Design of Medical Insurance Fund Audit Platform Based on Big Data Analysis
- DOI
- 10.2991/978-94-6463-262-0_97How to use a DOI?
- Keywords
- Medical Insurance Fund Audit; Big Data Analysis; Distributed Storage; Audit Platform
- Abstract
The medical insurance fund is an important guarantee for people's health. It is of great significance for the country to maintain the people's livelihood by timely discovering illegal acts and avoiding fund losses. Due to the characteristics of high dimension, large quantity and complex data type of medical insurance data, traditional audit methods have been unable to be fully applicable. Therefore, aiming at the massive medical insurance data, this paper takes the HDFS distributed storage system based on Hadoop as the basic system architecture, makes full use of the data analysis method in big data processing, designs and develops the medical insurance fund audit platform for the majority of medical insurance audit professionals, with a clear and friendly analysis process. This program can help to improve the accuracy and efficiency of medical insurance fund audit work, accelerate the transformation of results of big data analysis technology, and promote Chinese progress of medical insurance fund audit work.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Xiaolan ZHANG PY - 2023 DA - 2023/10/09 TI - Design of Medical Insurance Fund Audit Platform Based on Big Data Analysis BT - Proceedings of the 3rd International Conference on Management Science and Software Engineering (ICMSSE 2023) PB - Atlantis Press SP - 940 EP - 949 SN - 2589-4943 UR - https://doi.org/10.2991/978-94-6463-262-0_97 DO - 10.2991/978-94-6463-262-0_97 ID - ZHANG2023 ER -