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过敏诊室的临床数据挖掘和研究。

Clinical data mining and research in the allergy office.

机构信息

Technology & Education Committee American Academy of Allergy, Asthma & Immuology, Fargo, North Dakota, USA.

出版信息

Curr Opin Allergy Clin Immunol. 2010 Jun;10(3):171-7. doi: 10.1097/ACI.0b013e328337bce6.


DOI:10.1097/ACI.0b013e328337bce6
PMID:20179584
Abstract

PURPOSE OF REVIEW: More data are anticipated from the expected increase in use of electronic health records (EHRs). Upcoming initiatives require reporting of quality measures, meaningful use of clinical decision support, alert systems, and pharmacovigilance - knowledge resulting through use of EHRs. Data mining is a new tool that will help us manage information and derive knowledge from these data, and is a part of evolving new disciplines of informatics and knowledge management. RECENT FINDINGS: Studies are reported from smaller clinic data marts to larger repositories and warehouses in various health systems, biomedical registries, and the medical literature on the Internet. Data mining technologies show promise and challenges. Outcome measures as structured data and narrative text can be mined with human assistance and newer automated natural language processing software. Despite advances, the growing diversity of clinic EHRs lack integration and interoperability with Internet-based biomedical databases. SUMMARY: Allergists have the capability to mine clinic EHRs to discover new information, which may be hidden in charts. A central allergy computer can serve not just as a registry but also allows functionalities to enable EHRs' meaningful use. Harmonization of technological and organizational standards will allow seamless use of new natural language processing (NLP) tools and ontologies through a semantic web.

摘要

目的综述:随着电子健康记录(EHR)使用的预期增加,预计会有更多的数据。即将出台的各项举措要求报告质量措施、临床决策支持的有效使用、警报系统和药物警戒——这是通过使用 EHR 获得的知识。数据挖掘是一种新工具,它将帮助我们管理信息并从这些数据中获取知识,是信息学和知识管理新兴学科的一部分。

最新发现:从较小的临床数据集市到各种医疗系统、生物医学登记处以及互联网上的医学文献中的更大存储库和仓库,都有研究报告。数据挖掘技术显示出前景和挑战。可以在人类协助和更新的自动化自然语言处理软件的帮助下挖掘结构化数据和叙述性文本等结果测量指标。尽管取得了进展,但不断增长的临床 EHR 多样性缺乏与基于互联网的生物医学数据库的集成和互操作性。

总结:过敏症专家有能力从临床 EHR 中挖掘新信息,这些信息可能隐藏在图表中。中央过敏计算机不仅可以作为一个登记处,还可以启用功能,实现 EHR 的有效使用。通过语义网,技术和组织标准的协调将允许无缝使用新的自然语言处理(NLP)工具和本体。

相似文献

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[10]
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引用本文的文献

[1]
Pharmacovigilance - Technological Advancements, Recent Developments and Innovations.

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[2]
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