Conversational agents (CAs) have emerged as powerful tools for human-computer interaction, of ering natural language interfaces and personalized assistance, particularly in healthcare. Thedevelopment of CAs leveraging knowledge engineering (KE) techniques and LLMs necessitatestheconsideration of specific design principles (DPs) and interactive patterns to ensure their ef ectivenessand user satisfaction. This research focuses on a comprehensive analysis of the DPs andpatternscrucial for developing CA artifacts using KE techniques. To address the gap, author incorporateddesign science research methodology (DSRM) principles tailored to the modelling workshopmethodto capture domain knowledge and practitioner expertise in a new health information systemclass. Theresearch explores DPs based on meta-requirements suitable for interaction patterns andKE-basedCAs, including ontology-driven approaches. The research proposed systematic pathways, andbyapplying these DPs and patterns, developers can develop CAs exploiting LLMs to understandcomplexuser queries, provide accurate responses, and adapt to dynamic contexts.