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改进紧急医疗服务信息交流:实体解析自动化方法。

Improving Emergency Medical Services Information Exchange: Methods for Automating Entity Resolution.

机构信息

University of Texas Southwestern Medical Center, Department of Emergency Medicine. Dallas, TX, USA.

University of Texas Southwestern Medical Center, Clinical Informatics Center. Dallas, TX, USA.

出版信息

Stud Health Technol Inform. 2022 May 20;291:17-26. doi: 10.3233/SHTI220004.

Abstract

The 21st century has seen an enormous growth in emergency medical services (EMS) information technology systems, with corresponding accumulation of large volumes of data. Despite this growth, integration efforts between EMS-based systems and electronic health records, and public-sector databases have been limited due to inconsistent data structure, data missingness, and policy and regulatory obstacles. Efforts to integrate EMS systems have benefited from the evolving science of entity resolution and record linkage. In this chapter, we present the history and fundamentals of record linkage techniques, an overview of past uses of this technology in EMS, and a look into the future of record linkage techniques for integrating EMS data systems including the use of machine learning-based techniques.

摘要

21 世纪见证了紧急医疗服务 (EMS) 信息技术系统的巨大发展,相应地积累了大量数据。尽管有了这种增长,但由于数据结构不一致、数据缺失以及政策和监管障碍,基于 EMS 的系统与电子健康记录和公共部门数据库之间的集成工作一直受到限制。整合 EMS 系统的努力得益于实体解析和记录链接这门不断发展的科学。在本章中,我们介绍了记录链接技术的历史和基础,概述了过去在 EMS 中使用这项技术的情况,并展望了未来在整合 EMS 数据系统中使用记录链接技术,包括使用基于机器学习的技术。

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