Page 14 - 《中国药房》2024年19期

基于统计过程控制的药品用量动态监测研究
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陈 杨 ，淡重辉，徐美玲，陈 肖，刘 颖，郑晓媛（重庆市急救医疗中心药剂科，重庆 400014）
中图分类号 R952 文献标志码 A 文章编号 1001-0408（2024）19-2328-07
DOI 10.6039/j.issn.1001-0408.2024.19.02

摘 要 目的 探索基于统计过程控制（SPC）的药品用量动态监测方法，以提升药品使用过程的宏观监管水平。方法 根据药
品费用和国家相关文件建立我院重点监控药品品种目录。以全院、门诊药房和住院药房的重点监控药品品种月度用量数据为
监测对象，利用 SPC 的 X 控制图、移动极差控制图和指数加权移动平均值控制图建立药品用量动态监测（DMDC）模型，分别从
单月用量、极差变化以及用量趋势 3 个维度进行监测。以瑞舒伐他汀、美托洛尔和美罗培南为例，展示 DMDC 模型的监测效
果。结果 针对全院、门诊药房和住院药房分别建立了包含 203、167 和 200 个品种的重点监控药品目录。在排除无法建模及建
模失败的品种后，成功为这 3 个药品消耗区域分别建立了 179、116 和 172 个 DMDC 模型。这 3 组模型在 2024 年前 4 个月的实
践中，警示的药品品种数分别为 54、32、62 个。所建 DMDC 模型成功监测了全院瑞舒伐他汀、门诊药房美托洛尔以及住院药房
美罗培南等药品的月度用量。相较于我院原用的浮动率排序法，DMDC 模型的应用显著提升了药品监测的范围和深度，监测
品种由原先的约 50 种大幅扩展至 179 种，监测维度也从 1 个维度增加到了 3 个维度。结论 基于 SPC 的 DMDC 模型有效、可行，
适用于对月度用量较稳定的药品品种进行监测。
关键词 药品用量；药品动态监测；统计过程控制

Research on dynamic monitoring of drug consumption based on statistical process control
CHEN Yang，DAN Chonghui，XU Meiling，CHEN Xiao，LIU Ying，ZHENG Xiaoyuan（Dept. of Pharmacy，
Chongqing Emergency Medical Center， Chongqing 400014， China）

ABSTRACT OBJECTIVE To investigate a method for dynamic monitoring of drug consumption （DMDC） based on statistical
process control （SPC）， aiming to improve the macro-supervisory capacity in the process of drug utilization. METHODS The lists
of key monitoring drug varieties in our hospital were established based on drug cost and relevant national documents. Monthly
consumption data of key monitoring drug varieties in the entire hospital， outpatient pharmacy and inpatient pharmacy were taken as
monitoring objects，and the DMDC model was established using SPC’s X control chart， moving range control chart， and
exponentially weighted moving-average control chart， monitoring from three dimensions： single-month consumption， range
variation， and consumption trend. Rosuvastatin， metoprolol and meropenem were taken as examples to demonstrate the monitoring
capabilities of the DMDC model. RESULTS Lists of key monitoring drug varieties were established for entire hospital， outpatient
pharmacy and inpatient pharmacy， containing 203， 167 and 200 varieties， respectively. After excluding drug varieties that could not
be modeled and for which modeling failed， 179， 116 and 172 DMDC models were successfully established for these three drug
consumption areas， respectively. During the first four months of 2024， these three groups of model separately warned 54， 32 and
62 drug varieties. The DMDC model successfully monitored the monthly consumption of drugs，such as rosuvastatin throughout the
hospital， metoprolol in outpatient pharmacy， and meropenem in inpatient pharmacy. Compared with the previously used floating
rate ranking method in our hospital， the application of the DMDC model significantly improved the scope and depth of drug
monitoring， with the monitored drug varieties greatly expanded from about 50 to 179， and the monitoring dimensions increased
from a single dimension to three. CONCLUSIONS The DMDC model based on SPC is effective and feasible，suitable for
monitoring drug varieties with stable monthly consumption.
KEYWORDS drug consumption； drug dynamic monitoring； statistical process control

近年来，随着医疗行业的迅猛发展和药物种类的急 健全药品供应保障的重要环节。目前，可行的药品动态
剧增加，医院药品动态监测已成为确保药品合理使用和 监测方法包括浮动率排序法 、PDCA（Plan-Do-Check-
[1]
[2]
[3]
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Δ 基金项目 重庆市卫生健康委医学科研项目（No.2024WSJK030） Act）循环法 、金额排序法 和曲线法 等。这些传统监
＊第一作者 主管药师，硕士。研究方向：医院药学、化学计量学。 测方法虽然操作简便，但同时也存在工作量大以及监测
E-mail：yangchen8786@sina.com
效果欠佳等缺点。利用上述方法难以实现医院药品的
# 通信作者 主任药师，硕士。研究方向：药理学、医院药学。
[5]
E-mail：thymolblue@163.com 精细化管理 ，更无法满足医院智能化发展的需求。
· 2328 · China Pharmacy 2024 Vol. 35 No. 19 中国药房 2024年第35卷第19期