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A survey on statistical methods for health care fraud detection
Jing Li1, Kuei-Ying Huang, Jionghua Jin
1Department of Industrial Engineering, Arizona State University, P.O. Box 875906, Tempe, AZ 85287-5906, USA. jinglz@asu.edu
Health Care Management Science
|October 2, 2008
Summary
This survey explores statistical methods for detecting health care fraud and abuse, a major expense in the US. It identifies data sources, preprocessing steps, and compares detection techniques to guide future research.
Area of Science:
- Health Economics
- Data Science
- Statistical Analysis
Background:
- Healthcare fraud and abuse represent a significant financial burden on the US healthcare system.
- Effective fraud detection is crucial for cost containment and system integrity.
Purpose of the Study:
- To provide a comprehensive survey of statistical methods used in healthcare fraud detection.
- To classify fraudulent behaviors and identify data characteristics relevant to fraud detection.
- To highlight research gaps and suggest future research directions in statistical fraud detection.
Main Methods:
- Literature review and synthesis of statistical fraud detection methods.
- Categorization and comparison of different statistical approaches.
- Analysis of data sources and preprocessing techniques in fraud detection.
Main Results:
- Identification of various statistical techniques applied to healthcare fraud detection.
- Characterization of data sources and preprocessing steps commonly used.
- A comparative overview of the strengths and weaknesses of different methods.
Conclusions:
- Existing research has gaps in addressing certain aspects of statistical fraud detection.
- Further research is needed to refine and develop novel statistical approaches for more effective fraud detection.
- The survey provides a foundation for future work in combating healthcare fraud and abuse.
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