Nango Daisuke, Sekizuka Tuyoshi, Goto Makoto, Echizen Hirotoshi
Department of Pharmacy, Shin-Yurigaoka General Hospital.
INTAGE Healthcare Inc.
Yakugaku Zasshi. 2022;142(4):341-344. doi: 10.1248/yakushi.21-00178-5.
Nowadays, medical big data has been developed and made available in a variety of fields such as epidemiology and pharmacovigilance. Spontaneous reporting databases are one category of medical big data and that has been adequate for analysing events related to side effects that rarely occur in general practice. These data are freely available in several countries. In Japan, the Pharmaceuticals and Medical Devices Agency has developed the Japanese Adverse Drug Event Report (JADER), and the Food and Drug Administration (FDA) developed the FDA Adverse Events Reporting System (FAERS) in the United States. Since the release of these medical big data, many researchers in academic and research setting have accessed them, but it is still difficult for many medical professionals to analyse these data due to costs and operation of requisite statistical software. In this section, we give some tips to study spontaneous reporting databases resulting from our learning experiences.
如今，医学大数据已得到发展，并在流行病学和药物警戒等多个领域得到应用。自发报告数据库是医学大数据的一种类型，足以用于分析在一般医疗实践中很少发生的与副作用相关的事件。这些数据在多个国家均可免费获取。在日本，药品和医疗器械管理局开发了日本药品不良反应报告（JADER），美国食品药品监督管理局（FDA）开发了FDA不良事件报告系统（FAERS）。自从这些医学大数据发布以来，许多学术和研究机构的研究人员都可以访问它们，但由于成本和所需统计软件的操作问题，许多医学专业人员仍然难以分析这些数据。在本节中，我们根据自己的学习经验提供一些研究自发报告数据库的小贴士。
