基于NLP构建病历后结构化专病数据库探索与实践
Exploration and Practice of Constructing a Structured Specialized Disease Database Based on NLP for Medical Records
张亚男 1董亮 1何萍2
作者信息
- 1. 上海中医药大学附属龙华医院 上海 200032
- 2. 上海申康医院发展中心 上海 200041
- 折叠
摘要
目的/意义建设基于结构化电子病历的专病数据库,提高专病数据库规范性和可用性,提高临床科研工作效率.方法/过程采用模板化输入、自然语言处理等技术,将非结构化电子病历转化为结构化电子病历,基于结构化电子病历构建专病数据库.结果/结论龙华医院基于结构化电子病历建设的银屑病专病数据库分中心,为临床科研人员提供结构化科研数据源,辅助提升分析效率;同时有效支撑上海申康"基于多中心的银屑病专病大数据临床科研随访一体化平台"建设,有助于专病数据库高质量、规模化发展.
Abstract
Purpose/Significance To construct a specialized disease database based on structured electronic medical records(EMR),and to improve the standardization and usability of the specialized disease database and improve the efficiency of clinical scien-tific research.Method/Process By using templated input,natural language processing(NLP)and other technologies,unstructured EMR are converted into structured EMR,and a specialized disease database is constructed based on structured EMR.Result/Conclu-sion The psoriasis specialized disease database sub center built by Longhua Hospital based on structured EMR provides clinical research-ers with a structured scientific research data source,assists researchers in improving analysis efficiency,and effectively supports the con-struction of Shanghai Shenkang's"multi center psoriasis specialized disease big data clinical research follow-up integrated platform",which is conducive to the high-quality and large-scale development of specialized disease databases.
关键词
自然语言处理/结构化电子病历/专病数据库Key words
natural language processing(NLP)/structured electronic medical records(EMR)/specialized disease database引用本文复制引用
基金项目
上海申康医院发展中心管理研究项目(2023SKMR-22)
出版年
2024
NETL
NSTL
万方数据