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医疗机构制剂供应链精细化智能管理平台的构建与应用
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| 篇名： | 医疗机构制剂供应链精细化智能管理平台的构建与应用 |
| TITLE： | Construction and application of a refined intelligent management platform for the supply chain of hospital preparations |
| 摘要： | 目的 构建医疗机构制剂供应链精细化智能管理平台，并评价其实施效果。方法通过机器学习和经典时序模型对医疗机构制剂需求进行预测；基于预测结果，围绕医疗机构制剂供应链各环节构建包含智能辅助决策、日常效期监控、智能推送和持续改进3个功能模块的智能管理平台。通过对比苏州大学附属第一医院应用该平台前后的各制剂平均库存周转天数的均值、月均过期报废金额、临床平均满意度等指标，分别从成本控制、运营效率及药事服务质量3个维度评价应用效果。结果所建智能管理平台能自动生成库存动态分级预警、生产计划建议、物料采购建议及效期预警，并智能推送至相关责任人。与应用前比较，成本控制方面，各制剂平均库存周转天数的均值从64.1d缩短至48.4d，月均过期报废金额从1973元减少至1369元；运营效率方面，生产计划制定平均耗时从120min缩短至60min，效期预警信息平均滞后天数从15d缩短至0.5d；药事服务质量方面，临床平均满意度从85.4%提升至94.6%。结论成功构建了医疗机构制剂供应链精细化智能管理平台，可辅助管理人员进行生产计划制定、采购、近效期制剂和物料处置等决策，达到降本增效的目的。 |
| ABSTRACT： | OBJECTIVE To construct a refined intelligent management platform for the supply chain of hospital preparations and to evaluate its implementation effectiveness.METHODS Machine learning and classical time series model were used to predict the demand for hospital preparations. Based on the prediction results， an intelligent management platform was constructed around each link of the supply chain of hospital preparations， which included three functional modules： intelligent auxiliary decision-making， daily expiry date monitoring， and intelligent push and continuous improvement. By comparing indicators such as the mean of average inventory turnover days of each preparation， average monthly expired and scrapped amount， and average clinical satisfaction before and after the application of the platform in the First Affiliated Hospital of Soochow University， the application effectiveness was evaluated from three dimensions: cost control， operational efficiency， and pharmaceutical care service quality.RESULTS The constructed intelligent management platform could automatically generate dynamic inventory grading alerts， production plan suggestions， material procurement suggestions， and expiry date alerts， and intelligently push them to relevant responsible persons. Compared with before the application， in terms of cost control， the mean of average inventory turnover days of each preparation was shortened from 64.1 days to 48.4 days， and the average monthly expired and scrapped amount was reduced from 1 973 yuan to 1 369 yuan； in terms of operational efficiency， the average time for production plan formulation was shortened from 120 min to 60 min， and the average lag days of expiry date alert information was shortened from 15 days to 0.5 days； in terms of pharmaceutical care service quality， the average clinical satisfaction increased from 85.4% to 94.6%.CONCLUSIONS The refined intelligent management platform for the supply chain of hospital preparations has been successfully constructed， which can assist managers in decision-making regarding production plan formulation， procurement， and disposal of near-expiry preparations and materials， thereby achieving the purpose of cost reduction and efficiency improvement. |
| 期刊： | 2026年第37卷第17期 |
| 作者： | 柴煜莹；吴憩；陶香；张春歌 |
| AUTHORS： | CHAI Yuying，WU Qi，TAO Xiang，ZHANG Chunge |
| 关键字： | 医疗机构制剂；需求预测；库存预警；效期预警；智能管理；机器学习；经典时序模型 |
| KEYWORDS： | demand forecasting;inventory alert;expiry date alert;intelligent management;machine learning;classical time series model |
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