Inpatient admission assessment in West China Hospital based on hesitant fuzzy linguistic VIKOR method

Classified diagnose and treatment (CDT) is a hot research topic in hospital management in China. As an essential way to implement CDT, the inpatient admission assessment involves different kinds of vague and uncertain information. The hesitant fuzzy linguistic term set provides a new technology to depict the vague and subjective evaluation information of the experts in hospital. In this paper, we apply the hesitant fuzzy linguistic VIKOR (HFL-VIKOR) method to the inpatient admission assessment process in which all the evaluation information over the patients are expressed as linguistic term sets or linguistic expressions. Firstly, the index of CDT (ICDT) of a patient is introduced to describe the degree to which the patient conforms to the classified diagnose and treatment principle. Based on these indices of different patients, the priorities of inpatient admission are assigned to the patients to ensure that the scarce medical resources be distributed to the most appropriate patients in the view of CDT. The numerical example in the West China Hospital reveals that the HFL-VIKOR method is a feasible and efficient methodology to solve the inpatient admission problem for the purpose of the classified diagnose and treatment.