Primary Approach for Fraud Detection of Health Care Using Data Mining Techniques

Abstract

Data mining is one of the fastest growing fields in the computer industry; one of the greatest strengths of data mining is reflected in its wide range of methodologies and techniques that can be applied to a host of problem sets.

The major advantage that data mining tools have over the traditional analysis tools is that they use computer cycles to replace human cycles.

Patient health records represent comprehensive documents of the continuity of heath care and are a rich source of data for research. Data are generally accessible, accurate, and relatively inexpensive.

This research use data mining techniques to detect fraud from patients and providers .To detects those fraud we use combination of PolyAnalyst techniques.

We detect fraud from patients by performing analysis to the database and then create link chart, also we can detect fraud from providers by Transition Basket Analysis.

By performing those techniques we minimize the frauds from both patients and providers.