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Ambulance Taxis: The Impact of Regulation and Litigation on Health Care Fraud

Author

Listed:
  • Paul J. Eliason
  • Riley J. League
  • Jetson Leder-Luis
  • Ryan C. McDevitt
  • James W. Roberts

Abstract

We study the relative effectiveness of administrative regulations, criminal enforcement, and civil lawsuits for combatting health care fraud. Between 2003 and 2017, Medicare spent $7.7 billion on 37.5 million regularly scheduled, non-emergency ambulance rides for patients traveling to and from dialysis facilities, with dozens of lawsuits alleging that Medicare reimbursed rides for patients who did not meet the requirements for receiving one. Using a novel data set and an identification strategy based on the staggered timing of regulations and lawsuits across the United States, we find that a regulation requiring prior authorization for ambulance reimbursements reduced spending much more than criminal and civil lawsuits did. Despite the sharp drop in both ambulance transports and the companies that provide them following prior authorization, patients’ health outcomes did not change, indicating that most rides were not medically necessary. Our results suggest that administrative actions have a much larger impact than targeted criminal enforcement, providing novel evidence that regulations may be more cost-effective than ex post ligation for preventing health care fraud.

Suggested Citation

  • Paul J. Eliason & Riley J. League & Jetson Leder-Luis & Ryan C. McDevitt & James W. Roberts, 2021. "Ambulance Taxis: The Impact of Regulation and Litigation on Health Care Fraud," NBER Working Papers 29491, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:29491
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    Cited by:

    1. Shubhranshu Shekhar & Jetson Leder-Luis & Leman Akoglu, 2023. "Unsupervised Machine Learning for Explainable Health Care Fraud Detection," NBER Working Papers 30946, National Bureau of Economic Research, Inc.
    2. O'Malley, A. James & Bubolz, Thomas A. & Skinner, Jonathan S., 2023. "The diffusion of health care fraud: A bipartite network analysis," Social Science & Medicine, Elsevier, vol. 327(C).

    More about this item

    JEL classification:

    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • D73 - Microeconomics - - Analysis of Collective Decision-Making - - - Bureaucracy; Administrative Processes in Public Organizations; Corruption
    • H41 - Public Economics - - Publicly Provided Goods - - - Public Goods
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • K42 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Illegal Behavior and the Enforcement of Law

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