HEAL-AI: An AI-Powered Framework to Bridge Patient-Provider Communication Gaps in Healthcare

Abstract

Effective communication between patients and healthcare providers is essential for accurate diagnosis, treatment adherence, and overall patient satisfaction. However, communication gaps especially among elderly patients pose persistent challenges due to factors such as cognitive decline, limited health literacy, and language barriers. This paper introduces Healthcare Engagement and Accessibility through Language-AI (HEAL-AI), a prototype framework that leverages Natural Language Processing (NLP) and patient data analysis to bridge these gaps. HEAL-AI provides real-time interpretation, personalized health information delivery, and context-aware feedback mechanisms tailored to the communication needs of elderly patients. By analyzing historical patient interaction data and applying adaptive NLP models, the system enhances understanding, improves patient engagement, and supports shared decision-making. Preliminary evaluations of HEAL-AI in a simulated clinical setting demonstrate promising outcomes in improving clarity, reducing miscommunication, and increasing patient satisfaction. The proposed framework lays the groundwork for scalable, AI-assisted communication support tools in patient-centered healthcare delivery.

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