Zeng Qing T, Tse Tony, Crowell Jon, Divita Guy, Roth Laura, Browne Allen C
DSG, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
AMIA Annu Symp Proc. 2005;2005:859-63.
We have developed a systematic methodology using corpus-based text analysis followed by human review to assign "consumer-friendly display (CFD) names" to medical concepts from the National Library of Medicine (NLM) Unified Medical Language System (UMLS) Metathesaurus. Using NLM MedlinePlus queries as a corpus of consumer expressions and a collaborative Web-based tool to facilitate review, we analyzed 425 frequently occurring concepts. As a preliminary test of our method, we evaluated 34 ana-lyzed concepts and their CFD names, using a questionnaire modeled on standard reading assessments. The initial results that consumers (n=10) are more likely to understand and recognize CFD names than alternate labels suggest that the approach is useful in the development of consumer health vocabularies for displaying understandable health information.
我们开发了一种系统方法，先基于语料库进行文本分析，然后由人工审核，以便为美国国立医学图书馆（NLM）统一医学语言系统（UMLS）元词表中的医学概念赋予“消费者友好型显示（CFD）名称”。我们以NLM MedlinePlus查询作为消费者表达语料库，并使用一个基于网络的协作工具来促进审核，分析了425个频繁出现的概念。作为对我们方法的初步测试，我们使用一个基于标准阅读评估的问卷，对34个已分析的概念及其CFD名称进行了评估。消费者（n = 10）更有可能理解和识别CFD名称而非替代标签这一初步结果表明，该方法在开发用于展示易懂健康信息的消费者健康词汇方面很有用。
