McDonough Caitrin W, Smith Steven M, Cooper-DeHoff Rhonda M, Hogan William R
Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL, United States.
Division of Cardiovascular Medicine, Department of Medicine, College of Medicine, University of Florida, Gainesville, FL, United States.
JMIR Med Inform. 2020 Feb 27;8(2):e14777. doi: 10.2196/14777.
Computable phenotypes have the ability to utilize data within the electronic health record (EHR) to identify patients with certain characteristics. Many computable phenotypes rely on multiple types of data within the EHR including prescription drug information. Hypertension (HTN)-related computable phenotypes are particularly dependent on the correct classification of antihypertensive prescription drug information, as well as corresponding diagnoses and blood pressure information.
This study aimed to create an antihypertensive drug classification system to be utilized with EHR-based data as part of HTN-related computable phenotypes.
We compared 4 different antihypertensive drug classification systems based off of 4 different methodologies and terminologies, including 3 RxNorm Concept Unique Identifier (RxCUI)-based classifications and 1 medication name-based classification. The RxCUI-based classifications utilized data from (1) the Drug Ontology, (2) the new Medication Reference Terminology, and (3) the Anatomical Therapeutic Chemical Classification System and DrugBank, whereas the medication name-based classification relied on antihypertensive drug names. Each classification system was applied to EHR-based prescription drug data from hypertensive patients in the OneFlorida Data Trust.
There were 13,627 unique RxCUIs and 8025 unique medication names from the 13,879,046 prescriptions. We observed a broad overlap between the 4 methods, with 84.1% (691/822) to 95.3% (695/729) of terms overlapping pairwise between the different classification methods. Key differences arose from drug products with multiple dosage forms, drug products with an indication of benign prostatic hyperplasia, drug products that contain more than 1 ingredient (combination products), and terms within the classification systems corresponding to retired or obsolete RxCUIs.
In total, 2 antihypertensive drug classifications were constructed, one based on RxCUIs and one based on medication name, that can be used in future computable phenotypes that require antihypertensive drug classifications.
可计算表型能够利用电子健康记录(EHR)中的数据来识别具有特定特征的患者。许多可计算表型依赖于EHR中的多种类型数据,包括处方药信息。与高血压(HTN)相关的可计算表型尤其依赖于抗高血压处方药信息的正确分类,以及相应的诊断和血压信息。
本研究旨在创建一种抗高血压药物分类系统,作为与HTN相关的可计算表型的一部分,用于基于EHR的数据。
我们比较了基于4种不同方法和术语的4种不同抗高血压药物分类系统,包括3种基于RxNorm概念唯一标识符(RxCUI)的分类和1种基于药物名称的分类。基于RxCUI的分类利用了来自(1)药物本体、(2)新的药物参考术语和(3)解剖治疗化学分类系统及药物银行的数据,而基于药物名称的分类则依赖于抗高血压药物名称。每个分类系统都应用于来自OneFlorida数据信托中高血压患者的基于EHR的处方药数据。
在13879046张处方中,有13627个唯一的RxCUI和8025个唯一的药物名称。我们观察到这4种方法之间有广泛的重叠,不同分类方法之间两两重叠的术语比例为84.1%(691/822)至95.3%(695/729)。关键差异源于具有多种剂型的药品、具有良性前列腺增生指征的药品、含有不止一种成分的药品(复方制剂),以及分类系统中与已停用或过时的RxCUI相对应的术语。
总共构建了2种抗高血压药物分类,一种基于RxCUI,一种基于药物名称,可用于未来需要抗高血压药物分类的可计算表型。