An Integrated Decision Making Framework for Medical Audit Sampling

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dc.contributor.authorEkin, Tahir
dc.date.accessioned2019-01-03T00:23:22Z
dc.date.available2019-01-03T00:23:22Z
dc.date.issued2019-01-08
dc.description.abstractThe loss of three to ten percent of annual health care expenditures to fraudulent transactions makes medical audits paramount. In order to handle the size and complexity of medical claims, the use of analytical methods and information technology tools to aid in medical audits is necessary. In general, sampling frameworks are utilized to choose representative claims. However, these are not integrated within audit decision-making procedures. As a novelty, this paper presents an integrated decision-making framework for medical audit sampling. We propose a simple but effective optimization method that uses sampling output and enables auditors address the trade-offs between audit costs and expected overpayment recovery. We use U.S. Medicare Part B claims payment data to demonstrate the framework.
dc.format.extent8 pages
dc.identifier.doi10.24251/HICSS.2019.498
dc.identifier.isbn978-0-9981331-2-6
dc.identifier.urihttp://hdl.handle.net/10125/59848
dc.language.isoeng
dc.relation.ispartofProceedings of the 52nd 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.subjectOptimization of and the Use of IT for Healthcare Processes
dc.subjectInformation Technology in Healthcare
dc.subjecthealth care audits, optimization, sampling, information theory, Medicare
dc.titleAn Integrated Decision Making Framework for Medical Audit Sampling
dc.typeConference Paper
dc.type.dcmiText

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