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| 论文编号: | 14988 | |
| 作者编号: | 2320224127 | |
| 上传时间: | 2024/12/8 23:17:57 | |
| 中文题目: | T市血液中心血液供应链管理优化研究 | |
| 英文题目: | Research on the Optimization of Blood Supply Chain Management at T City Blood Center | |
| 指导老师: | 梁峰 | |
| 中文关键字: | 供应链管理;需求预测;库存预警;血液调剂。 | |
| 英文关键字: | Supply Chain Management;Demand Forecasting; Inventory Alert; Blood Allocation. | |
| 中文摘要: | 血液是重要的医疗资源和战略物资,血液安全关系到人民健康、社会稳定和国家安全,是“健康中国”的重要工作内容。随着人口老龄化趋势的加剧,医学研究的深入和手术技术的革新,突发事件如自然灾害、战争等不可预测因素,这些对血液产品市场产生了深远的影响。血液产品的供应与调配能力直接考验着一个国家或地区的医疗应急体系。因此,提升血液产品的储备量和应急响应能力,成为各国政府和医疗机构共同面临的课题,也为血液产品市场带来了新的发展机遇与挑战。在国际医疗体系中,血液供应链的现代化构建与管理是确保血液安全、高效流动的关键环节。这一体系融合了最前沿的信息技术、严格的监管框架、高效的物流网络以及多元化的血液来源,共同织就了一张复杂而精细的生命保障网。 血液供应链管理研究的核心目的在于打造高效、精准且稳定的血液供应体系,以满足医疗机构日益增长的血液需求。本文以T市血液中心的背景、组织架构为基础,通过使用PEST分析法对血液中心所处的宏观环境进行了分析,并对2018-2022年T市血液中心的采供血相关数据进行统计分析,提出了T市血液中心当前血液供应链管理中存在的问题和亟待提高的部分,即临床供血相对紧张、库存调控能力不足、信息共享与协同程度低。针对存在的问题,提出了相应的优化策略和保障措施,形成了以血液需求预测-库存管理优化-供应链执行优化为一体的血液保障优化策略。 本文以基于ARIMA模型的血液需求预测为基础,制定了动态库存预警分级体系,并以此为指导在供应链执行层面通过相应的采血优化、临床供血优化和血液调剂机制优化等优化策略的构建,有效的保障了临床用血需求。经过一系列优化策略的实施,T市血液中心2023年全血采集量较2022年增加了20%,血液调剂平均响应时间明显缩短,血液调剂效率显著提高,有效的保障了临床用血需求,有力的推动了整个血液供应链向更高效、安全、可持续的方向发展。 | |
| 英文摘要: | Blood is an important medical resource and strategic material. Blood safety is related to people’s health, social stability, and national security, and is an important part of the “Healthy China” initiative. With the intensification of the aging population trend, in-depth medical research, and the innovation of surgical techniques, unpredictable factors such as natural disasters and wars have a profound impact on the blood product market. The supply and allocation capacity of blood products directly tests the medical emergency system of a country or region. Therefore, increasing the reserve of blood products and emergency response capabilities has become a common issue faced by governments and medical institutions around the world, and has also brought new development opportunities and challenges to the blood product market. In the international medical system, the modern construction and management of the blood supply chain is a key link to ensure the safety and efficient flow of blood. This system integrates the most advanced information technology, a strict regulatory framework, an efficient logistics network, and a diversified source of blood, together forming a complex and delicate life safety network. The core objective of blood supply chain management research is to create an efficient, accurate, and stable blood supply system to meet the increasing demand for blood from medical institutions. This thesis, based on the background and organizational structure of the T City Blood Center, uses the PEST analysis method to analyze the macro environment in which the blood center is situated. It also conducts a statistical analysis of the blood collection and supply-related data from 2018 to 2022 of the T City Blood Center. The paper identifies existing problems and areas for improvement in the current blood supply chain management of the T City Blood Center, namely, the relative tension in clinical blood supply, insufficient inventory control capabilities, and low levels of information sharing and collaboration. In response to these issues, corresponding optimization strategies and safeguard measures are proposed, forming an integrated blood security optimization strategy that encompasses blood demand forecasting, inventory management optimization, and supply chain execution optimization. This study, based on blood demand forecasting using the ARIMA model, has formulated a dynamic inventory warning grading system. Guided by this system, it has constructed optimization strategies at the supply chain execution level, including corresponding blood collection optimization, clinical blood supply optimization, and blood allocation mechanism optimization. These strategies have effectively ensured the clinical blood demand. After the implementation of a series of optimization strategies, the T City Blood Center saw a 20% increase in whole blood collection in 2023 compared to 2022. The average response time for blood allocation has been significantly reduced, and the efficiency of blood allocation has been markedly improved. This has better ensured the clinical blood demand and has strongly propelled the entire blood supply chain towards a more efficient, safe, and sustainable direction. | |
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