基于成本分析的四川省血液集中化检测的研究

A study of centralized blood testing in Sichuan province based on cost analysis

目的随着输血技术的进步和发展,我国采供血机构存在血液检测模式比较分散,效率低,成本高的问题。集中化检测模式不仅能有效提高血液检测质量,还能从人工、设备等各方面节约成本。因此,本文依据四川省血液检测相关数据,综合考虑了血液检测的运输成本、检测成本和中心运营成本,研究了血液检测的最小成本模型。方法以血液检测年成本为目标函数,以标本处理能力、标本分配、运输和中心建设的逻辑关系、运输决策与运输量的一致性为约束条件建立混合整数规划模型。以四川省为例进行实证分析,通过访谈及调研形式收集数据,为满足模型需求对分段式数据做线性处理及调整,通过python编码及优化库进行模型运算并验证最优方案。结果建立了适合我国的集中检测实验室数量和选址的混合整数规划模型。在四川省的实证分析中,收集到模型所需数据,并对分段式数据做了线性处理。本研究通过详细的成本分析计算得出,最经济的方案为:以成都和遂宁为基点建立集中检测实验室;最不经济的方案为21个血站独立检测。与最不经济方案比较,最经济方案可节省29.433%的成本。为确保该结果的可靠性,我们对上述结果执行了多轮验证,进一步的分析揭示,相较于最优解,在成都和巴中构建检测中心的方案为次优选择,与最不经济方案比较,该方案可节省29.431%的成本。结论本文构建了集中检测实验室数量和选址的混合整数规划模型,首次从成本角度,为我国区域化血液集中检测的选址问题提供了决策依据,并对四川省进行了实证分析,求解了成本最低方案。

Objective With the development of blood transfusion technology,the blood testing model is relatively decentralized,inefficient and costly in blood stations in China.Blood centralized detection not only effectively improves the quality of blood testing,but is also more cost-effective in labor and equipment.The purpose of this paper is to create a minimum cost model for blood testing that integrates the transportation cost,testing cost and center operating cost.Methods A mixed-integer planning model was developed with the annual cost of blood testing as the objective function,and sample processing capacity,sample allocation,logistic relationship between transportation and center construction,and consistency of transportation decisions with transportation volume as constraints.The empirical analysis takes Sichuan province as an example,collects data through expert interviews and research,does linear processing and adjustments to the segmented data to meet the modeling needs,and carries out modeling operations and verifies the optimal solution through python coding.Results A mixed integer programming model suitable for the number and location of centralized testing laboratories in China was developed.In the empirical analysis of Sichuan,the data required for the model was collected and the segmented data was linearized.A detailed cost analysis was conducted,revealing that the most cost-effective option was to establish centralized testing laboratories in Chengdu and Suining.The least cost-effective option identified in this study involved independent testing at 21 blood stations.Compared to this baseline,the most cost-effective strategy(establishing centralized testing laboratories in Chengdu and Suining)can reduce expenses by 29.433%.To ensure the reliability of these results,multiple rounds of validation were performed.Further analysis revealed that the strategy of establishing testing centers in Chengdu and Bazhong was a suboptimal choice,which can achieve a cost reduction of 29.431%.Conclusion This paper constructs a mixed-integer planning model for the number and location of centralized testing laboratories,which for the first time provides a decision-making basis for the location of regional centralized blood testing in China from the perspective of cost,and carries out an empirical analysis of Sichuan to develop the most cost-effective option.