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Auditing Institutional Heterogeneity for Generative AI in Patient Education: A Large-Scale Study of 102 US Transplant Handbooks

● high · 2026-07-28generative-ai, health-education, equity, content-quality, equity-in-ai-education, adaptive-virtual-patient-psychotherapy-training, llm, ai-education

Li, Padman and Krishnan audit 102 US transplant-center patient handbooks that serve as grounding corpora for generative AI patient-education assistants. They show large institutional heterogeneity in the underlying education materials, undermining the premise that grounding a genAI assistant in local content yields consistent guidance: patients at different institutions can receive materially different AI-mediated answers to the same question. The study extends grounding-quality concerns familiar from Retrieval Augmented Tutoring Algorithm Kite into health education, and connects to AI-driven medical training work such as Medeasy AI Standardized Patients, Adaptive Virtual Patient Psychotherapy Training and Medgame LLM Medical Education Gamification. The equity implication (institution-dependent quality of AI-mediated education) parallels Equity In AI Education.

Connected Concepts

  • Equity In AI Education

    • Connected Articles

  • Retrieval Augmented Tutoring Algorithm Kite
  • Medeasy AI Standardized Patients
  • Adaptive Virtual Patient Psychotherapy Training
  • Medgame LLM Medical Education Gamification

    • Citation

    Yubo Li, Rema Padman, Ramayya Krishnan (2026). Auditing Institutional Heterogeneity for Generative AI in Patient Education: A Large-Scale Study of 102 US Transplant Handbooks. arXiv:2607.22606.