Lelong Romain, Soualmia Lina, Dahamna Badisse, Griffon Nicolas, Darmoni Stéfan J
Department of Biomedical Informatics, Rouen University Hospital, France.
Stud Health Technol Inform. 2017;235:121-125.
While the digitization of medical documents has greatly expanded during the past decade, health information retrieval has become a great challenge to address many issues in medical research. Information retrieval in electronic health records (EHR) should also reduce the difficult tasks of manual information retrieval from records in paper format or computer. The aim of this article was to present the features of a semantic search engine implemented in EHRs. A flexible, scalable and entity-oriented query language tool is proposed. The program is designed to retrieve and visualize data which can support any Conceptual Data Model. The search engine deals with structured and unstructured data, for a sole patient from a caregiver perspective, and for a number of patients (e.g. epidemiology). Several types of queries on a test database containing 2,000 anonymized patients EHRs (i.e. approximately 200,000 records) were tested. These queries were able to accurately treat symbolic, textual, numerical and chronological data.
在过去十年中，虽然医学文档的数字化有了极大的发展，但健康信息检索已成为应对医学研究中诸多问题的一项重大挑战。电子健康记录（EHR）中的信息检索还应减少从纸质记录或计算机记录中手动检索信息的艰巨任务。本文的目的是介绍在电子健康记录中实现的语义搜索引擎的特点。提出了一种灵活、可扩展且面向实体的查询语言工具。该程序旨在检索和可视化能够支持任何概念数据模型的数据。该搜索引擎从护理人员的角度处理单个患者的结构化和非结构化数据，以及多个患者的数据（如流行病学数据）。在一个包含2000份匿名患者电子健康记录（即约200,000条记录）的测试数据库上对几种类型的查询进行了测试。这些查询能够准确处理符号、文本、数值和时间数据。
