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·智慧药学·
基于季节性Mann-Kendall趋势检验的药品用量动态监测研究 Δ
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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）
中图分类号 R952 文献标志码 A 文章编号 1001-0408（2026）03-0377-06
DOI 10.6039/j.issn.1001-0408.2026.03.18
摘 要 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%）（χ ＝20.114，P＜0.001；χ ＝19.600，P＜0.001）。结论 基
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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。
关键词 药品用量；动态监测；季节性Mann-Kendall趋势检验；季节性波动
Research on dynamic monitoring of drug consumption based on seasonal Mann-Kendall trend test
YU Ziheng，CHEN Chen，YANG Xiangyu，LI Lulu，ZHANG Shaohui（Dept. of Pharmacy， Wuhan No. 1
Hospital， Wuhan 430022， China）
ABSTRACT 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） （χ ＝20.114， P＜0.001； χ ＝19.600， P＜0.001）. CONCLUSIONS DMDC model based on the seasonal
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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.
KEYWORDS drug consumption； dynamic monitoring； seasonal Mann-Kendall trend test； seasonal fluctuations
随着门诊统筹和医疗大数据的发展，医院药品使用
Δ 基金项目 武汉市卫生健康委课题（No.S202406050039） 动态监测与预警已经成为医院药事管理的重要组成部
＊第一作者 中药师，硕士。研究方向：医院药学、天然药物化学。 分，其在保障药品合理使用、健全药品供应等环节上为
E-mail：yuziheng0728@163.com
[1]
患者健康权益提供支撑 。国家卫生健康委在《关于开
# 通信作者 副主任药师，博士。研究方向：临床药学、医院药学。
E-mail：zshtjmu@hotmail.com 展药品使用监测与临床综合评价工作的通知》中指明了
中国药房 2026年第37卷第3期 China Pharmacy 2026 Vol. 37 No. 3 · 377 ·
