Monday, November 18, 2024

Medicare Fraud; Trump Office of Government Efficiency; Expert at Boston University

There's much press about the proposed Department of Government Efficiency - DOGE - to be headed by Elon Musk and Vivek Ramaswamy (The Hill, here, CenterSquare here.)

Bloomberg ODD LOTS Podcast is on the case fast, with a stellar interview [podcast] with a top fraud expert, Prof. Jetson Leder-Luis at Boston University.  (His resume speeds along in high gear).  

I served as a Medicare medical director for California 2004-2008, and the fraud issues were colossal and fascinating.   I've continued to track areas like genomic test fraud (Code 81408 here, here, OIG here) and recent ACO/catheter fraud (my angry blog here).

I really enjoyed the podcast connecting DOGE with CMS fraud, and I've downloaded a number of Leder-Luis' open-access articles to read.   See also a one-hour lecture, or summary.

I think Chat GPT 4o did a good job of summarizing the podcast and summarizing his resume' (below). 

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Another academic expert on healthcare fraud is Prof. Malcolm Sparrow of Harvard's Kennedy school, whom I had a chance to meet when I worked on CMS fraud in California.  His book, License to Steal: How Fraud Bleeds America's Health Care System [2000], was foundational.

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In addition to lab Medicare fraud under code 81408, as reported by an GAO report and other sources, in December 2024 JAMA has some negative articles about possible abuse of generic molecular microbiology codes for UTI's.  Here, here, here.   I wrote about the same topic 18 months before JAMA (here).

AI CORNER

Summary of podcast, followed by summary of C.V.

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This episode of the Odd Lots podcast delivers a thoughtful, data-driven exploration of government fraud, particularly focusing on fraud in healthcare and public spending. Below is a detailed assessment:

Main Themes

  1. Government Fraud in Healthcare:

    • Ambulance Services: The episode explains how fraudulent practices in non-emergency ambulance services, particularly for dialysis patients, exploited Medicare loopholes for billions of dollars. Requiring physician prior authorization was a successful solution, reducing fraud by 67% without negatively affecting patient outcomes.
    • Durable Medical Equipment: Common fraud practices include upcoding, medical necessity fraud, and substandard care. Examples include fraudulent wheelchairs and other equipment, often billed at higher rates or unnecessary for patients.
    • Wound Care and Vascular Fraud: Emerging trends in fraud are flagged, such as excessive spending on non-healing wound treatments and vascular care.

  2. Anti-Fraud Mechanisms:

    • Prior Authorization: Highlighted as an effective strategy in the ambulance case, showing substantial savings without negative health impacts.
    • Whistleblower Programs: The False Claims Act incentivizes whistleblowing by offering financial rewards to individuals who expose fraud, creating a private market for anti-fraud efforts.
    • Data-Driven Detection: Emphasis on the underutilization of data analytics in detecting fraud. While data exists, a lack of skilled analysts and insufficient government resources limits its utility.

  3. Broader Fraud Examples:

    • Pandemic-Related Unemployment Fraud: Exploitation of unemployment insurance systems during COVID-19 through identity theft and fraudulent claims.
    • Defense and Infrastructure Fraud: Acknowledgment of areas like defense contracting, where fraud may persist due to limited oversight and information asymmetry.

  4. Challenges in Addressing Fraud:

    • Government Incentives: The focus on recovery rather than deterrence is criticized. Deterrence efforts have a far greater impact but are underfunded.
    • Resource Allocation: The DOJ and other agencies lack the capacity to address even known fraud cases due to staff and budget limitations.
    • Cultural and Structural Issues: The lack of competitive salaries for skilled data analysts and attorneys within government positions hinders fraud detection efforts.

Strengths of the Episode

  • Expert Insights: Jetson Leder-Luis provides academic rigor and empirical evidence, citing his research and recent publications.
  • Clear Illustrations: Real-world examples, such as the dialysis ambulance fraud and durable medical equipment scams, make complex issues accessible.
  • Balanced Discussion: The hosts maintain an engaging balance of skepticism and optimism, acknowledging both successes and ongoing challenges in fraud prevention.

