings), over a median of 90 days.
• The mean (±SD) number of recordings per practice per week was 5.45 (±5.68).
• There were 32 practices with utilisation data for at least 12 weeks. There was a weakly positive utilisation trend (r = 0.042; P= &gt;0.05, Figure 1A), with no significant difference in rates of utilisation at 4, 8 and 12 weeks (Figure 1B).
• There were 159 (4.88%), 89 (2.74%) and 102 (3.13%) abnormal AI flags for reduced LVEF, AF and structural murmurs, respectively.
• We characterised three groups by patterns of use (Table 1). There were no significant differences between mean rates of abnormal AI findings between groups (ANOVA p = 0.43).

Conclusions
• Implementation of an AI-stethoscope in primary care is feasible and was associated with stable utilisation.
• The proportion of abnormal AI findings are consistent with modelled detection gap of the target conditions in the UK, and would not consequentially overwhelm downstream health services.
•The proportion of abnormal AI findings did not significantly differ between low and high-utilisation groups.Table 1Figure 1