DRG-Oriented Mathematical Calculation Model and Method of Integrated Medical Service Cost

Sun, Xiaowei and Zhu, Yi and Jiang, Yi-Zhang (2020) DRG-Oriented Mathematical Calculation Model and Method of Integrated Medical Service Cost. Computational and Mathematical Methods in Medicine, 2020. pp. 1-9. ISSN 1748-670X

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Abstract

In the context of the new round of medical and health reform, in order to alleviate the problem of “difficult to see a doctor and expensive to see a doctor,” the state focuses on reducing the cost of medical services, so it puts forward the calculation and method research of medical costs. The purpose of this study is to calculate and predict the cost of medical services in a DRG-oriented integrated environment. In this study, activity-based costing and weighted moving average methods are used. First, basic data of medical services are collected, then all medical activities are confirmed and all service costs are collected, then a cost database is established, and a calculation model of medical costs is designed. Finally, calculation suggestions and optimization methods are put forward by analyzing the calculated data. The experimental results show that the actual demand of drugs predicted by the general moving average method is relatively insufficient, with the maximum error of 41%, the minimum of 5%, and the average error of 19.8%; the maximum error of drug demand predicted by the weighted moving average method is 24%, the minimum is 2%, and the average is 15.4%. It can be concluded that the prediction effect of the weighted moving average method is better than that of the ordinary moving average method, which plays a good and effective role in the prediction of medical cost. The activity-based costing method is more detailed and organized for the cost calculation and classification of medical services. It provides a certain value for the effective management and control of medical service cost.

Item Type: Article
Subjects: Institute Archives > Medical Science
Depositing User: Managing Editor
Date Deposited: 22 Mar 2023 04:59
Last Modified: 26 Jun 2024 06:29
URI: http://eprint.subtopublish.com/id/eprint/1217

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