Columbia University Irving Medical Center, NY, USA.
Odysseus Data Services Inc, Cambridge, MA, USA.
Stud Health Technol Inform. 2024 Jan 25;310:53-57. doi: 10.3233/SHTI230926.
Observational research utilizes patient information from many disparate databases worldwide. To be able to systematically analyze data and compare the results of such research studies, information about exposure to drugs or classes of drugs needs to be harmonized across these data. The NLM's RxNorm drug terminology and WHO's ATC classification serve these needs but are currently not satisfactorily combined into a common system. Creating such system is hampered by a number of challenges, resulting from different approaches to representing attributes of drugs and ontological rules. Here, we present a combined ATC-RxNorm drug hierarchy, allowing to use ATC classes for retrieval of drug information in large scale observational data. We present the heuristic for maintaining this resource and evaluate it in a real world database containing drug and drug classification information.
观察性研究利用来自全球许多不同数据库的患者信息。为了能够系统地分析数据并比较此类研究的结果,需要在这些数据中协调关于药物或药物类别的暴露信息。NLM 的 RxNorm 药物术语和世卫组织的 ATC 分类满足了这些需求,但目前尚未令人满意地组合成一个通用系统。创建这样的系统受到许多挑战的阻碍,这些挑战源于代表药物属性和本体论规则的不同方法。在这里,我们提出了一个组合的 ATC-RxNorm 药物层次结构,允许在大规模观察性数据中使用 ATC 类别来检索药物信息。我们提出了维护此资源的启发式方法,并在包含药物和药物分类信息的真实世界数据库中对其进行了评估。