National Institute of Infectious Diseases.
EM Systems Co. Ltd.
Biosci Trends. 2018;12(5):523-525. doi: 10.5582/bst.2018.01201.
Based on prescriptions filled at external pharmacies, prescription surveillance (PS) in Japan has been reporting the estimated numbers of influenza and varicella patients and people prescribed certain drugs since 2009. Every morning, this system estimates the numbers of patients from the numbers of prescriptions filled nationwide for neuraminidase inhibitors, anti-herpes virus drugs, antibiotic drugs, antipyretic analgesics, and multi-ingredient cold medications. Moreover, it can detect "unexplained" infectious diseases that are not explained as infectious diseases monitored by other surveillance systems. Such "unexplained" infectious diseases might be emerging and re-emerging infectious diseases including bioterrorism attacks, which are reportedly difficult to diagnose, at least in early outbreak stages. To ascertain the system's potential benefits, this study examined schemes to detect "unexplained" infectious diseases using PS information. The numbers of patients prescribed the respective drugs are first regressed on the known infectious diseases, time trends, and dummies for day-of-the-week, holidays, and days following a holiday. Known infectious diseases are defined as covered by the National Official Sentinel Surveillance for Infectious Diseases under the Infection Control Law. After the numbers of patients from PS are compared with the predicted numbers of patients, their probabilities of occurrence are calculated. We examined the system's prospective operation from January 2017 through July 2018. The criterion we used to define aberrations varied, from 0.01 to 10. For criteria of 0.01 and 10 we found 254 and 15 aberrations, respectively. We confirmed its feasibility and effectiveness.
基于外部药店的处方数据,日本自 2009 年以来一直在通过处方监测(PS)报告流感和水痘患者以及某些药物处方人群的估计数量。该系统每天早上根据全国范围内使用神经氨酸酶抑制剂、抗疱疹病毒药物、抗生素药物、解热镇痛药和多种成分感冒药的处方数量,估算患者人数。此外,它还可以检测到其他监测系统无法解释的“不明”传染病。这些“不明”传染病可能是新兴和重现传染病,包括据报道难以诊断的生物恐怖袭击,至少在早期爆发阶段是如此。为了确定该系统的潜在益处,本研究利用 PS 信息检查了检测“不明”传染病的方案。首先,将患者的处方数量回归到已知传染病、时间趋势以及周几、节假日和节假日后日的虚拟变量上。已知传染病是指《传染病控制法》规定的国家官方哨点传染病监测所涵盖的传染病。将 PS 中的患者数量与预测患者数量进行比较后,计算其发生概率。我们从 2017 年 1 月到 2018 年 7 月检查了系统的前瞻性运行情况。我们用来定义异常的标准有所不同,从 0.01 到 10。对于 0.01 和 10 的标准,我们分别发现了 254 个和 15 个异常。我们确认了它的可行性和有效性。