Objective:

To explore the role of AI-enabled devices in nurse- and allied health professional-led opportunistic screening for atrial fibrillation (AF) in community and primary care settings.

Approach:

• Screening Strategies: Distinguishes between systematic and opportunistic screening, focusing on the latter which utilizes existing healthcare interactions.
• AI-Enabled Devices: Discusses the use of AI-enabled devices like single-lead ECG and photoplethysmography (PPG) as alternatives to traditional physician-interpreted 12-lead ECG.
• Nurse and AHP Involvement: Advocates for empowering nurses and allied health professionals to conduct opportunistic AF screening, enhancing early detection and intervention.

Key Findings:

• AI-enabled devices show good diagnostic accuracy compared to traditional ECG.
• Nurse-led opportunistic screening is cost-effective and facilitates earlier anticoagulant initiation.
• Barriers to widespread adoption include false positives, lack of standardized training, and liability concerns.

Interpretation:

The shift to nurse- and AHP-led opportunistic screening using AI technology represents a proactive approach to AF detection, potentially reducing stroke risks in the community.

Limitations:

• False positive results may lead to unnecessary anxiety and further testing.
• Lack of standardized training for nurses and AHPs in using AI devices.
• Liability concerns regarding AI interpretation may hinder implementation.

Conclusion:

Future strategies should focus on workforce training, data governance, and integrating AI findings into clinical pathways for effective AF management.

Sources:

• European Society of Cardiology Guidelines