在编辑中迷失:在合成记录的时代,恢复临床叙述
Shaheen E Lakhan1,2,3,4,5
1Bioscience, Boricua Bio, San Juan, PRI.
Cureus
|February 9, 2026
概括
由人工智能 (AI) 驱动的合成临床记录有可能侵蚀临床推理和患者叙述. 需要一种新的"全道"方法,临床医生产生核心意图,人工智能为不同的受众量身定制,确保安全.
科学领域:
- 医疗信息学 医疗信息学
- 临床文档 临床文档
- 医疗保健中的人工智能
背景情况:
- 环境人工智能 (AI) 和大型语言模型 (LLM) 的临床接触自动化正在创建一个"合成记录".
- 这种转变可能会削弱明确的临床推理和人类临床叙述,影响患者安全,护理过渡和问责制.
- 目前的临床说明与"CGI大片"相似,优先考虑数据而不是连贯的临床推理,以满足多个受众.
研究的目的:
- 为了检查AI生成记录时代的临床笔记的危机.
- 为了确定多样化的受众需要骨折的临床推理.
- 倡导一个"全道"临床生产范式.
主要方法:
- 通过电影镜头对"合成记录"的分析.
- 确定10个不同的临床注释受众.
- 在临床文档中引入叙述失败的分类学.
- 关于"全道"临床生产模式的建议.
主要成果:
- 现代的临床注释是分散的,试图同时为多个利益相关者 (患者,审计员,算法) 服务.
- 人工智能生成的散文可以流利,但缺乏临床意图,诊断推理可能不完整.
- 试图满足相互矛盾的要求导致连贯的临床推理和叙事完整性的损失.
结论:
- 建议转向"全道"临床生产,其中临床医生创建一个核心叙事合成.
- 人工智能应该将这一核心意图转化为利益相关者特定的格式.
- 恢复临床说明作为一个有说服力的论点,而不是交易收据,对于数字时代的患者安全至关重要.
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