Abstract
Healthcare insurance frauds are causing millions of dollars of public healthcare fund losses around the world in various ways, which makes it very important to strengthen the management of medical insurance in order to guarantee the steady operation of medical insurance funds. Healthcare fraud detection methods can reduce the losses of healthcare insurance funds and improve medical quality. Existing fraud detection studies mostly focus on finding normal behavior patterns and treat those violating normal behavior patterns as fraudsters. However, fraudsters can often disguise themselves with some normal behaviors, such as some consistent behaviors when they seek medical treatments. To address these issues, we combined a MapReduce distributed computing model and association rule mining to propose a medical cluster behavior detection algorithm based on frequent pattern mining. It can detect certain consistent behaviors of patients in medical treatment activities. By analyzing 1.5 million medical claim records, we have verified the effectiveness of the method. Experiments show that this method has better performance than several benchmark methods.
Highlights
Medical insurance is a social insurance system established to compensate workers for economic losses caused by disease risks
The medical insurance funds are established via payments from insured employers and individuals, and their medical expenses for medical treatment will be partly compensated by medical insurance institutions
Our main contributions in this paper are listed as follows: 1) constructing a medical aggregation behavior model that includes a formal description of medical aggregation behaviors; 2) designing a distributed anomaly detection algorithm and corresponding interpretation of the detection results; 3) compared with several benchmark methods for frequent itemset mining, the performance advantage of this method becomes more significant as the amount of data continues to increase, which can significantly improve the accuracy of fraud detection
Summary
Medical insurance is a social insurance system established to compensate workers for economic losses caused by disease risks. The medical insurance funds are established via payments from insured employers and individuals, and their medical expenses for medical treatment will be partly compensated by medical insurance institutions. The establishment and implementation of the medical insurance system can enable patients to obtain the necessary help, reduce the burden of medical expenses, and prevent the diseased members of the society from becoming ‘‘poor after illness’’ [1]. China’s social medical insurance has developed rapidly. Increasing the coverage of social medical insurance has become the most important task for China’s social security system. By the end of 2018, 1.345 billion people had registered in the basic medical insurance, covering
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