Suppr超能文献

“大数据”与电子健康记录

"Big data" and the electronic health record.

作者信息

Ross M K, Wei W, Ohno-Machado L

机构信息

Lucila Ohno-Machado, Division of Biomedical Informatics, 9500 Gilman Drive, MC 0505, La Jolla, California, 92037-0505, USA, Tel: +1 858 822 4931, E-mail:

出版信息

Yearb Med Inform. 2014 Aug 15;9(1):97-104. doi: 10.15265/IY-2014-0003.

Abstract

OBJECTIVES

Implementation of Electronic Health Record (EHR) systems continues to expand. The massive number of patient encounters results in high amounts of stored data. Transforming clinical data into knowledge to improve patient care has been the goal of biomedical informatics professionals for many decades, and this work is now increasingly recognized outside our field. In reviewing the literature for the past three years, we focus on "big data" in the context of EHR systems and we report on some examples of how secondary use of data has been put into practice.

METHODS

We searched PubMed database for articles from January 1, 2011 to November 1, 2013. We initiated the search with keywords related to "big data" and EHR. We identified relevant articles and additional keywords from the retrieved articles were added. Based on the new keywords, more articles were retrieved and we manually narrowed down the set utilizing predefined inclusion and exclusion criteria.

RESULTS

Our final review includes articles categorized into the themes of data mining (pharmacovigilance, phenotyping, natural language processing), data application and integration (clinical decision support, personal monitoring, social media), and privacy and security.

CONCLUSION

The increasing adoption of EHR systems worldwide makes it possible to capture large amounts of clinical data. There is an increasing number of articles addressing the theme of "big data", and the concepts associated with these articles vary. The next step is to transform healthcare big data into actionable knowledge.

摘要

目标

电子健康记录(EHR)系统的应用范围持续扩大。大量的患者诊疗记录产生了海量的存储数据。几十年来,将临床数据转化为知识以改善患者护理一直是生物医学信息学专业人员的目标,如今这项工作在我们领域之外也越来越受到认可。在回顾过去三年的文献时,我们聚焦于EHR系统背景下的“大数据”,并报告一些数据二次利用付诸实践的实例。

方法

我们在PubMed数据库中搜索2011年1月1日至2013年11月1日期间的文章。我们以与“大数据”和EHR相关的关键词启动搜索。我们识别出相关文章,并从检索到的文章中添加其他关键词。基于新的关键词,检索到更多文章,我们利用预定义的纳入和排除标准手动缩小范围。

结果

我们的最终综述包括分类为数据挖掘(药物警戒、表型分析、自然语言处理)、数据应用与整合(临床决策支持、个人监测、社交媒体)以及隐私与安全等主题的文章。

结论

全球范围内EHR系统的采用日益广泛,使得获取大量临床数据成为可能。涉及“大数据”主题的文章数量不断增加,且与这些文章相关的概念各不相同。下一步是将医疗大数据转化为可付诸行动的知识。

相似文献

1
"Big data" and the electronic health record.“大数据”与电子健康记录
Yearb Med Inform. 2014 Aug 15;9(1):97-104. doi: 10.15265/IY-2014-0003.
3
Concurrence of big data analytics and healthcare: A systematic review.大数据分析与医疗保健的并存:系统评价。
Int J Med Inform. 2018 Jun;114:57-65. doi: 10.1016/j.ijmedinf.2018.03.013. Epub 2018 Mar 26.
4
Mining the electronic health record for disease knowledge.从电子健康记录中挖掘疾病知识。
Methods Mol Biol. 2014;1159:269-86. doi: 10.1007/978-1-4939-0709-0_15.
9
Big Data Analytics in Medicine and Healthcare.医学与医疗保健中的大数据分析
J Integr Bioinform. 2018 May 10;15(3):20170030. doi: 10.1515/jib-2017-0030.

引用本文的文献

5
A Scoping Review of Artificial Intelligence for Precision Nutrition.人工智能在精准营养领域的范围综述。
Adv Nutr. 2025 Apr;16(4):100398. doi: 10.1016/j.advnut.2025.100398. Epub 2025 Feb 28.

本文引用的文献

4
Mining clinical text for signals of adverse drug-drug interactions.从临床文本中挖掘药物-药物不良相互作用信号。
J Am Med Inform Assoc. 2014 Mar-Apr;21(2):353-62. doi: 10.1136/amiajnl-2013-001612. Epub 2013 Oct 24.
7
Contrasting temporal trend discovery for large healthcare databases.大型医疗保健数据库的对比时间趋势发现。
Comput Methods Programs Biomed. 2014;113(1):251-7. doi: 10.1016/j.cmpb.2013.09.005. Epub 2013 Sep 16.
9
Protection of electronic health records (EHRs) in cloud.云端电子健康记录(EHRs)的保护
Annu Int Conf IEEE Eng Med Biol Soc. 2013;2013:4191-4. doi: 10.1109/EMBC.2013.6610469.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验