Patient Perspectives Towards Artificial Intelligence in Heart Failure Care

Area of Science:

• Cardiology
• Medical Informatics
• Artificial Intelligence in Healthcare

Background:

• Artificial intelligence (AI) tools are emerging for chronic disease management, including heart failure (HF).
• Limited understanding exists regarding HF patient perspectives on AI integration into their care.
• This study addresses the need to explore patient views for patient-centered AI adoption in HF.

Purpose of the Study:

• To investigate heart failure patients' perceptions of integrating AI into their care.
• To guide the patient-centered adoption of AI in heart failure management.
• To assess patient attitudes towards AI in diagnosis and treatment decisions.

Main Methods:

• A cross-sectional survey was administered to 110 patients with heart failure with reduced ejection fraction.
• Questionnaires assessed satisfaction with current care, trust in cardiologists, and attitudes toward AI involvement.
• Data were analyzed using logistic regression, examining associations with demographics, smartphone ownership, and symptom burden.

Main Results:

• Patient attitudes towards AI in HF care were mixed; only 38.1% supported AI in treatment decisions with physician input.
• Support significantly decreased when AI acted independently (18.2%) or managed remote adjustments (21.8%).
• A strong preference for cardiologist diagnoses (80.9%) and treatment plans (84.6%) was observed, with 97.3% trusting cardiologists over AI in disagreements. Smartphone ownership correlated with greater acceptance of remote AI adjustments.

Conclusions:

• Heart failure patients express high satisfaction with current care and strong trust in cardiologists, showing more caution towards AI than general populations.
• Smartphone ownership, not demographics or prior AI experience, predicted openness to AI-driven remote adjustments.
• Equitable AI adoption in HF care hinges on maintaining clinician oversight and developing accessible AI tools.