Show Me Your Claims and I'll Tell You Your Offenses: Machine Learning-Based Decision Support for Fraud Detection on Medical Claim Data

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dc.contributor.authorMatschak, Tizian
dc.contributor.authorPrinz, Christoph
dc.contributor.authorRampold, Florian
dc.contributor.authorTrang, Simon
dc.date.accessioned2021-12-24T17:52:12Z
dc.date.available2021-12-24T17:52:12Z
dc.date.issued2022-01-04
dc.description.abstractHealth insurance claim fraud is a serious issue for the healthcare industry as it drives up costs and inefficiency. Therefore, claim fraud must be effectively detected to provide economical and high-quality healthcare. In practice, however, fraud detection is mainly performed by domain experts resulting in significant cost and resource consumption. This paper presents a novel Convolutional Neural Network-based fraud detection approach that was developed, implemented, and evaluated on Medicare Part B records. The model aids manual fraud detection by classifying potential types of fraud, which can then be specifically analyzed. Our model is the first of its kind for Medicare data, yields an AUC of 0.7 for selected fraud types and provides an applicable method for medical claim fraud detection.
dc.format.extent9 pages
dc.identifier.doi10.24251/HICSS.2022.454
dc.identifier.isbn978-0-9981331-5-7
dc.identifier.urihttp://hdl.handle.net/10125/79790
dc.language.isoeng
dc.relation.ispartofProceedings of the 55th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectDecision Support for Healthcare Processes and Services
dc.subjectdigital health
dc.subjectfraud detection
dc.subjecthealthcare
dc.subjectmachine learning
dc.titleShow Me Your Claims and I'll Tell You Your Offenses: Machine Learning-Based Decision Support for Fraud Detection on Medical Claim Data
dc.type.dcmitext

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