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Data analytics (ab) use in healthcare fraud audits

Author

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  • Koreff, Jared
  • Weisner, Martin
  • Sutton, Steve G.

Abstract

This study explores how government-adopted audit data analytic tools promote the abuse of power by auditors enabling politically sensitive processes that encourage industry-wide normalization of behavior. In an audit setting, we investigate how a governmental organization enables algorithmic decision-making to alter power relationships to effect organizational and industry-wide change. While prior research has identified discriminatory threats emanating from the deployment of algorithmic decision-making, the effects of algorithmic decision-making on inherently imbalanced power relationships have received scant attention. Our results provide empirical evidence of how systemic and episodic power relationships strengthen each other, thereby enabling the governmental organization to effect social change that might be too politically prohibitive to enact directly. Overall, the results suggest that there are potentially negative effects caused by the use of algorithmic decision-making and the resulting power shifts, and these effects create a different view of the level of purported success attained through auditor use of data analytics.

Suggested Citation

  • Koreff, Jared & Weisner, Martin & Sutton, Steve G., 2021. "Data analytics (ab) use in healthcare fraud audits," International Journal of Accounting Information Systems, Elsevier, vol. 42(C).
    • Handle: RePEc:eee:ijoais:v:42:y:2021:i:c:s1467089521000257
    DOI: 10.1016/j.accinf.2021.100523
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    Cited by:

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    2. Nathanael Betti & Steven DeSimone & Joy Gray, 2022. "The impacts of the use of data analytics and the performance of consulting activities on perceived internal audit quality," Working Papers 2202, College of the Holy Cross, Department of Economics.
    3. Perdana, Arif & Lee, Hwee Hoon & Koh, SzeKee & Arisandi, Desi, 2022. "Data analytics in small and mid-size enterprises: Enablers and inhibitors for business value and firm performance," International Journal of Accounting Information Systems, Elsevier, vol. 44(C).

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