Takahashi Yoshimitsu, Ishizaki Tatsuro, Nakayama Takeo, Kawachi Ichiro
Department of Health Informatics, Kyoto University School of Public Health, Yoshida-Konoe, Sakyo, Kyoto 606-8501, Japan; Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA 02115, USA.
Research Team for Human Care, Tokyo Metropolitan Institute of Gerontology, 35-2 Sakae, Itabashi, Tokyo 173-0015, Japan.
Health Policy. 2016 Mar;120(3):334-41. doi: 10.1016/j.healthpol.2016.01.020. Epub 2016 Feb 3.
Duplicative prescriptions refer to situations in which patients receive medications for the same condition from two or more sources. Health officials in Japan have expressed concern about medical "waste" resulting from this practices. We sought to conduct descriptive analysis of duplicative prescriptions using social network analysis and to report their prevalence across ages.
We analyzed a health insurance claims database including 1.24 million people from December 2012. Through social network analysis, we examined the duplicative prescription networks, representing each medical facility as nodes, and individual prescriptions for patients as edges.
The prevalence of duplicative prescription for any drug class was strongly correlated with its frequency of prescription (r=0.90). Among patients aged 0-19, cough and colds drugs showed the highest prevalence of duplicative prescriptions (10.8%). Among people aged 65 and over, antihypertensive drugs had the highest frequency of prescriptions, but the prevalence of duplicative prescriptions was low (0.2-0.3%). Social network analysis revealed clusters of facilities connected via duplicative prescriptions, e.g., psychotropic drugs showed clustering due to a few patients receiving drugs from 10 or more facilities.
Overall, the prevalence of duplicative prescriptions was quite low - less than 10% - although the extent of the problem varied by drug class and age group. Our approach illustrates the potential utility of using a social network approach to understand these practices.
重复处方是指患者从两个或更多来源接受针对同一病症的药物治疗的情况。日本卫生官员对这种做法导致的医疗“浪费”表示担忧。我们试图使用社会网络分析对重复处方进行描述性分析,并报告其在不同年龄段的患病率。
我们分析了一个自2012年12月起涵盖124万人的医疗保险理赔数据库。通过社会网络分析,我们研究了重复处方网络,将每个医疗机构视为节点,将患者的个体处方视为边。
任何药物类别的重复处方患病率与其处方频率密切相关(r = 0.90)。在0至19岁的患者中,止咳感冒药的重复处方患病率最高(10.8%)。在65岁及以上的人群中,降压药的处方频率最高,但重复处方的患病率较低(0.2 - 0.3%)。社会网络分析揭示了通过重复处方连接的医疗机构集群,例如,精神药物由于少数患者从10个或更多医疗机构接受药物治疗而呈现出集群现象。
总体而言,重复处方的患病率相当低——低于10%——尽管问题的严重程度因药物类别和年龄组而异。我们的方法说明了使用社会网络方法理解这些做法的潜在效用。