基于贝叶斯网络的高货值药品冷链物流风险评估
The Risk Assessment for High-Value Pharmaceutical Cold Chain Logistics Based on Bayesian Network

高货值药品由于商业价值高、敏感性高的特点，物流中的各个环节都受到了政府与企业的严密管制。如何将高货值药品安全、高效、快速地传递给客户是亟待解决的重要问题。首先深入剖析国药冷链物流中高货值药品的入库、储存、出库、运输环节，识别出国药高货值药品在冷链物流中可能存在的各种风险因素；然后构建贝叶斯网络模型，通过逆向推理、敏感性分析、影响强度分析等方法，实现对国药高货值药品冷链物流过程中各环节风险的有效控制。研究发现，在运输设备故障、冷藏设备检查、订单复核和温控包装等环节中，存在着比较高的风险。针对上述问题，提出了以下对策：重视对生产源头的审查、加强入库环节的验收程序、保障冷链药品的存储和养护、监控冷链药品出库情况，从而降低其发生的风险。
Due to their high commercial value and sensitivity, all logistics links of high-value pharmaceuticals are strictly controlled by both governments and enterprises. How to deliver high-value pharmaceuticals safely, efficiently, and rapidly to customers is an important issue that needs to be resolved urgently. Firstly, this paper conducts an in-depth analysis of the warehousing, storage, outbound, and transportation links of high-value pharmaceuticals in the cold chain logistics of a state-owned pharmaceutical company and identifies various potential risk factors in these links. Then, a Bayesian network model is constructed to effectively control the risks in each link of the cold chain logistics process for high-value pharmaceuticals through methods such as backward reasoning, sensitivity analysis, and impact intensity analysis. The study found that there are relatively high risks in links such as transportation equipment failure, refrigeration equipment inspection, order verification, and temperature-controlled packaging. In response to the above problems, the following countermeasures are proposed: attaching importance to the audit of production sources, strengthening the acceptance procedures in the warehousing link, ensuring the storage and maintenance of cold chain pharmaceuticals, and monitoring the outbound situation of cold chain pharmaceuticals, thereby reducing the risks involved.