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A bottom-up approach to creating an ontology for medication indications
Journal of the American Medical Informatics Association ( IF 6.4 ) Pub Date : 2021-01-23 , DOI: 10.1093/jamia/ocaa331
Stuart J Nelson 1 , Allen Flynn 2 , Mark S Tuttle 3
Affiliation  

Abstract
Objectives
The study sought to learn if it were possible to develop an ontology that would allow the Food and Drug Administration approved indications to be expressed in a manner computable and comparable to what is expressed in an electronic health record.
Materials and Methods
A random sample of 1177 of the 3000+ extant, distinct medical products (identified by unique new drug application numbers) was selected for investigation. Close manual examination of the indication portion of the labels for these drugs led to the development of a formal model of indications.
Results
The model represents each narrative indication as a disjunct of conjuncts of assertions about an individual. A desirable attribute is that each assertion about an individual should be testable without reference to other contextual information about the situation. The logical primitives are chosen from 2 categories (context and conditions) and are linked to an enumeration of uses, such as prevention. We found that more than 99% of approved label indications for treatment or prevention could be so represented.
Discussion
While some indications are straightforward to represent, difficulties stem from the need to represent temporal or sequential references. In addition, there is a mismatch of terminologies between what is present in an electronic health record and in the label narrative.
Conclusions
A workable model for formalizing drug indications is possible. Remaining challenges include designing workflow to model narrative label indications for all approved drug products and incorporation of standard vocabularies.


中文翻译:

为药物适应症创建本体的自下而上方法

摘要
目标
该研究试图了解是否有可能开发一种本体,使食品和药物管理局批准的适应症能够以可计算的方式表达,并且与电子健康记录中表达的内容相当。
材料和方法
从 3000 多种现存的、不同的医疗产品(由唯一的新药申请号标识)中随机抽取 1177 种样本进行调查。对这些药物标签的适应症部分进行仔细的人工检查导致了适应症正式模型的开发。
结果
该模型将每个叙述指示表示为关于个人的断言的连词的分离。一个理想的属性是,关于个人的每个断言都应该是可测试的,而无需参考有关情况的其他上下文信息。逻辑原语是从 2 个类别(上下文和条件)中选择的,并与使用的枚举相关联,例如预防。我们发现,超过 99% 的已获批准的治疗或预防标签适应症可以这样表示。
讨论
虽然有些迹象很容易表示,但困难源于表示时间或顺序参考的需要。此外,电子健康记录和标签叙述中存在的术语不匹配。
结论
正式确定药物适应症的可行模型是可能的。剩下的挑战包括设计工作流程以模拟所有已批准药品的叙述性标签适应症和标准词汇的结合。
更新日期:2021-03-19
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