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Privatizing Plaintiffs: How Medicaid, the False Claims Act, and Decentralized Fraud Detection Affect Public Fraud Enforcement Efforts

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  • Thuy Nguyen
  • Victoria Perez

Abstract

In 2016, decentralized fraud enforcement under the federal False Claims Act (FCA) recovered $ 2.5 billion spent on healthcare fraud without increasing spending. The FCA induces private citizens to pursue civil fraud claims on behalf of both themselves and the government, or qui tam; incentives to pursue legal action for Medicaid fraud vary at the state level. We hypothesize that fraud enforcement agencies shift strategies as incentives for private citizens to monitor civil offenses rise. We find that state‐level FCAs did not increase the number of filed qui tam suits as incentives rose. Among filed cases, case quality did not change. Instead, agencies pursued fewer civil cases and case length increased. Our findings suggest potential qui tam plaintiffs are constrained by an ability to pursue cases, not incentives. Government‐led civil fraud enforcement may thus overestimate the capacity to decentralize fraud enforcement.

Suggested Citation

  • Thuy Nguyen & Victoria Perez, 2020. "Privatizing Plaintiffs: How Medicaid, the False Claims Act, and Decentralized Fraud Detection Affect Public Fraud Enforcement Efforts," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 87(4), pages 1063-1091, December.
    • Handle: RePEc:bla:jrinsu:v:87:y:2020:i:4:p:1063-1091
    DOI: 10.1111/jori.12281
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    References listed on IDEAS

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    1. Christopher S. Brunt, 2011. "CPT fee differentials and visit upcoding under Medicare Part B," Health Economics, John Wiley & Sons, Ltd., vol. 20(7), pages 831-841, July.
    2. Rajeev Goel & Michael Nelson, 2011. "Government fragmentation versus fiscal decentralization and corruption," Public Choice, Springer, vol. 148(3), pages 471-490, September.
    3. Alpert, Abby & Duggan, Mark & Hellerstein, Judith K., 2013. "Perverse reverse price competition: Average wholesale prices and Medicaid pharmaceutical spending," Journal of Public Economics, Elsevier, vol. 108(C), pages 44-62.
    4. Hanming Fang & Qing Gong, 2017. "Detecting Potential Overbilling in Medicare Reimbursement via Hours Worked," American Economic Review, American Economic Association, vol. 107(2), pages 562-591, February.
    5. Rai, Arti K, 2001. "Health Care Fraud and Abuse: A Tale of Behavior Induced by Payment Structure," The Journal of Legal Studies, University of Chicago Press, vol. 30(2), pages 579-587, June.
    6. Rajeev K. Goel & Michael A. Nelson, 2014. "Whistleblower laws and exposed corruption in the United States," Applied Economics, Taylor & Francis Journals, vol. 46(20), pages 2331-2341, July.
    7. Hyunyoung Choi & Hal Varian, 2012. "Predicting the Present with Google Trends," The Economic Record, The Economic Society of Australia, vol. 88(s1), pages 2-9, June.
    8. repec:hhs:bofitp:2013_009 is not listed on IDEAS
    9. Hyman, David A, 2001. "Health Care Fraud and Abuse: Market Change, Social Norms, and the Trust "Reposed in the Workmen."," The Journal of Legal Studies, University of Chicago Press, vol. 30(2), pages 531-567, June.
    10. Silverman, Elaine & Skinner, Jonathan, 2004. "Medicare upcoding and hospital ownership," Journal of Health Economics, Elsevier, vol. 23(2), pages 369-389, March.
    11. Leemore S. Dafny, 2005. "How Do Hospitals Respond to Price Changes?," American Economic Review, American Economic Association, vol. 95(5), pages 1525-1547, December.
    12. Rajeev K. Goel & Michael A. Nelson, 2014. "Whistleblower laws and exposed corruption in the United States," Applied Economics, Taylor & Francis Journals, vol. 46(20), pages 2331-2341, July.
    13. Karpoff, Jonathan M & Lott, John R, Jr, 1993. "The Reputational Penalty Firms Bear from Committing Criminal Fraud," Journal of Law and Economics, University of Chicago Press, vol. 36(2), pages 757-802, October.
    14. Feldman, Roger, 2001. "An Economic Explanation for Fraud and Abuse in Public Medical Care Programs," The Journal of Legal Studies, University of Chicago Press, vol. 30(2), pages 569-577, June.
    15. Park, David K. & Gelman, Andrew & Bafumi, Joseph, 2004. "Bayesian Multilevel Estimation with Poststratification: State-Level Estimates from National Polls," Political Analysis, Cambridge University Press, vol. 12(4), pages 375-385.
    16. John R. Bowblis & Christopher S. Brunt, 2014. "Medicare Skilled Nursing Facility Reimbursement And Upcoding," Health Economics, John Wiley & Sons, Ltd., vol. 23(7), pages 821-840, July.
    17. Jason Barabas & Jennifer Jerit, 2009. "Estimating the Causal Effects of Media Coverage on Policy‐Specific Knowledge," American Journal of Political Science, John Wiley & Sons, vol. 53(1), pages 73-89, January.
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    Cited by:

    1. Chamal Gomes & Zhuo Jin & Hailiang Yang, 2021. "Insurance fraud detection with unsupervised deep learning," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 88(3), pages 591-624, September.

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