The Medical Education Case Generator Workflow is a standardized process for generating structured AI-enabled virtual patient profiles for graduate medical education simulations. The workflow outlines step-by-step procedures for creating curriculum-aligned virtual patient cases, obtaining user approval of generated profiles, and exporting simulation-ready patient descriptions for deployment in conversational simulation platforms (e.g., Character AI).
This workflow is designed to support internal medicine, pediatrics, and primary care training programs seeking scalable approaches to simulation-based education, particularly for mental and behavioral health learning scenarios. It emphasizes competency-aligned case design, progressive disclosure of patient information, role-locked patient behaviors, and structured clinical reasoning opportunities that facilitate deliberate practice in simulated encounters.
The workflow document describes the operational process used by the Medical Education Case Generator GPT and functions as a case-development support tool. Teaching, facilitation, assessment, and learner feedback remain the responsibility of human educators. The workflow is intended for educational, academic, and faculty development use.
This version contains the workflow documentation only and does not include the full simulation toolkit or case library. Adaptation for non-commercial educational purposes is permitted with appropriate attribution to the original author.
Note: ChatGPT 5.2 and Character AI 1.10.0 were used to create this resource.
Last updated February 2026
Author
Adriana Quiroga Velasquez, MD, Clinical Research Coordinator, Tulane University School of Medicine