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Leveraging Large Language Models to Improve the Readability of German Online Medical Texts: Evaluation Study
Amela Miftaroski1, Richard Zowalla1,2, Martin Wiesner1,3
1Faculty of Informatics, Heilbronn University, Max-Planck-Str. 39, Heilbronn, 74081, Germany, 49 7131 504 ext 633.
Background:
Patient education materials (PEMs) found online are often written at a complexity level too high for the average reader, which can hinder understanding and informed decision-making. Large language models (LLMs) may offer a solution by simplifying complex medical texts. To date, little is known about how well LLMs can handle simplification tasks for German-language PEMs.
Objective:
The study aims to investigate whether LLMs can increase the readability of German online medical texts to a recommended level.
Methods:
A sample of 60 German texts originating from online medical resources was compiled. To improve the readability of these texts, four LLMs were selected and used for text simplification: ChatGPT-3.5, ChatGPT-4o, Microsoft Copilot, and Le Chat. Next, readability scores (Flesch reading ease [FRE] and Wiener Sachtextformel [4th Vienna Formula; WSTF]) of the original texts were computed and compared to the rephrased LLM versions. A Student t test for paired samples was used to test the reduction of readability scores, ideally to or lower than the eighth grade level.
Results:
Most of the original texts were rated as difficult to quite difficult (average WSTF 11.24, SD 1.29; FRE 35.92, SD 7.64). On average, the LLMs achieved the following average scores: ChatGPT-3.5 (WSTF 9.96, SD 1.52; FRE 45.04, SD 8.62), ChatGPT-4o (WSTF 10.6, SD 1.37; FRE 39.23, SD 7.45), Microsoft Copilot (WSTF 8.99, SD 1.10; FRE 49.0, SD 6.51), and Le Chat (WSTF 11.71, SD 1.47; FRE 33.72, SD 8.58). ChatGPT-3.5, ChatGPT-40, and Microsoft Copilot showed a statistically significant improvement in readability. However, the t tests yielded no statistically significant results for the reduction of scores lower than the eighth grade level.
Conclusions:
LLMs can improve the readability of PEMs in German. This moderate improvement can support patients reading PEMs online. LLMs demonstrated their potential to make complex online medical text more accessible to a broader audience by increasing readability. This is the first study to evaluate this for German online medical texts.
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