An Integrated Fuzzy VIKOR Method for Performance Management in Healthcare

Author:

Shekarian Ehsan1,Abdul-Rashid Salwa Hanim1,Olugu Ezutah Udoncy2

Affiliation:

1. University of Malaya, Malaysia

2. UCSI University, Malaysia

Abstract

Poor quality control has become a major threat to medical laboratory services, especially in the developing countries. It has become necessary to assess and rank the quality of diagnostic services in medical laboratories using systematic approaches. The main aim of this research is to develop and apply a quantitative method in ranking medical laboratory services. This method is based on a combination of Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) with fuzzy set theory. VIKOR is a multiple criteria decision making technique which focuses on ranking and selection from a set of alternatives, and determines the compromise solution for a problem with different criteria. This approach aids decision makers to achieve the most acceptable decision amidst numerous alternatives. In the present evaluation method, international standard ISO 15189 (Medical Laboratories Particular Requirements for Quality and Competence) proposed by International Organization for Standardization (ISO) is used as a fundamental source of selected attributes of a medical laboratory. The study compares three medical laboratories to each other and ranks them. This study will be a valuable and effective contribution in enhancing both qualitative and quantitative criteria in the field of medical laboratory services. Finally, some directions for further studies are proposed.

Publisher

IGI Global

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A new fuzzy multi-criteria decision-making method based on proximity index value;Journal of Industrial and Production Engineering;2021-08-07

2. Designing a Model for Evaluating Iranian University Websites: Using Fuzzy VIKOR Approach;Iranian Journal of Information Processing and Management;2021-07-01

3. Development of FDEA Models to Measure the Performance Efficiencies of DMUs;International Journal of Fuzzy Systems;2017-05-10

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