医生和护士对消化系统疾病的住院患者的进展记录之间的信息异质性
Yukinori Mashima1,2, Masatoshi Tanigawa3, Hideto Yokoi3,4
1Clinical Research Support Center, Kagawa University Hospital, 1750-1 Ikenobe, Miki-cho, Kita-gun, Kagawa, 761-0793, Japan. mashima-yukinori@umin.ac.jp.
Scientific reports
|April 1, 2024
概括
与医生相比,护士从患者的进展记录中提取更多的症状 (R码). 然而,医生更经常记录消化系统症状和疾病名称,反映他们的专业. 这突显了医疗记录中的信息异质性.
科学领域:
- 医疗信息学 医疗信息学
- 临床文档分析 临床文档分析
- 在医疗保健中的自然语言处理.
背景情况:
- 医生和护士的进度记录包含重要患者信息,但表现出异质性.
- 了解这种异质性对于开发医疗人工智能 (AI) 应用至关重要.
- 以前的研究没有全面分析医生和护士笔记之间的信息内容差异.
研究的目的:
- 为了研究症状和疾病的差异,从医生与护士的进展笔记中提取.
- 根据作者医疗保健专业人员,量化临床文档中的异质性.
- 为未来医疗人工智能开发提供对数据特征的见解.
主要方法:
- 分析了来自83名住院患者的806天的进展记录.
- 使用MedNER-J自然语言处理软件提取国际疾病分类 (ICD) 第18章 (R码) 的症状.
- 计算了R码提取率,并将它们与医生和护士的笔记进行了比较,包括特定的子类别和疾病章节.
主要成果:
- 与医生 (68.5%) 相比,护士的整体R码提取率 (75.2%) 显著更高.
- 医生更频繁地提取消化系统症状 (R10-R19:44.2%对37.5%) 和疾病名称 (ICD第11章:68.4%对30.9%).
- 这些差异反映了医生和护士的不同记录模式和专业.
结论:
- 在医生和护士进度笔记中捕获的信息中存在显著的异质性.
- 护士能够捕捉到更广泛的症状,而医生则更多地关注特定的疾病及其专业.
- 认识到这种信息异质性是推动医疗人工智能发展和改善临床数据利用的基本步骤.
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