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Bridging the literacy gap for surgical consents: an AI-human expert collaborative approach
npj Digital Medicine ( IF 15.2 ) Pub Date : 2024-03-08 , DOI: 10.1038/s41746-024-01039-2
Rohaid Ali , Ian D. Connolly , Oliver Y. Tang , Fatima N. Mirza , Benjamin Johnston , Hael F. Abdulrazeq , Paul F. Galamaga , Tiffany J. Libby , Neel R. Sodha , Michael W. Groff , Ziya L. Gokaslan , Albert E. Telfeian , John H. Shin , Wael F. Asaad , James Zou , Curtis E. Doberstein

Despite the importance of informed consent in healthcare, the readability and specificity of consent forms often impede patients’ comprehension. This study investigates the use of GPT-4 to simplify surgical consent forms and introduces an AI-human expert collaborative approach to validate content appropriateness. Consent forms from multiple institutions were assessed for readability and simplified using GPT-4, with pre- and post-simplification readability metrics compared using nonparametric tests. Independent reviews by medical authors and a malpractice defense attorney were conducted. Finally, GPT-4’s potential for generating de novo procedure-specific consent forms was assessed, with forms evaluated using a validated 8-item rubric and expert subspecialty surgeon review. Analysis of 15 academic medical centers’ consent forms revealed significant reductions in average reading time, word rarity, and passive sentence frequency (all P < 0.05) following GPT-4-faciliated simplification. Readability improved from an average college freshman to an 8th-grade level (P = 0.004), matching the average American’s reading level. Medical and legal sufficiency consistency was confirmed. GPT-4 generated procedure-specific consent forms for five varied surgical procedures at an average 6th-grade reading level. These forms received perfect scores on a standardized consent form rubric and withstood scrutiny upon expert subspeciality surgeon review. This study demonstrates the first AI-human expert collaboration to enhance surgical consent forms, significantly improving readability without sacrificing clinical detail. Our framework could be extended to other patient communication materials, emphasizing clear communication and mitigating disparities related to health literacy barriers.



中文翻译:

缩小手术同意的文化差距:人工智能与人类专家的协作方法

尽管知情同意在医疗保健中很重要,但同意书的可读性和特异性常常妨碍患者的理解。本研究调查了使用 GPT-4 来简化手术同意书,并引入了人工智能-人类专家协作方法来验证内容的适当性。使用 GPT-4 评估多个机构的同意书的可读性并进行简化,并使用非参数测试对简化前和简化后的可读性指标进行比较。医学作者和医疗事故辩护律师进行了独立审查。最后,评估了 GPT-4 生成从头手术特定同意书的潜力,并使用经过验证的 8 项标准和专家亚专科外科医生审查来评估表格。 对 15 个学术医疗中心同意书的分析显示,经过 GPT-4 简化后,平均阅读时间、单词稀有度和被动句频率显着减少(所有P < 0.05)。可读性从大学新生的平均水平提高到八年级的水平(P  = 0.004),与美国人的平均阅读水平相当。医疗和法律充分性的一致性得到了确认。GPT-4 以六年级平均阅读水平为五种不同的外科手术生成了特定于手术的同意书。这些表格在标准化同意书评分标准上获得了满分,并经受住了专家亚专科外科医生审查的严格审查。这项研究展示了人工智能与人类专家的首次合作,以增强手术同意书的质量,在不牺牲临床细节的情况下显着提高可读性。我们的框架可以扩展到其他患者沟通材料,强调清晰的沟通并减少与健康素养障碍相关的差异。

更新日期:2024-03-08
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