MedicareVis: a Joint Visual Analytics Approach for Anti-Fraud in Medical Insurance

Q3 Computer Science
Jiehui Zhou, Rongchen Zhu, Wei Zhang, Junhua Lu, Haochao Ying, Jian Wu, Wei Chen
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引用次数: 1

Abstract

Medical insurance fraud causes serious economic losses, which has a great impact on the safety and stability of the medical insurance system. However, existing work does not support the joint analysis and exploration of various types of fraud. Based on the medical insurance data related to multi-dimensional time series, a visual analytics approach for anti-fraud in medical insurance is proposed. It can perform spatio-temporal filtering of medical insurance data, locate fraud quickly, and discover hidden frauds by performing the correlation analysis between different types and different subjects of fraud. We design and develop MedicareVis, a visual analysis system for medical insurance anti-fraud. We demonstrate the usefulness and effectiveness of our approach in helping detect the association of fraud through a case study on real-world medical insurance data and interviews with domain experts.
MedicareVis:一种用于医疗保险反欺诈的联合视觉分析方法
医疗保险欺诈造成严重的经济损失,对医疗保险制度的安全稳定有很大影响。然而,现有工作并不支持对各种类型的欺诈行为进行联合分析和探索。基于与多维时间序列相关的医疗保险数据,提出了一种可视化的医疗保险反欺诈分析方法。它可以对医疗保险数据进行时空过滤,快速定位欺诈行为,并通过对不同类型和不同主体的欺诈行为进行相关性分析,发现隐藏的欺诈行为。我们设计并开发了MedicareVis,一个用于医疗保险反欺诈的可视化分析系统。我们通过对真实世界医疗保险数据的案例研究和对领域专家的采访,证明了我们的方法在帮助检测欺诈关联方面的有用性和有效性。
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来源期刊
计算机辅助设计与图形学学报
计算机辅助设计与图形学学报 Computer Science-Computer Graphics and Computer-Aided Design
CiteScore
1.20
自引率
0.00%
发文量
6833
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