Department of Clinical Leadership and Research, Biomedical Informatics Center, George Washington University, Washington, DC, USA.
Department of Medicine, University of Michigan, Ann Arbor, Michigan, USA.
J Am Med Inform Assoc. 2021 Mar 18;28(4):753-758. doi: 10.1093/jamia/ocaa331.
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.
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.
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.
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.
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.
本研究旨在探讨是否有可能开发一种本体论，使食品和药物管理局批准的适应证以一种可计算且可与电子健康记录中表达的内容相媲美的方式表达。
从 3000 多种现有独特药物产品（通过新药申请编号识别）中随机抽取了 1177 个进行调查。对这些药物标签适应证部分进行仔细的手动检查，导致了适应证形式模型的发展。
该模型将每个叙述性适应证表示为关于个体的合取的析取。一个理想的属性是，关于个体的每一个断言都应该可以在不参考关于情况的其他上下文信息的情况下进行测试。逻辑基元从 2 个类别（上下文和条件）中选择，并链接到使用枚举，如预防。我们发现，超过 99%的已批准标签适应证（治疗或预防）可以如此表示。
虽然一些适应证很容易表示，但困难源于需要表示时间或顺序参考。此外，电子健康记录和标签叙述中存在术语不匹配的问题。
形式化药物适应证的可行模型是可能的。仍然存在的挑战包括设计用于为所有批准的药物产品建模叙述标签适应证的工作流程，以及纳入标准词汇表。
