A Healthcare-Specific Classification Schema for Conversational AI Agents

Recent advances in natural language processing (NLP) have accelerated the development of conversational agents (chatbots) in healthcare. Despite widespread adoption, a domain-specific classification schema tailored to the healthcare context is lacking. This paper proposes a novel classification framework for healthcare chatbots based on three dimensions: (1) the patient's journey within the healthcare system, (2) the chatbot’s functional purpose, and (3) the end-user role. Using morphological analysis and literature-based review, we categorize existing healthcare chatbot implementations within this schema. The framework reveals adoption trends, design implications, and gaps for future research, offering a structured basis for more effective and targeted chatbot development in healthcare.