MedEx: a medication information extraction system for clinical narratives
MedEx: a medication information extraction system for clinical narratives
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DOI：
10.1197/jamia.m3378
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发表时间：
2010-01-01
影响因子：
6.4
通讯作者：
Denny, Joshua C.
中科院分区：
文献类型：
--
作者：
Xu, Hua;Stenner, Shane P.;Denny, Joshua C.
药物信息是电子病历中最重要的临床数据类型之一。它对于医疗保健安全和质量以及使用电子病历数据的临床研究至关重要。然而，药物数据通常以自由文本的形式记录在临床记录中。因此，依赖于编码数据的其他计算机化应用程序无法访问它们。我们描述了一种新的自然语言处理系统（MedEx），它可以从临床记录中提取药物信息。MedEx最初是根据出院摘要开发的。使用50份出院总结数据集进行评估，结果表明，该方法不仅在识别药品名称（f值为93.2%），而且在识别强度、路径和频率等特征信息（f值分别为94.5%、93.9%和96.0%）方面表现良好。然后我们将MedEx原液应用于门诊就诊记录。在一组25个诊所就诊记录上，它的f值也达到了90%以上。
Medication information is one of the most important types of clinical data in electronic medical records. It is critical for healthcare safety and quality, as well as for clinical research that uses electronic medical record data. However, medication data are often recorded in clinical notes as free-text. As such, they are not accessible to other computerized applications that rely on coded data, We describe a new natural language processing system (MedEx), which extracts medication information from clinical notes. MedEx was initially developed using discharge summaries. An evaluation using a data set of 50 discharge summaries showed it performed well on identifying not only drug names (F-measure 93.2%), but also signature information, such as strength, route, and frequency, with F-measures of 94.5%, 93.9%, and 96.0% respectively. We then applied MedEx unchanged to outpatient clinic visit notes. It performed similarly with F-measures over 90% on a set of 25 clinic visit notes.