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Application of the DRGs and the Fuzzy Demand in the Medical Service Resource Allocation Based on the Data Mining Algorithm

Fanxiu Dong*

Xinjiang Medical University, Xinjiang 830000, China
Address: Medical Record Management Office, Xinjiang Uygur Municipality People’s Hospital, 91 Tianchi Road, Tianshan District, Urumqi, Xinjiang, 830001

* Corresponding Author: Fanxiu Dong, email

Intelligent Automation & Soft Computing 2020, 26(3), 617-624. https://doi.org/10.32604/iasc.2020.013940

Abstract

At present, the allocation of the medical service resources is directed at a single service resource, and there are many unreasonable problems, which causes medical cost to be high. Based on this, the application of the DRGs and the fuzzy demand in the medical service resource allocation based on the data mining algorithm is proposed. The application research of the DRGs and the data mining algorithm is simply analyzed, then the uncertain demand estimation is applied to the fuzzy demand processing based on the fuzzy demand theory and the medical service resources are configured under the established demand satisfaction rate. Through the example analysis, it is proven that the proposed algorithm has higher reliability, and the optimal allocation of resources can greatly reduce the total medical cost and confirm the feasibility of the resource optimization.

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APA Style
Dong, F. (2020). Application of the drgs and the fuzzy demand in the medical service resource allocation based on the data mining algorithm. Intelligent Automation & Soft Computing, 26(3), 617-624. https://doi.org/10.32604/iasc.2020.013940
Vancouver Style
Dong F. Application of the drgs and the fuzzy demand in the medical service resource allocation based on the data mining algorithm. Intell Automat Soft Comput . 2020;26(3):617-624 https://doi.org/10.32604/iasc.2020.013940
IEEE Style
F. Dong, “Application of the DRGs and the Fuzzy Demand in the Medical Service Resource Allocation Based on the Data Mining Algorithm,” Intell. Automat. Soft Comput. , vol. 26, no. 3, pp. 617-624, 2020. https://doi.org/10.32604/iasc.2020.013940

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cc Copyright © 2020 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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