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An efficient method for kidney allocation problem: a credibility-based fuzzy common weights data envelopment analysis approach

机译:一种有效的肾分配方法:基于信誉的模糊普通权重数据包络分析方法

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Given the perennial imbalance and chronic scarcity between the demand for and supply of available organs, organ allocation is one of the most critical decisions in the management of organ transplantation networks. Organ allocation systems undergo rapid revisions for the sake of improved outcomes in terms of both equity and medical efficiency. This paper presents a Data Envelopment Analysis (DEA)-based model to evaluate the efficiency of possible patient-organ pairs for kidney allocation in order to enhance the fitness of organ allocation under inherent uncertainty in such problem. Eligible patient-kidney pairs are regarded as decision making units (DMUs) in a Credibility-based Fuzzy Common Weights DEA (CFCWDEA) approach and are ranked based on efficiency scores. Using a common set of weights for all DMUs ensures a high degree of fairness in the assessment and ranking of DMUs. The proposed model is also the first allocation method capable of coping with the vague and intervallic medical and nonmedical allocation factors by the aid of fuzzy programming. Verification and validation of the proposed approach are performed in two steps using a real case study from the Iranian kidney allocation system. First, the superiority of the proposed deterministic model in enhancing allocation outcomes is demonstrated and analyzed. Second, the applicability of the proposed fuzzy DEA method is demonstrated using a series of data realizations for different credibility levels.
机译:鉴于可用器官需求和供应之间的多年生不平衡和慢性稀缺,器官分配是器官移植网络管理中最关键的决策之一。器官分配系统为了股权和医疗效率而改善结果,经受快速修订。本文介绍了数据包络分析(DEA),基础模型,以评估肾脏分配可能的患者器官对的效率,以提高器官分配在此问题中固有的不确定性下的适应性。符合条件的患者 - 肾脏对被视为基于信誉基础的模糊普通重量DEA(CFCWDEA)方法的决策单位(DMU),并根据效率分数排列。所有DMUS使用一组常见的重量确保DMUS评估和排名中的高度公平性。所提出的模型也是能够通过模糊编程的帮助应对模糊和跨越医疗和非医疗分配因素的第一种分配方法。核查和验证所提出的方法是以伊朗肾分配系统的真正案例研究的两个步骤进行。首先,证实和分析了提高分配结果中提出的确定性模型的优越性。其次,使用针对不同可信度水平的一系列数据实现来证明所提出的模糊DEA方法的适用性。

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