Denny Joshua C, Speltz Peter, Maddox Raquel, Stein Glenn, Xu Hua, Spickard Anderson
Department of Biomedical Informatics, Vanderbilt University, Nashville, TN;
AMIA Annu Symp Proc. 2010 Nov 13;2010:157-61.
Accurate assessment and evaluation of medical curricula has long been a goal of medical educators. Current methods rely on manually-entered keywords and trainee-recorded logs of case exposure. In this study, we used natural language processing to compare the clinical content coverage in a four-year medical curriculum to the electronic medical record notes written by clinical trainees. The content coverage was compared for each of 25 agreed-upon core clinical problems (CCPs) and seven categories of infectious diseases. Most CCPs were covered in both corpora. Lecture curricula more frequently represented rare curricula, and several areas of low content coverage were identified, primarily related to outpatient complaints. Such methods may prove useful for future curriculum evaluations and revisions.
准确评估和评价医学课程一直是医学教育工作者的目标。目前的方法依赖于手动输入的关键词和学员记录的病例接触日志。在本研究中，我们使用自然语言处理技术，将一个四年制医学课程中的临床内容覆盖情况与临床实习生书写的电子病历记录进行比较。对25个商定的核心临床问题（CCP）中的每一个以及七类传染病的内容覆盖情况进行了比较。两个语料库中都涵盖了大多数CCP。讲座课程更频繁地呈现罕见课程，并确定了几个内容覆盖较低的领域，主要与门诊投诉有关。此类方法可能对未来的课程评估和修订有用。
