Large Group Decision‐Making Approach Based on Stochastic MULTIMOORA: An Application of Doctor Evaluation in Healthcare Service

Abstract

Purpose. This paper presents a new method and model based on stochastic MULTIMOORA method and discuss its application to the doctor evaluation in healthcare service. Design/Methodology/Approach. In the previous studies, the number of decision group is often assumed to be small, and the different dimensions of the evaluation indexes were also less. In this paper, the authors study how to evaluate the healthcare service quality of doctors by the large group. Based on the stochastic MULTIMOORA theory, the authors use the method that builds the function of the net probability, the distance between the ideal solutions, and the utility of each doctor. Findings. This paper presents a novel model to determine the optimal doctor that considers both two dimensions in the index system and balances the evaluation results of the two dimensions. The authors designed the questionnaire and conducted field survey to make the proposed method closer to the actual situation in China. Then, they determined the optimal evaluation result for the healthcare service quality of doctors. Research Limitations/Implications. In the process of practical decision-making, there are differences in intellectual literacy level, regional background, and language preference between different decision-makers. it is impossible for the method we proposed to consider the differentiation index system of decision-makers’ preference comprehensively. And this will be a further research direction. Practical Implications. The authors proposed two evaluation index dimensions and tryed to balance the evaluation results of the two dimensions as much as possible. Meanwhile, the information aggregation method based on stochastic MULTIMOORA is distinguished. Social Implications. The proposed method can be applied to the evaluation of doctors in actual healthcare service. It is helpful to improve the healthcare service quality and the hospital management level, further improve the core competition of hospitals Originality/Value. This paper makes up for the lack of existing studies of the large group evaluation decision in the healthcare service. A new method on the evaluation of doctors by the large group is established and applied to a healthcare management decision-making problem with Chinese characteristics in reality.

LSGDM with Biogeography-Based Optimization (BBO) Model for Healthcare Applications

“…Later, a dynamic programming approach based on clustering models was presented for clustering the DM from an overall perspective. Gao et al [ 15 ] created a novel paradigm for selecting an appropriate physician in the index system that balances the 2D calculation result. The researchers created questionaries and conducted field research to bring the given technique closer to the actual situation in China.…”