Dipartimento di Scienza e Tecnologia del Farmaco, Università degli Studi di Torino, Via Pietro Giuria 9, 10125 Turin, Italy.
Centro di Competenza sul Calcolo Scientifico C3S, Università degli Studi di Torino, Corso Svizzera 185, 10149 Turin, Italy.
Int J Environ Res Public Health. 2021 May 2;18(9):4859. doi: 10.3390/ijerph18094859.
In a Drug Prescription Network (DPN), each drug is represented as a node and two drugs co-prescribed to the same patient are represented as an edge linking the nodes. The use of DPNs is a novel approach that has been proposed as a means to study the complexity of drug prescription. The aim of this study is to demonstrate the analytical power of the DPN-based approach when it is applied to the analysis of administrative data. Drug prescription data that were collected at a local health unit (ASL TO4, Regione Piemonte, Italy), over a 12-month period (July 2018-June 2019), were used to create several DPNs that correspond to the five levels of the Anatomical Therapeutic Chemical classification system. A total of 5,431,335 drugs prescribed to 361,574 patients (age 0-100 years; 54.7% females) were analysed. As indicated by our results, the DPNs were dense networks, with giant components that contain all nodes. The disassortative mixing of node degrees was observed, which implies that non-random connectivity exists in the networks. Network-based methods have proven to be a flexible and efficient approach to the analysis of administrative data on drug prescription.
在药物处方网络 (DPN) 中,每种药物都表示为一个节点,而同时开给同一患者的两种药物则表示为连接节点的边。DPN 的使用是一种新方法,被提议作为研究药物处方复杂性的手段。本研究旨在展示基于 DPN 的方法在分析行政数据时的分析能力。使用在意大利皮埃蒙特大区(ASL TO4)的一个地方卫生单位收集的 12 个月(2018 年 7 月至 2019 年 6 月)的药物处方数据,创建了与解剖治疗化学分类系统的五个层次相对应的几个 DPN。共分析了 361,574 名患者(年龄 0-100 岁;女性占 54.7%)开出的 5,431,335 种药物。结果表明,DPN 是密集网络,具有包含所有节点的巨型组件。观察到节点度数的反关联混合,这意味着网络中存在非随机连接。基于网络的方法已被证明是一种灵活高效的分析药物处方行政数据的方法。