An unsupervised Bayesian hierarchical method for medical fraud assessment

DOI10.1002/SAM.11408OpenAlexW2919823329MaRDI QIDQ4970238

Greg Lakomski, Tahir Ekin, Rasim Muzaffer Musal

Publication date: 14 October 2020

Published in: Statistical Analysis and Data Mining: The ASA Data Science Journal (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/sam.11408

zbMATH Keywords

health care fraudBayesian hierarchical methodsmedical auditsmedical fraudunsupervised data mining

Mathematics Subject Classification ID

Statistics (62-XX) Computer science (68-XX)

Related Items (1)

Multicriteria decision frontiers for prescription anomaly detection over time

Uses Software

• tm
• wordcloud
• GibbsLDA++

Cites Work

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• Text Mining
• 10.1162/jmlr.2003.3.4-5.993
• Overpayment models for medical audits: multiple scenarios
• On the Use of the Concentration Function in Medical Fraud Assessment
• Statistical Medical Fraud Assessment: Exposition to an Emerging Field

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