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Computer-aided auditing of prescription drug claims

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Abstract

We describe a methodology for identifying and ranking candidate audit targets from a database of prescription drug claims. The relevant audit targets may include various entities such as prescribers, patients and pharmacies, who exhibit certain statistical behavior indicative of potential fraud and abuse over the prescription claims during a specified period of interest. Our overall approach is consistent with related work in statistical methods for detection of fraud and abuse, but has a relative emphasis on three specific aspects: first, based on the assessment of domain experts, certain focus areas are selected and data elements pertinent to the audit analysis in each focus area are identified; second, specialized statistical models are developed to characterize the normalized baseline behavior in each focus area; and third, statistical hypothesis testing is used to identify entities that diverge significantly from their expected behavior according to the relevant baseline model. The application of this overall methodology to a prescription claims database from a large health plan is considered in detail.

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Acknowledgments

We thank the health plan staff responsible for audits and fraud prevention and detection for their support and guidance during this project. We also thank the reviewers for their feedback and suggestions.

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Authors and Affiliations

  1. IBM Thomas J. Watson Research Center, P. O. Box 218, Yorktown Heights, NY, 10598, USA

    Vijay S. Iyengar, Keith B. Hermiz & Ramesh Natarajan

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  1. Vijay S. Iyengar
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  2. Keith B. Hermiz
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  3. Ramesh Natarajan
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Correspondence to Keith B. Hermiz.

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Iyengar, V.S., Hermiz, K.B. & Natarajan, R. Computer-aided auditing of prescription drug claims. Health Care Manag Sci 17, 203–214 (2014). https://doi.org/10.1007/s10729-013-9247-x

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  • DOI: https://doi.org/10.1007/s10729-013-9247-x

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