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Stable Two-Sided Satisfied Matching for Hospitals and Patients Based on the Disappointment Theory
International Journal of Computational Intelligence Systems ; 15(1), 2022.
Article in English | EuropePMC | ID: covidwho-2034498
ABSTRACT
With the global spread of COVID-19 and the shortage of medical resources, the key to improve the quality of medical services is to solve the problem of hospitalpatient matching. This paper constructs a two-sided matching (TSM) model based on the psychological perceptions of hospitals and patients to realize effective matching that maximizes the satisfaction of hospitals and patients. First, we determine the influencing factors of mutual choice between hospitals and patients through investigation and literature and establish a TSM evaluation system to obtain the preference order of hospitals and patients. Then, using disappointment theory, the preference order value is transformed into preference utility, and the preference utility of hospitals and patients is transformed into the perceived utility of hospital and patient satisfaction. Finally, under the constraint of stable matching, a multiobjective optimization model of TSM is established with the goal of maximizing the sum of the perceived utility of hospitals and patients. The optimal TSM results are obtained by solving the model, and an example is given to verify the practicability and effectiveness of the model. The results show that the stable bilateral satisfaction matching model considering the psychological factors of both sides can fully meet the expectations of hospitals and patients and has certain practical value.
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Collection: Databases of international organizations Database: EuropePMC Language: English Journal: International Journal of Computational Intelligence Systems Year: 2022 Document Type: Article

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Collection: Databases of international organizations Database: EuropePMC Language: English Journal: International Journal of Computational Intelligence Systems Year: 2022 Document Type: Article