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分析中文和英文临床文本之间的差异:两种语言出院小结的跨机构比较。

Analyzing differences between chinese and english clinical text: a cross-institution comparison of discharge summaries in two languages.

作者信息

Wu Yonghui, Lei Jianbo, Wei Wei-Qi, Tang Buzhou, Denny Joshua C, Rosenbloom S Trent, Miller Randolph A, Giuse Dario A, Zheng Kai, Xu Hua

机构信息

School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TN, USA.

出版信息

Stud Health Technol Inform. 2013;192:662-6.

Abstract

Worldwide adoption of Electronic Medical Records (EMRs) databases in health care have generated an unprecedented amount of clinical data available electronically. There has been an increasing trend in US and western institutions towards collaborating with China on medical research using EMR data. However, few studies have investigated characteristics of EMR data in China and their differences with the data in US hospitals. As an initial step towards differentiating EMR data in Chinese and US systems, this study attempts to understand system and cultural differences that may exist between Chinese and English clinical documents. We collected inpatient discharge summaries from one Chinese and from three US institutions and manually analyzed three major clinical components in text: medical problems, tests, and treatments. We reported comparison results at the document level and section level and discussed potential reasons for observed differences. Documenting and understanding differences in clinical reports from the US and China EMRs are important for cross-country collaborations. Our study also provided valuable insights for developing natural language processing tools for Chinese clinical text.

摘要

全球范围内医疗保健领域对电子病历(EMR)数据库的采用产生了前所未有的大量可电子获取的临床数据。美国和西方机构与中国合作开展使用电子病历数据的医学研究的趋势日益增强。然而,很少有研究调查中国电子病历数据的特征及其与美国医院数据的差异。作为区分中美系统中电子病历数据的第一步,本研究试图了解中英文临床文档之间可能存在的系统和文化差异。我们从一家中国机构和三家美国机构收集了住院出院小结,并手动分析了文本中的三个主要临床组成部分:医疗问题、检查和治疗。我们报告了文档层面和部分层面的比较结果,并讨论了观察到的差异的潜在原因。记录和理解中美电子病历临床报告中的差异对于跨国合作很重要。我们的研究还为开发用于中文临床文本的自然语言处理工具提供了有价值的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cafa/4957806/0364ac77ef8b/nihms803375f1.jpg

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