研究医生如何修改AI生成病历中的模糊用语，发现修改后反而更不确定。
Examine Clinicians' Modification of Hedging Language in Ambient AI Documentation: A Comparative Study of AI Drafts and Final Notes
- 对比分析医生修改前后的病历片段，观察模糊表达变化
- 修改后模糊用语增多，整体倾向更不确定，比例达62,811处
- 不同AI厂商和科室差异显著，提示需个性化优化
环境化AI病历系统生成临床记录初稿，医生常在签署前进行修订，但这些修改如何影响模糊语言（hedging language）尚不明确。本研究对62,811个成对的初稿与终稿片段进行分析，考察：（1）修改是否改变模糊语言频率；（2）修改是否系统性地使语言更确定或更不确定；（3）这种变化是否因AI供应商和临床专科而异。结果发现，相较于从已有模糊文本中删除，医生更倾向于在原本无模糊表达的文本中引入模糊用语。修改后的文本中模糊表达数量高于修改前。方向性分析显示，在替换类编辑中，整体存在显著的不确定性增强趋势。不同供应商及临床专科间的模糊表达频率、修改前后变化幅度及方向均存在显著差异。
原文摘要 · Abstract (English)
Ambient AI documentation systems generate clinical note drafts that clinicians frequently revise before signing off into electronic health records, yet how these edits alter hedging language remains unclear. We conducted paired analysis of clinician-edited portions of ambient AI drafts and final notes to examine (1) whether these edits change the prevalence of hedging language, (2) whether these edits exhibit a systematic shift toward greater certainty or uncertainty, and (3) whether these changes in hedging prevalence and directionality differ by ambient AI vendors and clinical specialties. Among 62,811 paired note sections, hedging terms were more often introduced into previously non-hedged text than removed from previously hedged text, and post-edit text contained more hedging mentions than pre-edit text. Directionality analyses showed a significant overall tendency toward greater uncertainty in hedging-related replacement edits. Vendor and specialty analyses revealed substantial heterogeneity in hedging prevalence, pre-to-post changes in hedging mentions, and directionality.
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