Evaluating Large Language Model Adherence to Targeted Fifth‐Grade Readability Standards in Patient Education on Chronic Conditions

Summary Large Language Models (LLMs) frequently generate patient education materials that exceed recommended reading levels. Prompting LLMs to produce PEMs at a 5th‐grade level consistently produced statistically lower readability scores than unprompted outputs. These findings suggest that simple prompt engineering can improve clarity and accessibility of LLM‐generated PEMs.