Mantena Surendranath, Schadow Gunther
Regenstrief Institute, Indianapolis, IN, USA.
AMIA Annu Symp Proc. 2007 Oct 11;2007:498-502.
A standardized terminology for medical indications is essential for building e-prescription applications with decision support. The FDA has adopted the Veteran Administration and Kaiser Permanente (VA/KP) Problem List Subset of SNOMED as the terminology to represent indications in electronic labels. In this paper, we evaluate the ability of this subset to represent the text phrases extracted from a medication decision support system and the indications section of existing drug labels. We compiled a test set of 1265 distinct indication phrases and mapped them to (1) UMLS, (2) Entire SNOMED, (3) All Precoordinated concepts from the "Clinical Finding" hierarchy of SNOMED, and (4) VA/KP Subset. 95% of the phrases mapped to concepts in UMLS, 90.3% to SNOMED, 79.5% to SNOMED Precordinated and 71.1% mapped completely or partially to concepts in the VA/KP subset. Our study suggests that the VA/KP Subset has significant limitations for coding drug indications; however, when focusing on indications as medical conditions only, the coverage seems more adequate.
用于医学适应症的标准化术语对于构建具有决策支持功能的电子处方应用程序至关重要。美国食品药品监督管理局(FDA)已采用SNOMED的退伍军人管理局和凯撒医疗集团(VA/KP)问题列表子集作为在电子标签中表示适应症的术语。在本文中,我们评估了该子集表示从药物决策支持系统和现有药品标签的适应症部分提取的文本短语 的能力。我们编制了一个包含1265个不同适应症短语的测试集,并将它们映射到:(1)统一医学语言系统(UMLS),(2)完整的SNOMED,(3)来自SNOMED“临床发现”层次结构的所有预协调概念,以及(4)VA/KP子集。95%的短语映射到UMLS中的概念,90.3%映射到SNOMED,79.5%映射到SNOMED预协调概念,71.1%完全或部分映射到VA/KP子集中的概念。我们的研究表明,VA/KP子集在编码药物适应症方面存在重大局限性;然而,当仅将适应症视为医疗状况时,覆盖范围似乎更充足。