Bui Alex A T, Taira Ricky K, El-Saden Suzie, Dordoni Alicia, Aberle Denise R
Medical Informatics Group & Biomedical Informatics Center, University of California-Los Angeles, 924 Westwood Boulevard, Los Angeles, CA 90024, USA.
Stud Health Technol Inform. 2004;107(Pt 1):587-91.
The problem-oriented electronic medical record has been investigated as an alternative to source-oriented organization of patient data. At the core of a problem-oriented view is the medical problem list. Maintenance of the medical problem list is often manual, making it highly user dependent. We detail the beginnings of an automated medical problem list generator based on ICD-9: given a set of ICD-9 codes associated with a patient record, the system maps the codes (and related data) to an anatomy-centric hierarchy. 1 million patient encounters from an outpatient setting were reviewed to generate a unique set of 7,890 ICD-9 codes. Natural language processing of the ICD-9 string descriptions identified 1,981 anatomical terms, which were subsequently mapped to one of 21 anatomical categories. The output of the medical problem list generator was then used to create a problem-oriented, gestalt view of a patient's medical record. Preliminary evaluation of the generator revealed 100% recall, but only 60% precision. This initial work has highlighted several issues in defining a medical problem list, including questions of granularity and performance trade-offs.
面向问题的电子病历已被作为一种替代面向源的患者数据组织方式进行研究。面向问题观点的核心是医疗问题列表。医疗问题列表的维护通常是手动的,这使其高度依赖用户。我们详细介绍了基于ICD - 9的自动医疗问题列表生成器的开端:给定一组与患者记录相关的ICD - 9代码,系统将这些代码(及相关数据)映射到以解剖学为中心的层次结构中。对来自门诊环境的100万次患者就诊进行了审查,以生成一组独特的7890个ICD - 9代码。对ICD - 9字符串描述进行自然语言处理识别出1981个解剖学术语,这些术语随后被映射到21个解剖学类别中的一个。然后,医疗问题列表生成器的输出被用于创建患者病历的面向问题的整体视图。对该生成器的初步评估显示召回率为100%,但精确率仅为60%。这项初步工作突出了在定义医疗问题列表时的几个问题,包括粒度问题和性能权衡问题。