Department of Pharmacy, The General Hospital of the People's Liberation Army, 28 Fu Xing Road, Beijing, 100853, China.
Ther Innov Regul Sci. 2020 Jan;54(1):32-41. doi: 10.1007/s43441-019-00027-z. Epub 2020 Jan 6.
Computerized detection is a promising method for monitoring adverse drug events (ADEs); however, this method is currently in its infancy and is a new area of exploration in China. This study aimed to develop a computerized ADE alarm and assessment system to help pharmacists effectively detect, assess, and analyze possible ADEs in patients in China.
Based on the clinical characteristics of these adverse drug events, we designed combined multiparameters as ADE alert rules to be assembled into detection configurations. We also developed system function modules by extracting data from the People's Liberation Army (PLA) general hospital information system (electronic medical records). Positive predictive values were calculated for the alert.
Five function modules were created in this platform: automatic screening, assisted evaluation, risk characteristic analysis, report generation into SRS (spontaneous reporting system), and a dictionary database. Four ADE alert configurations were set in our ADE alarm and assessment system: drug-related thrombocytopenia, anemia, liver injury, and kidney injury. The positive predictive values of the 4 monitored ADEs were approximately 44.4% to 95.8%.
An automatic ADE screening system was established for hospitalized patients in Chinese medical institutions. Compared with previous studies, combined drug-event alerts and a system-assisted assessment interface performed better than alerts based only on laboratory values. Furthermore, this platform's assisted-layered evaluation and risk factor analysis functions could save considerable time for professionals and improve early prevention of potentially serious ADEs. To date, this system has been applied in 10 large-scale medical institutions.
计算机化检测是监测药物不良事件（ADE）的一种很有前途的方法；然而，这种方法目前还处于起步阶段，是中国探索的一个新领域。本研究旨在开发一种计算机化的 ADE 报警和评估系统，帮助中国的药师有效检测、评估和分析患者中可能发生的 ADE。
根据这些药物不良事件的临床特征，我们设计了组合多参数作为 ADE 报警规则，组装成检测配置。我们还通过从解放军总医院信息系统（电子病历）中提取数据来开发系统功能模块。对报警的阳性预测值进行了计算。
该平台创建了五个功能模块：自动筛选、辅助评估、风险特征分析、生成 SRS（自发报告系统）报告和字典数据库。在我们的 ADE 报警和评估系统中设置了四个 ADE 报警配置：与药物相关的血小板减少症、贫血、肝损伤和肾损伤。4 种监测的 ADE 的阳性预测值约为 44.4%至 95.8%。
为中国医疗机构的住院患者建立了自动 ADE 筛选系统。与以往的研究相比，组合药物事件报警和系统辅助评估界面的性能优于仅基于实验室值的报警。此外，该平台的辅助分层评估和风险因素分析功能可以为专业人员节省大量时间，并提高对潜在严重 ADE 的早期预防。迄今为止，该系统已应用于 10 家大型医疗机构。
