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Research on Optimization of Pooling System and Its Application in Drug Supply Chain Based on Big Data Analysis

机译:大数据分析的共享系统优化及其在药品供应链中的应用研究

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摘要

Reform of drug procurement is being extensively implemented and expanded in China, especially in today's big data environment. However, the pattern of supply mode innovation lags behind procurement improvement. Problems in financial strain and supply break frequently occur, which affect the stability of drug supply. Drug Pooling System is proposed and applied in a few pilot cities to resolve these problems. From the perspective of supply chain, this study analyzes the process of setting important parameters and sets out the tasks of involved parties in a pooling system according to the issues identified in the pilot run. The approach is based on big data analysis and simulation using system dynamic theory and modeling of Vensim software to optimize system performance. This study proposes a theoretical framework to resolve problems and attempts to provide a valuable reference for future application of pooling systems.
机译:在中国,尤其是在当今的大数据环境中,药品采购的改革正在广泛实施和扩展。但是,供应方式创新的模式滞后于采购改进。经常出现财务紧张和供应中断的问题,这会影响药品供应的稳定性。为解决这些问题,提出并在一些试点城市中应用了药物共享系统。从供应链的角度,本研究分析了设置重要参数的过程,并根据试运行中发现的问题确定了集合系统中参与方的任务。该方法基于大数据分析和仿真,使用系统动力学理论和Vensim软件建模来优化系统性能。这项研究提出了一个解决问题的理论框架,并为池系统的未来应用提供了有价值的参考。

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