ArticleHealth care management science2016
Multi-stage methodology to detect health insurance claim fraud.
Article in Health care management science, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Economic impact of health insurance fraud, waste, and abuse: a literature review of direct and indirect costs and system sustainability.Frontiers in public health · 2026Pooled it
- A study on the current status of collaboration between China's commercial health insurance and medical institutions and improvement strategies.BMC health services research · 2026Article
- What goals does China's medical insurance fund supervision aim to achieve? A quantitative analysis based on national-level policies.BMC health services research · 2025Article
- What influences the public's willingness to report health insurance fraud in familiar or unfamiliar healthcare settings? a cross-sectional study of the young and middle-aged people in China.BMC public health · 2024Article
- Detecting fraud, waste, and abuse in substance use disorder treatment.Health services research · 2022Article
- Multicriteria decision frontiers for prescription anomaly detection over time.Journal of applied statistics · 2022Article
- Fourteen years of manifestations and factors of health insurance fraud, 2006-2020: a scoping review.Health & justice · 2021Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Healthcare costs in the US, as well as in other countries, increase rapidly due to demographic, economic, social, and legal changes. This increase in healthcare costs impacts both government and private health insurance systems. Fraudulent behaviors of healthcare providers and patients have become a serious burden to insurance systems by bringing unnecessary costs. Insurance companies thus develop methods to identify fraud. This paper proposes a new multistage methodology for insurance companies to detect fraud committed by providers and patients. The first three stages aim at detecting abnormalities among providers, services, and claim amounts. Stage four then integrates the information obtained in the previous three stages into an overall risk measure. Subsequently, a decision tree based method in stage five computes risk threshold values. The final decision stating whether the claim is fraudulent is made by comparing the risk value obtained in stage four with the risk threshold value from stage five. The research methodology performs well on real-world insurance data.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.