Abstract
With the number of patients with chronic diseases increasing, a hierarchical diagnosis and treatment system is a feature of long-term treatment. During the treatment, if patients with chronic diseases are relieved, they can be referred to community hospitals for rehabilitation treatment, and to promote the rational allocation of hospital medical resources. Therefore, hospitals need referral standards to encourage patients to refer down. Existing ranking research which is mainly based on referral criteria,has not considered the low reliability due to different opinions within each group when making referral standard. In view of this, we propose a probabilistic linguistic-multiple criteria decision-making (PL-MCDM) method based on the decision-making reliability of multi-group for patients with chronic diseases requiring downward referral. First, the decision information of different groups on referral criteria is expressed as probabilistic linguistic preferences, and then the reliability levels of groups are measured when setting standards respectively. After that, the decision information and referral standards are re-adjusted for the least reliable group to improve the whole reliability. Secondly, the patients requiring downward referral are ranked by the similarity measure based on statistics of probability preference to acquire the formal referral standards. Finally, compared with the methods without reliability improvement, the real case of coronary heart disease in First Hospital of Qinhuangdao is used to verify the effectiveness of the proposed method, which illustrates its superiority.




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Acknowledgements
The work presented in this paper is supported by the National Natural Science Foundation of China (No. 71701037, 71971051), Fundamental Research Funds for the Central Universities (N2123020), and Youth Top-notch Talent Support Program of Hebei province (No. BJ2020211).
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Zhao, M., Wang, X., Xu, Z. et al. A PL-MCDM Method based on the Decision-Making Reliability of Multi-Group for Patients with Chronic Diseases Requiring Downward Referral. Appl Intell 52, 2655–2670 (2022). https://doi.org/10.1007/s10489-021-02436-w
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DOI: https://doi.org/10.1007/s10489-021-02436-w