Stephan Daniel, Bertsch Annika S, Schumacher Sophia, Puladi Behrus, Burwinkel Matthias, Al-Nawas Bilal, Kämmerer Peer W, Thiem Daniel Ge
Department of Oral and Maxillofacial Surgery, Facial Plastic Surgery, University Medical Centre, Johannes Gutenberg-University Mainz, Mainz, Germany.
Department of Oral and Maxillofacial Surgery, University Hospital Rheinisch-Westfälische Technische Hochschule Aachen, Aachen, Germany.
J Med Internet Res. 2025 Jun 9;27:e73337. doi: 10.2196/73337.
Medical reports, particularly radiology findings, are often written for professional communication, making them difficult for patients to understand. This communication barrier can reduce patient engagement and lead to misinterpretation. Artificial intelligence (AI), especially large language models such as ChatGPT, offers new opportunities for simplifying medical documentation to improve patient comprehension.
We aimed to evaluate whether AI-generated radiology reports simplified by ChatGPT improve patient understanding, readability, and communication quality compared to original AI-generated reports.
In total, 3 versions of radiology reports were created using ChatGPT: an original AI-generated version (text 1), a patient-friendly, simplified version (text 2), and a further simplified and accessibility-optimized version (text 3). A total of 300 patients (n=100, 33.3% per group), excluding patients with medical education, were randomly assigned to review one text version and complete a standardized questionnaire. Readability was assessed using the Flesch Reading Ease (FRE) score and LIX indices.
Both simplified texts showed significantly higher readability scores (text 1: FRE score=51.1; text 2: FRE score=55.0; and text 3: FRE score=56.4; P<.001) and lower LIX scores, indicating enhanced clarity. Text 3 had the shortest sentences, had the fewest long words, and scored best on all patient-rated dimensions. Questionnaire results revealed significantly higher ratings for texts 2 and 3 across clarity (P<.001), tone (P<.001), structure, and patient engagement. For example, patients rated the ability to understand findings without help highest for text 3 (mean 1.5, SD 0.7) and lowest for text 1 (mean 3.1, SD 1.4). Both simplified texts significantly improved patients' ability to prepare for clinical conversations and promoted shared decision-making.
AI-generated simplification of radiology reports significantly enhances patient comprehension and engagement. These findings highlight the potential of ChatGPT as a tool to improve patient-centered communication. While promising, future research should focus on ensuring clinical accuracy and exploring applications across diverse patient populations to support equitable and effective integration of AI in health care communication.
医学报告，尤其是放射学检查结果，通常是用于专业交流，患者难以理解。这种沟通障碍会降低患者参与度并导致误解。人工智能（AI），尤其是像ChatGPT这样的大语言模型，为简化医学文档以提高患者理解度提供了新机会。
我们旨在评估与原始的由人工智能生成的报告相比，由ChatGPT简化生成的放射学报告是否能提高患者的理解度、可读性和沟通质量。
使用ChatGPT总共创建了3个版本的放射学报告：原始的由人工智能生成的版本（文本1）、患者友好的简化版本（文本2）以及进一步简化且优化了可及性的版本（文本3）。总共300名患者（每组n = 100，占33.3%），排除接受过医学教育的患者，被随机分配阅读一个文本版本并完成一份标准化问卷。使用弗莱什易读性（FRE）得分和LIX指数评估可读性。
两个简化后的文本均显示出显著更高的可读性得分（文本1：FRE得分 = 51.1；文本2：FRE得分 = 55.0；文本3：FRE得分 = 56.4；P <.001）和更低的LIX得分，表明清晰度提高。文本3的句子最短，长单词最少，在所有患者评分维度上得分最高。问卷结果显示，文本2和文本3在清晰度（P <.001）、语气（P <.001）、结构和患者参与度方面的评分显著更高。例如，患者对文本3在无需帮助就能理解检查结果的能力方面评分最高（平均1.5，标准差0.7），对文本1评分最低（平均3.1，标准差1.4）。两个简化后的文本均显著提高了患者为临床对话做准备的能力，并促进了共同决策。
人工智能生成的放射学报告简化显著提高了患者的理解度和参与度。这些发现凸显了ChatGPT作为一种改善以患者为中心的沟通工具的潜力。虽然前景广阔，但未来的研究应专注于确保临床准确性，并探索在不同患者群体中的应用，以支持人工智能在医疗保健沟通中的公平和有效整合。
