Biron P, Metzger M H, Pezet C, Sebban C, Barthuet E, Durand T
Léon Bérard Cancer Center , Lyon, France.
Université Lyon I - CNRS-UMR 5558 , Lyon, France.
Appl Clin Inform. 2014 Mar 5;5(1):191-205. doi: 10.4338/ACI-2013-08-CR-0065. eCollection 2014.
A full-text search tool was introduced into the daily practice of Léon Bérard Center (France), a health care facility devoted to treatment of cancer. This tool was integrated into the hospital information system by the IT department having been granted full autonomy to improve the system.
To describe the development and various uses of a tool for full-text search of computerized patient records.
The technology is based on Solr, an open-source search engine. It is a web-based application that processes HTTP requests and returns HTTP responses. A data processing pipeline that retrieves data from different repositories, normalizes, cleans and publishes it to Solr, was integrated in the information system of the Leon Bérard center. The IT department developed also user interfaces to allow users to access the search engine within the computerized medical record of the patient.
From January to May 2013, 500 queries were launched per month by an average of 140 different users. Several usages of the tool were described, as follows: medical management of patients, medical research, and improving the traceability of medical care in medical records. The sensitivity of the tool for detecting the medical records of patients diagnosed with both breast cancer and diabetes was 83.0%, and its positive predictive value was 48.7% (gold standard: manual screening by a clinical research assistant).
The project demonstrates that the introduction of full-text-search tools allowed practitioners to use unstructured medical information for various purposes.
一个全文搜索工具被引入到里昂贝拉尔中心(法国)的日常医疗实践中,该中心是一家致力于癌症治疗的医疗机构。这个工具由信息技术部门集成到医院信息系统中,信息技术部门被赋予了充分的自主权来改进该系统。
描述一种用于计算机化患者记录全文搜索工具的开发及各种用途。
该技术基于开源搜索引擎Solr。它是一个基于网络的应用程序,处理HTTP请求并返回HTTP响应。一个从不同存储库检索数据、进行规范化、清理并将其发布到Solr的数据处理管道被集成到里昂贝拉尔中心的信息系统中。信息技术部门还开发了用户界面,以便用户能够在患者的计算机化病历中访问搜索引擎。
在2013年1月至5月期间,平均每月有140名不同用户发起500次查询。该工具的几种用途如下:患者的医疗管理、医学研究以及提高病历中医护可追溯性。该工具检测同时患有乳腺癌和糖尿病患者病历的灵敏度为83.0%,其阳性预测值为48.7%(金标准:由临床研究助理进行人工筛查)。
该项目表明,引入全文搜索工具使从业者能够将非结构化医疗信息用于各种目的。