未见的见解:在眼科中对安全患者信息的AI驱动的探索
medRxiv : the preprint server for health sciences
|February 12, 2026
概括
安全的患者信息揭示了眼科中常见的行政和临床问题,根据患者人口统计学,主题存在显著差异. 分析可以提高护理公平性和效率.
科学领域:
- 眼科医生 眼科 眼科
- 医疗信息学 医疗信息学
- 医疗保健服务研究 医疗服务研究
背景情况:
- 安全消息平台越来越多地用于医疗保健中的患者与医疗服务提供者的沟通.
- 了解这些信息的内容对于优化临床工作流程和患者护理至关重要.
- 眼科患者的信息往往包含行政和临床查询.
研究的目的:
- 通过安全的眼科信息传递来描述通过安全眼科信息传递的临床和行政问题.
- 评估信息内容在各种患者社会人口统计学群体中如何不同.
主要方法:
- 一项横截面研究分析了未识别的,由患者发起的安全消息.
- 使用自然语言处理和大型语言模型辅助的主题分类.
- 消息内容根据患者的人口统计学 (年龄,性别,种族,种族,婚姻状况) 进行了分层.
主要成果:
- 近一半的消息涉及行政问题 (安排,补充,保险).
- 最主要的临床问题包括视力障碍,绿眼病,成像/瘤问题以及术后问题.
- 观察到显著的人口差异:非白人患者提出了更多的补充/保险/青光眼问题;白人患者报告了更多的手术问题. 老年患者讨论了青光眼/手术/瘤;女性患者报告了并发症/胀/感染.
结论:
- 安全的患者信息经常包含临床相关的信息,影响分拣和护理.
- 消息内容中的人口差异突出了寻求护理行为的差异.
- 系统分析支持更安全的分组,高效的工作流程和公平的眼科护理服务.
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