CAJ | 학술논문

目的：开展重点品种重点事件的多中心主动监测研究，探讨军队医院开展ADE主动监测、自动警示与评估工作的特点、规律和相关因素，深化药品安全监测技术。方法：由经过集中培训的高年资临床药师，收集2014年1–6月期间5所扩大试点医院运行“住院患者药品不良事件主动监测与评估警示系统”的预警数据，逐例分析确定ADE阳性案例，统一汇总并分类统计。结果：四种ADE（肝功能异常、肾功能异常、贫血、血小板减少）自动监测结果的阳性预测值分别为（78.93±24.97）%、（46.45±32.81）%、（46.00±36.47）%、（41.27±31.14）%。由于案例排除率过高，未涵盖多数用药患者，相应的ADE发生率也高。研究者主动试行了22对拓展品种监测，主要为多个品种对1个ADE、也有1个品种对多个ADE，拓展品种的阳性预测值普遍高于常规品种。结论：该系统实现了“实时监测”和“预防为主”的药品风险控制模式；为大数据时代有效防范临床用药风险、减少ADE损害提供新的思路；为临床药师针对性开展重点品种主动监测提供高效实用的技术支撑工具。
목적：개전중점품충중점사건적다중심주동감측연구，탐토군대의원개전ADE주동감측、자동경시여평고공작적특점、규률화상관인소，심화약품안전감측기술。방법：유경과집중배훈적고년자림상약사，수집2014년1–6월기간5소확대시점의원운행“주원환자약품불량사건주동감측여평고경시계통”적예경수거，축례분석학정ADE양성안례，통일회총병분류통계。결과：사충ADE（간공능이상、신공능이상、빈혈、혈소판감소）자동감측결과적양성예측치분별위（78.93±24.97）%、（46.45±32.81）%、（46.00±36.47）%、（41.27±31.14）%。유우안례배제솔과고，미함개다수용약환자，상응적ADE발생솔야고。연구자주동시행료22대탁전품충감측，주요위다개품충대1개ADE、야유1개품충대다개ADE，탁전품충적양성예측치보편고우상규품충。결론：해계통실현료“실시감측”화“예방위주”적약품풍험공제모식；위대수거시대유효방범림상용약풍험、감소ADE손해제공신적사로；위림상약사침대성개전중점품충주동감측제공고효실용적기술지탱공구。
[ABSTRACT]Objective:Active monitoring of key categories of medicine and important event were conducted in multicenter military medical institutions. Characteristics of active monitoring, regularity and related factors about the ADE active monitoring were evaluated to improve technology for drug safety monitoring.Methods: The trained senior clinical pharmacists from ifve pilot hospitals collected the warning data through ADE active monitoring and assessment warning systems for hospitalized patients from January to June in 2014. ADE positive cases were analyzed, classiifed and summarized.Results: The active monitoring positive predictive values of the four ADEs (liver damage, kidney damage, anemia, thrombocytopenia) were (78.93 ± 24.97)%, (46.45 ± 32.81)%, (46.00 ± 36.47)%, (41.27 ± 31.14)%, respectively. Because the case ruled out rate was too high and could not cover the majority of patients with medication, the rate of ADE was correspondingly high. The researchers actively monitored twenty-two pairs of expand drugs, mainly multiple drugs correspond to the one ADE, and also the one drug corresponds to multiple ADEs. The result showed that positive predictive value of expand drugs was generally higher than that of conventional drugs.Conclusion:The system has realized the "real-time monitoring" and "prevention ifrst" drug risk control mode, which provides new methods for effective prevention of clinical medicine risk and reducing ADE damage in the age of big data. As a practical tool, this system can help clinical pharmacist to actively monitor key categories of medicine more efifciently.