基于季节性Mann-Kendall趋势检验的药品用量动态监测研究OA
Research on dynamic monitoring of drug consumption based on seasonal Mann-Kendall trend test
目的 探索构建基于季节性Mann-Kendall趋势检验的药品用量动态监测(DMDC)模型,为高效、宏观地监测药品使用提供科学依据.方法 基于2024年10月门诊药房销售额排名前20%的药品建立门诊重点药物监控目录.以门诊重点药物2021年11月-2024年10月的月度用量数据建立Mann-Kendall趋势检验的DMDC模型,消除季节性波动的影响,分析药品用量随时间的变化趋势.以黏液溶解性祛痰药、皮肤真菌病用三唑类衍生物、单方羟甲基戊二酸单酰辅酶A(HMG-CoA)还原酶抑制剂为例,展示DMDC模型的监测效果,并与传统的环比增长率排序法的监测效能进行比较.结果 门诊重点药物监控目录共纳入215个品种,其均成功建立DMDC模型.其中,具有显著上升趋势的品种119个(P＜0.05,S'＞0).所建模型成功监测了黏液溶解性祛痰药、皮肤真菌病用三唑类衍生物、单方HMG-CoA还原酶抑制剂等药品的月度用量.DMDC模型识别潜在异动药品的精确率和召回率分别为60.7%、85.0%,均显著高于环比增长率排序法(8.3%、15.0%)(χ2=20.114,P＜0.001;χ2=19.600,P＜0.001).结论 基于季节性Mann-Kendall趋势检验的DMDC模型能够有效识别药品用量的长期趋势,排除季节性干扰,提升监测精准性与管理效率,适用于对药品用量进行动态监测.
OBJECTIVE To investigate a dynamic monitoring of drug consumption(DMDC)model based on the seasonal Mann-Kendall trend test,aiming to provide scientific evidence for the efficient and macroscopic monitoring of drug use.METHODS A monitoring list of key outpatient drugs was established based on the top 20%of drugs ranked by sales volume in the outpatient pharmacy in October 2024.A DMDC model based on the Mann-Kendall trend test was constructed using the monthly usage data of key outpatient drugs from November 2021 to October 2024,aiming to eliminate the impact of seasonal fluctuations and analyze the temporal trends in drug consumption.Taking mucolytic expectorants,triazole derivatives for dermatophytosis,and single-agent hydroxymethylglutaryl coenzyme A(HMG-CoA)reductase inhibitors as examples,the monitoring effectiveness of the DMDC model was demonstrated,and its performance was compared with that achieved by the traditional sequential growth rate ranking method.RESULTS A total of 215 drug varieties were included in the monitoring list,and DMDC models were successfully established for all of them.Among these,119 showed a significant increasing trend(P＜0.05,S'＞0).The model successfully monitored the monthly consumption of mucolytic expectorants,triazole derivatives for dermatophytosis,and single-agent HMG-CoA reductase inhibitors.The precision and recall rates of the DMDC model for identifying abnormal drug use were 60.7%and 85.0%,respectively,both significantly higher than those of the sequential growth rate ranking method(8.3%and 15.0%,respectively)(χ2=20.114,P＜0.001;χ2=19.600,P＜0.001).CONCLUSIONS DMDC model based on the seasonal Mann-Kendall trend test can effectively identify long-term trends in drug consumption,eliminate seasonal interference,enhance monitoring accuracy and management efficiency,and is suitable for the dynamic monitoring of drug consumption.
余子珩;陈辰;杨香瑜;李璐璐;张韶辉
武汉市第一医院药学部,武汉 430022武汉市第一医院药学部,武汉 430022武汉市第一医院药学部,武汉 430022武汉市第一医院药学部,武汉 430022武汉市第一医院药学部,武汉 430022
医药卫生
药品用量动态监测季节性Mann-Kendall趋势检验季节性波动
drug consumptiondynamic monitoringseasonal Mann-Kendall trend testseasonal fluctuations
《中国药房》 2026 (3)
377-382,6
武汉市卫生健康委课题(No.S202406050039)
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