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Unraveling Healthcare Fraud: Exploring ROI and Deterrence Challenges

Jetson Leder-LuisbyJetson Leder-Luis
May 20, 2024
in Feature, Health, Biopharma, & Health-Tech
32
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Unraveling Healthcare Fraud: Exploring ROI and Deterrence Challenges
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In the ongoing battle against healthcare fraud, understanding the effectiveness of anti-fraud efforts is paramount. This Q&A, featuring Questrom Assistant Professor of Markets, Public Policy, and Law, Jetson Leder-Luis, dives into the intricacies of combating healthcare fraud, with a focus on the significance of return on investment (ROI) and the challenges of measuring deterrence.

The Centers for Medicare and Medicaid Services (CMS) has commissioned a white paper by Dr. Leder-Luis and a team at Boston University. You can read the white paper here.

Q: Why are efforts to combat healthcare fraud important?
A: Efforts to combat healthcare fraud are important for the long-term financial sustainability of health insurance programs, as well as for ensuring that patients receive appropriate care.

Q: How do insurers combat healthcare fraud?
A: Insurers combat healthcare fraud through various means, including pre-payment and post-payment reviews like audits, criminal and civil lawsuits against fraudulent health care providers, and regulatory measures aimed at eliminating opportunities for fraud.

Q: What is ROI, and why is it important in evaluating anti-fraud efforts?
A: ROI, or return on investment, measures the net value of these efforts against costs. When evaluating anti-fraud efforts, ROI helps assess the relative cost-effectiveness reducing spending on fraud, waste, and abuse while improving the quality of healthcare. ROI should be standardized between types of enforcement, and across organizations, to ensure public resources are directed at effective solutions.

Q: What are the financial components of anti-fraud efforts? How does this differ from past thinking about the issue?
A: Historically, the US government has focused on recovery, the money recuperated from these efforts. However, the full financial value of anti-fraud efforts includes both recovery and deterrence, which involves saving money through prevention efforts.

Q: How is deterrence measured in anti-fraud efforts?
A: Deterrence in anti-fraud efforts is challenging to measure directly, because it involves estimating the money not spent, including through pre-payment detection and also changes in fraudulent behavior post-enforcement. In our white paper, we show how this can be done, by estimating trends in the pre-enforcement spending patterns of fraudulent behavior. In other scholarly work, I show these estimates hold using more sophisticated techniques.

Q: How does including deterrence impact ROI measurements?
A:  If you fail to include deterrence in ROI, you severely undercount the value of these anti-fraud efforts like lawsuits. Including deterrence in ROI measurements can significantly increase the calculated ROI, often by a factor of 2 to 10, compared to only considering recovery.

Q: What policy recommendations does your work suggest?
A: Undercounting or excluding deterrence in ROI calculations undervalues preventative anti-fraud efforts, because there is no recovery when the money is never spent. As insurers – both private and the government – move toward models of preventing rather than catching fraud, it’s increasingly important that we appropriately value those tools, and direct our efforts accordingly.

Tags: Anti-Fraud Effortshealth careHealthcarehealthcare anti-fraud effortsReturn on Investment
Jetson Leder-Luis

Jetson Leder-Luis

Jetson Leder-Luis is an Assistant Professor in Markets, Public Policy, & Law at Boston University Questrom School of Business. He is an economist studying public economics, health economics and political economy. He also has interests in fraud, misreporting and overbilling in public expenditures, particularly in the Medicare and Medicaid programs, as well as the consequences of these behaviors for public spending and patient health outcomes. He also researches the detection and deterrence of fraud and corruption, as well as the statistical properties of misreported data.

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