Fabry Paul, Baud Robert, Ruch Patrick, Despont-Gros Christelle, Lovis Christian
CRED, Centre Hospitalier Universitaire de Sherbrooke, Que., Canada.
Int J Med Inform. 2006 Aug;75(8):624-32. doi: 10.1016/j.ijmedinf.2005.08.011. Epub 2005 Oct 10.
Problem lists summarize an aspect of the patient's medical history and provide an important way to implement entry points for clinical pathways and guideline-oriented care. However, in order to automate processes based on problem lists, the use of controlled vocabularies is required. We developed a methodology to extract a collection of standardized problem-related terms from medical documents entered in free text by physicians.
We extracted a corpus of sentences describing problems from a randomized selection of admission notes collected at the University Hospitals of Geneva. Theses sentences underwent manual and automatic normalization processes, and a statistical clustering, in order to build a set of terms.
We obtained 17,805 sentences from 5000 admission notes. We refined them into 1546 terms, 88.6% of which could be related to a relevant problem statement.
A clinically relevant problems terminology was derived from clinical admission notes in free-text using a few methodical steps with a reasonable investment of human resources. Such an approach will ease the development and the use of problem lists better suited to user needs.
问题列表总结了患者病史的一个方面，并提供了一种重要方式来实施临床路径和以指南为导向的护理的切入点。然而，为了基于问题列表实现流程自动化，需要使用受控词汇表。我们开发了一种方法，用于从医生以自由文本形式输入的医疗文档中提取标准化问题相关术语的集合。
我们从日内瓦大学医院随机抽取的入院记录中提取了描述问题的句子语料库。这些句子经过手动和自动规范化处理以及统计聚类，以构建一组术语。
我们从5000份入院记录中获得了17805个句子。我们将它们提炼为1546个术语，其中88.6%可与相关问题陈述相关联。
通过几个有条不紊的步骤，并投入合理的人力资源，从自由文本形式的临床入院记录中得出了与临床相关的问题术语。这种方法将便于开发和使用更符合用户需求的问题列表。
