Use of emergency department electronic medical records for automated epidemiological surveillance of suicide attempts: a French pilot study
Use of emergency department electronic medical records for automated epidemiological surveillance of suicide attempts: a French pilot study
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DOI：
10.1002/mpr.1522
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发表时间：
2017-06-01
影响因子：
3.1
通讯作者：
Potinet-Pagliaroli, Veronique
中科院分区：
文献类型：
--
作者：
Metzger, Marie-Helene;Tvardik, Nastassia;Potinet-Pagliaroli, Veronique
本研究的目的是确定一个专家系统的基础上自动化处理的电子健康记录（EHRs）是否可以提供一个更准确的估计每年的急诊室（艾德）访问自杀企图在法国，相比，目前的国家监测系统的基础上手动编码的急诊医生。在里昂大学医院进行了一项可行性研究，使用了2012年所有艾德患者就诊的数据。在自动数据提取和预处理后，包括通过使用统一医学语言系统对医学自由文本进行自动编码，使用七种不同的机器学习方法将艾德就诊的原因分类为自杀企图与其他原因。这些不同的方法的性能进行了比较，通过使用F-措施。在2012年艾德收治的444例患者的测试样本中（98例自杀企图，48例自杀意念，292例对照，无记录的非致命性自杀行为），自动检测自杀企图的F测量值范围为70.4%至95.3%。随机森林和朴素贝叶斯方法表现最好。这项研究表明，与目前对自杀企图的国家监测相比，机器学习方法可以提高流行病学指标的质量。
The aim of this study was to determine whether an expert system based on automated processing of electronic health records (EHRs) could provide a more accurate estimate of the annual rate of emergency department (ED) visits for suicide attempts in France, as compared to the current national surveillance system based on manual coding by emergency practitioners. A feasibility study was conducted at Lyon University Hospital, using data for all ED patient visits in 2012. After automatic data extraction and pre-processing, including automatic coding of medical free-text through use of the Unified Medical Language System, seven different machine-learning methods were used to classify the reasons for ED visits into suicide attempts versus other reasons. The performance of these different methods was compared by using the F-measure. In a test sample of 444 patients admitted to the ED in 2012 (98 suicide attempts, 48 cases of suicidal ideation, and 292 controls with no recorded non-fatal suicidal behaviour), the F-measure for automatic detection of suicide attempts ranged from 70.4% to 95.3%. The random forest and naive Bayes methods performed best. This study demonstrates that machine-learning methods can improve the quality of epidemiological indicators as compared to current national surveillance of suicide attempts.