Data from: Co-prescription network reveals social dynamics of opioid doctor shopping

This paper examines network prominence in a co-prescription network as an indicator of opioid doctor shopping (i.e., fraudulent solicitation of opioids from multiple prescribers). Using longitudinal data from a large commercially insured population, we construct a network where a tie between patients is weighted by the number of shared opioid prescribers. Given prior research suggesting that doctor shopping may be a social process, we hypothesize that active doctor shoppers will occupy central structural positions in this network. We show that network prominence, operationalized using PageRank, is associated with more opioid prescriptions, higher predicted risk for dangerous morphine dosage, opioid overdose, and opioid use disorder, controlling for number of prescribers and other variables. Moreover, as a patient's prominence increases over time, so does their risk for these outcomes, compared to their own average level of risk. Results highlight the importance of co-prescription networks in characterizing high-risk social dynamics.

本文以联合处方网络（co-prescription network）中的网络突出性作为阿片类药物医生转购行为（doctor shopping，即从多名处方医师处欺诈性获取阿片类药物的行为）的识别指标。本研究依托大型商业保险参保人群的纵向数据，构建了联合处方网络，其中患者间的关联边权重由二者共享的阿片类处方医师数量决定。鉴于既往研究提示医生转购行为属于一种社会过程，我们提出研究假设：活跃的医生转购者将在该网络中占据核心结构位置。研究结果显示，在控制处方医师数量及其他变量的前提下，以PageRank进行操作化定义的网络突出性，与更高的阿片类药物处方量、更高的危险吗啡剂量预测风险、阿片类药物过量风险以及阿片类使用障碍（opioid use disorder）风险均存在显著关联。此外，相较于患者自身的平均风险水平，随着患者的网络突出性随时间推移不断提升，其罹患上述不良结局的风险也会同步升高。本研究结果凸显了联合处方网络在刻画高风险社会动态方面的重要价值。