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Published on: July 11, 2025
Beyond readability: Advancing patient-centered evaluation of AI-generated clinical reports.
Michela Monaci1, Elena Viviani1, Federico Sottotetti2
1WHYpsy Lab, Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.
Patient Education and Counseling
|May 25, 2026
Summary
Large language models can simplify medical documents, but true patient-centered communication requires more than just readability. Evaluating AI-generated content must include comprehensibility, relevance, and patient empowerment for meaningful engagement in care.
Area of Science:
- Medical Informatics
- Artificial Intelligence in Healthcare
- Patient Communication
Background:
- Large language models (LLMs) show potential for improving clinical documentation and patient access to medical information.
- Recent work has explored LLM-generated patient-centered reports, such as GPT-4 for prostate cancer pathology.
- Readability is a key consideration for AI-generated clinical documents.
Purpose of the Study:
- To argue that readability alone is insufficient for genuinely patient-centered communication.
- To propose broader multidimensional criteria for evaluating AI-generated clinical documents.
- To emphasize the importance of patient and caregiver involvement in AI tool development.
Main Methods:
- Review of recent evidence on various patient-facing medical documents (e.g., after-visit summaries, discharge summaries, open notes).
- Analysis of existing literature on AI in healthcare and patient communication.
- Conceptual framework development for evaluating AI-generated clinical communication.
Main Results:
- Readability is a necessary but not sufficient criterion for patient-centered AI-generated clinical documents.
- Broader evaluation criteria are needed, including comprehensibility, relevance, usability, emotional impact, and empowerment potential.
- Direct patient and caregiver involvement is crucial for designing and evaluating these tools.
Conclusions:
- AI-generated clinical documents must move beyond mere simplification of medical terminology.
- Effective AI tools should support patients in understanding health information and actively participating in their care.
- Multidimensional evaluation and co-design with patients are essential for truly patient-centered AI communication.
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