Alex Ralevski

Medical providers often receive less than 15 minutes of instruction in how to interact with patients during emotionally charged end of life interactions. Continuing education for clinicians is critical to hone these skills but is difficult to scale traditional approaches that require professional patients and instructors. Here, we describe a custom chatbot that plays the role of patient and coach to provide a scaling learning experience. A critical challenge was how to mitigate the persistently cheerful and helpful tone which results from standard pretraining in the Patient Persona AI. We accomplished this by implementing a multi-agent architecture based upon a graphical model of the conversation. System prompts reflecting the patient’s cognitive state are dynamically updated as the conversation progresses. Future extensions of the work are intended to focus on additional custom model fine-tuning in the Mosaic AI platform to further improve the realism of the conversation.