使用一种新的自然语言处理实用程序,从自由文本医疗笔记中提取结构化数据
1Department of Surgery, Saint Louis University, St. Louis, USA.
Cureus
|December 16, 2025
概括
注意:与手动搜索相比,语言处理 (NoteLP) 软件显著加快了从电子病历 (EMR) 中提取临床数据的速度. 这种工具为研究数据检索提供了更好的灵敏度和可比的特异性.
科学领域:
- 医疗信息学 医疗信息学
- 自然语言处理 (NLP) 是一种自然语言处理.
- 临床数据管理 临床数据管理
背景情况:
- 电子医疗记录 (EMR) 包含大量的研究数据,但大部分是非结构化的自由文本.
- 手动提取这些非结构化数据耗时,并对研究构成障碍.
- 传统的基于规则的NLP和新的机器学习模型用于数据提取.
研究的目的:
- 开发和评估笔记语言处理 (NoteLP),这是一个用于从自由文本临床笔记中提取研究数据的软件实用程序.
- 将NoteLP的效率和准确性与EMR手动数据搜索方法进行比较.
- 评估NoteLP在获取研究项目的数据方面的表现.
主要方法:
- 开发了NoteLP软件,将自由文本笔记转换为结构化数据集.
- 在Epic EMR中进行手动数据搜索,以建立基于时间的参考标准.
- 设计了22个样本研究项目,将NoteLP的数据提取时间和准确性与手工方法和ICD-9代码进行比较.
主要成果:
- 注意LP显著减少了数据检索时间:在ICD-9比较中,每个患者的数据检索时间为37.5秒,在广泛的搜索中为16.6秒,而手动检索时间为63.4秒.
- 注意LP的平均灵敏度为0.98,明显高于ICD-9的0.65.
- 注意LP的平均特异性为0.94,相当于ICD-9的0.93.
结论:
- NoteLP是一个比手动搜索更有效的工具来从EMR中提取研究数据.
- 与手动编码和ICD-9代码相比,NoteLP提供了更高的灵敏度和同等的特异性.
- 基于规则的NLP实用程序,如NoteLP,对于有效访问非结构化医学数据进行研究是有价值的.
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