2022
DOI: 10.3389/fpubh.2022.883551
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Evaluation of Laboratory Management Based on a Combination of TOPSIS and RSR Methods: A Study in 7 Provincial Laboratories of China

Abstract: In this study, a comprehensive evaluation of management for pathogenic microbiology laboratories is performed based on a combination of Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and Rank Sum Ratio (RSR) methods; in addition, the basis for improving laboratory management is provided. Using the laboratory evaluation tool developed by World Health Organization and a combination of TOPSIS and RSR methods, a system of evaluation indicators for the management of Chinese pathogenic mi… Show more

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Cited by 6 publications
(7 citation statements)
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“…The RSR method is a comprehensive evaluation method that constructs an n×m matrix, converts the evaluation indexes into rank to obtain the RSR value of dimensionless statistics, and ranks and grades the evaluation indexes based on the RSR value. 20 The steps of the calculation are the following: first, rank the RSR values from smallest to largest by C-value instead and calculate the downward cumulative frequency p value, and then convert the probability p value to probit value by referring to the ‘Comparison Table of Percentages and Probability Units’. Second, using the probit value as the independent variable and the C-value as the dependent variable, the regression equation, Y=a+bprobit, was established.…”
Section: Methodsmentioning
confidence: 99%
“…The RSR method is a comprehensive evaluation method that constructs an n×m matrix, converts the evaluation indexes into rank to obtain the RSR value of dimensionless statistics, and ranks and grades the evaluation indexes based on the RSR value. 20 The steps of the calculation are the following: first, rank the RSR values from smallest to largest by C-value instead and calculate the downward cumulative frequency p value, and then convert the probability p value to probit value by referring to the ‘Comparison Table of Percentages and Probability Units’. Second, using the probit value as the independent variable and the C-value as the dependent variable, the regression equation, Y=a+bprobit, was established.…”
Section: Methodsmentioning
confidence: 99%
“…The RSR method focuses on sorting while the TOPSIS method provides a grading perspective. This combined approach can identify and alleviate issues related to data dispersion and information loss [7]. The specific steps are as follows:…”
Section: Topsis-rmr Methodsmentioning
confidence: 99%
“…This approach aims to achieve a more comprehensive and nuanced understanding of the data, balancing the retention of the original data characteristics with the ability to effectively categorize the results. 23 Using the TOPSIS method, the optimal vector and the worst vector are solved based on a normalized matrix. The distance between the evaluation objects and the positive ideal solution and the negative ideal solution is calculated and ranking is done by calculating the relative proximity of each evaluation object to the positive ideal solution Ci value.…”
Section: Topsis and Rank Sum Ratio (Rsr) Methodsmentioning
confidence: 99%
“…The distance between the evaluation objects and the positive ideal solution and the negative ideal solution is calculated and ranking is done by calculating the relative proximity of each evaluation object to the positive ideal solution Ci value. 23 The following steps are taken: 24 1) Conduct homogenization processing to transform low-optimal and neutral indicators into high-optimal indicators.…”
Section: Topsis and Rank Sum Ratio (Rsr) Methodsmentioning
confidence: 99%