十多年来,来自电子健康记录的精神病学临床笔记的词汇稳定性
Lasse Hansen1,2,3, Kenneth Enevoldsen2,3, Martin Bernstorff1,2
1Department of Affective Disorders, Aarhus University Hospital - Psychiatry, Aarhus, Denmark.
Acta neuropsychiatrica
|August 24, 2023
概括
精神病学服务中的临床笔记显示了随着时间的推移的词汇和语法稳定性. 这种稳定性支持在临床预测模型中可靠使用自然语言处理 (NLP).
科学领域:
- 临床信息学 临床信息学
- 自然语言处理自然语言处理.
- 精神病学服务 精神病学服务
背景情况:
- 电子健康记录包含有价值的临床笔记.
- 随着时间的推移,临床实践和系统的变化可能会改变笔记内容.
- 临床笔记的稳定性对于NLP预测模型至关重要,但很少被研究.
研究的目的:
- 评估临床笔记的时间稳定性.
- 评估时间对笔记的影响与NLP相关的特征.
主要方法:
- 分析了来自精神病学服务的14811551份临床笔记 (2011-2021年).
- 量化句子长度,可读性,语法复杂性和临床内容.
- 采用变化点检测模型来识别时间变化.
主要成果:
- 在临床笔记中发现了整体的词汇和语法稳定性.
- 在近3000个数据点中仅检测到17个变化点 (0.6%).
- 在COVID-19大流行期间观察到的轻微偏差,主要与笔记类型的停止有关.
结论:
- 精神病学服务中的临床记录显示了显著的时间稳定性.
- 这种稳定性有利于NLP在临床预测中的应用.
- 支持精神病学中NLP驱动的预测模型的长期可行性.
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