Page 118 - 《中国药房》2026年5期

·智慧药学·

基于数智驱动的中药房调剂取药流程优化研究
Δ

＊
王 琦 ，曾攀科，宋昊昕，冯永刚，孙丽丽，冯靖婷，牛蔚青，董海燕，王 丰（西安交通大学第一附属医院药学
#
部，西安 710061）

中图分类号 R952 文献标志码 A 文章编号 1001-0408（2026）05-0660-05
DOI 10.6039/j.issn.1001-0408.2026.05.19

摘 要 目的 基于数智驱动对我院中药房调剂取药流程进行改造，以提升药师工作效率与患者取药体验。方法 运用价值流程
图和旅程映射图，系统识别传统流程中药师调剂的非增值环节及患者取药的关键痛点；基于C#和Android电视平台开发中药房智
能调剂取药系统，并采用机器学习模型预测患者取药等待时间，从系统性能、预测准确性及药师、患者满意度3个维度开展综合评
价。结果 该系统成功精简“待取写板”和“翻找药品”的非增值环节，实现调剂状态听觉（叫号）与视觉（电视端）的多模动态提示；
所构建的取药等待时间预测模型拟合度与泛化性能良好（平均绝对误差为4.28 min，决定系数为0.882）；药师与患者综合满意度分
别由传统模式的（70.99±1.74）分和（73.58±1.98）分显著提升至新建系统的（90.02±1.30）和（88.61±2.08）分（P＜0.01）。结论 基
于数智驱动改造的中药房智能调剂取药系统，有效提高了药师调剂工作效率，实现了流程透明化与等待时间可预测化，显著改善
了患者取药体验。
关键词 中药房；智能调剂取药系统；数智驱动；工作效率；取药等待时间预测；满意度

Optimization of drug dispensing and pickup process in traditional Chinese medicine pharmacy based on
data-intelligence-driven
WANG Qi，ZENG Panke，SONG Haoxin，FENG Yonggang，SUN Lili，FENG Jingting，NIU Weiqing，DONG
Haiyan，WANG Feng（Dept. of Pharmacy， the First Affiliated Hospital of Xi’an Jiaotong University， Xi’an
710061， China）

ABSTRACT OBJECTIVE To explore the transformation of the dispensing and drug pickup process in traditional Chinese
medicine pharmacy （TCM Pharmacy） in our hospital based on data-intelligence-driven， aiming to improve pharmacists’ work
efficiency and patients’ drug pickup experience. METHODS Value stream mapping and journey mapping were used to
systematically identify non-value-added links in pharmacists’ dispensing process and key pain points in patients’ drug pickup under
the traditional process. An intelligent dispensing and drug pickup system for the TCM Pharmacy was developed based on the C# and
Android television platforms， and a machine-learning model was adopted to predict patients’ drug pickup waiting time. A
comprehensive evaluation was performed from three perspectives： system performance， prediction accuracy， and satisfaction of
pharmacists and patients. RESULTS The system successfully streamlined non-value-added links such as “waiting for writing on the
board” and “searching for drugs”， and realized multimodal dynamic prompts of dispensing status through auditory （number calling）
and visual （television terminal） channels. The constructed model for predicting drug pickup waiting time exhibited good fitting
degree and generalization ability （mean absolute error＝4.28 min， R ＝0.882）. The comprehensive satisfaction scores of pharmacists
2
and patients in the traditional mode were significantly increased from （70.99±1.74） and （73.58±1.98） to （90.02±1.30） and
（88.61±2.08） in the new system， respectively （P＜0.01）. CONCLUSIONS The transformation of the intelligent drug dispensing
and pickup system for TCM pharmacy based on data-intelligence-driven effectively improves the efficiency of pharmacists’
dispensing work， realizes process transparency and waiting time predictability， and significantly enhances patients’ drug pickup
experience.
KEYWORDS traditional Chinese medicine pharmacy； intelligent dispensing and drug pickup system； data-intelligence-driven；
work efficiency； waiting time prediction of drug pickup；
Δ 基金项目 国家卫生健康委医院管理研究所医院药学高质量发
satisfaction
展研究项目（No.NIHAYSZX2537）；西安交通大学第一附属医院基金
项目（No.2024-RK-1）
＊第一作者 药师，硕士。研究方向：医院药学和药学信息化。电
在中医药现代化进程中，中药房作为医疗服务体系
话：029-85324174。E-mail：1152169315@qq.com
的关键终端，其发展长期面临着调剂流程碎片化与取药
# 通信作者 主管药师。研究方向：医院药学和药学信息化。电
[1]
话：029-85324174。E-mail：wangfeng7927@126.com 体验滞后性的双重结构性矛盾 。传统法药师调剂依赖

· 660 · China Pharmacy 2026 Vol. 37 No. 5 中国药房 2026年第37卷第5期