Evidence map›Paper›PMID 31492132›Full record

ArticleBMC medical informatics and decision making2019

Identification and weighting of kidney allocation criteria: a novel multi-expert fuzzy method.

Nasrin Taherkhani, Mohammad Mehdi Sepehri, Shadi Shafaghi, Toktam Khatibi

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Article in BMC medical informatics and decision making, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

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8citing papers in PubMed
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3 · Its place in the literature

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8 citing papers in PubMed.

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  8. Proposal for the elaboration of a triage guideline in the context of the COVID-19 pandemic.Revista de bioetica y derecho & perspectivas bioeticas · 2020
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5 · Who and what money

Authors and funding

4 authors.

Nasrin TaherkhaniGroup of Information Technology, Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, 1411713116, Iran.
Mohammad Mehdi SepehriFaculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, 1411713116, Iran. mehdi.sepehri@modares.ac.ir.ORCID 0000-0002-9920-7452
Shadi ShafaghiLung Transplantation Research Center, National Research Institute of Tuberculosis and Lung Diseases (NRITLDD), Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Toktam KhatibiFaculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, 1411713116, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundKidney allocation is a multi-criteria and complex decision-making problem, which should also consider ethical issues in addition to the medical aspects. Leading countries in this field use a point scoring system to allocate kidneys. Hence, the purpose of this study is to identify and weight the kidney allocation criteria considering the balance between utility and equity.

methodsTo do this, a new fuzzy hybrid approach is proposed, which consists of two steps: In the first step, Fuzzy Delphi Method (FDM) is used to identify the effective criteria in the kidney allocation algorithm. In the second step, Intuitionistic Fuzzy Analytic Hierarchy Process (IF-AHP) is employed to determine the weight of the criteria.

resultsThe results showed that the highest weight belongs to "Medical emergency" criterion and the lowest weight to "5 HLA mismatches", which is similar to Euro-transplant kidney allocation system (ETKAS). The developed method is evaluated in two steps. First, the proposed model is implemented using a real case study from the Iranian Kidney Allocation System. It was shown that the proposed model has the potential to improve allocation outcome. Second, the proposed model's superiority to the current model is approved by the experts using the results display in the profile matrix. Finally, sensitivity analysis is performed to check the robustness of the proposed model.

conclusionsThis paper contributes to the kidney allocation literature by doing the following: (a) developing a comprehensive framework for identification and weightings of criteria for kidney allocation, (b) using, for the first time, the IF-AHP technique to consider hesitancy of decision makers and uncertainty in organ allocation, and (c) proposing an appropriate framework for the countries that intend to improve or modify their organ allocation system.

Indexed as

Fuzzy LogicKidney TransplantationPatient SelectionResource AllocationAlgorithmsDecision MakingHumansIranTissue and Organ ProcurementUncertaintyFuzzy Delphi methodIntuitionistic fuzzy AHPKidney allocationKidney allocation criteria

Identifiers

PMID31492132
PMCPMC6729045

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