AI-Enabled Optimization of Heart Failure Patient Discharge Pathways: A Proposal for Implementation at the Hospital of Vallo Della Lucania, ASL Salerno

Abstract

Heart failure remains a leading cause of hospital readmission, especially in elderly populations with complex health needs. In this proposal, we outline a strategy for integrating artificial intelligence (AI) into the discharge process for heart failure patients at the Internal medicine ward of Vallo della Lucania hospital. The initiative combines predictive algorithms, natural language processing, and patient engagement tools to identify individuals at high risk of adverse outcomes, support clinicians in personalized discharge planning, and ensure coordination with territorial care services. By improving communication, automating followups, and enabling remote symptom tracking, the AI-supported workflow seeks to reduce preventable readmissions, optimize resource use, and foster continuity of care between hospital and home. The proposed model aligns with national health objectives and offers a scalable framework for digital transformation in internal medicine.