Potential Areas for Improvement

  1. Depth on Broader Fraud: While the episode focuses primarily on healthcare fraud, further elaboration on defense and infrastructure fraud could add value.
  2. Implementation Barriers: Discussion of practical barriers (e.g., political resistance, bureaucratic inertia) to adopting more robust data-driven anti-fraud systems could enhance the analysis.
  3. Comparison with Other Systems: Contrasting U.S. government anti-fraud efforts with those of other countries (e.g., UK’s NHS) could provide additional context.

Notable Takeaways

  • Economic Impact of Fraud: U.S. healthcare fraud alone may account for $100 billion annually, underscoring the need for targeted anti-fraud measures.
  • Data Underutilization: The government has access to rich datasets but lacks the resources to fully leverage them.
  • Whistleblower Effectiveness: Private enforcement of anti-fraud laws via whistleblowers is an underappreciated but critical tool in reducing fraud.

Conclusion

This episode succeeds in offering a detailed, engaging examination of government fraud, with a strong emphasis on healthcare. By blending academic insights with practical examples, it provides actionable insights for policymakers and an accessible narrative for general listeners. However, expanding coverage to other sectors and discussing systemic barriers would make the episode even more comprehensive.

Overall, the podcast exemplifies how data analysis and targeted policy interventions can meaningfully reduce fraud, ultimately benefiting both taxpayers and program beneficiaries.

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Jetson Leder-Luis, PhD, exemplifies a highly productive and influential scholar at the intersection of public economics, health economics, and political economy. His work stands out for its empirical rigor, multidisciplinary approach, and policy relevance. Below is a detailed analysis of his academic profile, contributions, and impact:

Academic and Professional Background

  1. Education:

    • PhD in Economics from MIT (2020), mentored by prominent economists Jim Poterba and Ben Olken.
    • Dual BS in Applied and Computational Mathematics and Economics from Caltech (2014).

  2. Current Roles:

    • Assistant Professor at Boston University’s Questrom School of Business.
    • Faculty Research Fellow at the National Bureau of Economic Research (NBER).

  3. Affiliations and Leadership:

    • Co-organizer of the Empirical Health Law Conference and the Harvard-MIT-BU Health Economics Seminar, showcasing his leadership in fostering academic discourse.

  4. Fellowships and Honors:

    • Notable fellowships include the Ford Foundation Dissertation Fellowship and recognition through programs like REACH Prep and the Stamps Scholars.

Research Focus

Dr. Leder-Luis’s research addresses fraud, corruption, and inefficiencies in public spending, with a particular emphasis on the Medicare and Medicaid programs. His work is distinguished by:

  • A strong empirical focus, leveraging vast datasets (e.g., 100% Medicare claims data).
  • Examination of the statistical properties of fraud and misreporting in public expenditures.
  • Policy-driven inquiries that have direct implications for healthcare regulation and fraud prevention.

His working papers and publications have explored fraud detection, the economic implications of public spending, and innovative anti-fraud mechanisms, such as whistleblowing and machine learning.

Key Contributions

Published Work

  1. "Can Whistleblowers Root Out Public Expenditure Fraud?" (2023):

    • Highlights the effectiveness of whistleblower programs in Medicare fraud detection.
    • Emphasizes the role of private enforcement in deterring public expenditure fraud.

  2. "Maimonides Rule Redux" (2019):

    • Explores statistical applications in education policy, co-authored with influential economists.

  3. “Structural Topic Models for Open-Ended Survey Responses” (2014):

    • A methodological breakthrough in text analysis, earning the Gosnell Prize for Excellence in Political Methodology.

  4. White Papers and Policy Reports:

    • Authored a widely cited CMS white paper quantifying the value of healthcare anti-fraud efforts.

Accepted and Forthcoming Papers

  • "Ambulance Taxis": Analyzes the impact of regulation and litigation on healthcare fraud in the ambulance industry, forthcoming in Journal of Political Economy.
  • "Dying or Lying?": Challenges the narrative around for-profit hospices, showing cost-saving and patient-preference benefits despite allegations of fraud (American Economic Review).

Ongoing Research

  • Machine Learning in Fraud Detection:
    • Investigates how AI can enhance fraud detection in Medicare, bridging advanced analytics with public policy.
  • Unemployment Insurance Fraud:
    • Examines the vulnerabilities in pandemic-era unemployment benefits, shedding light on identity theft and systemic exploitation.

Engagement Beyond Academia

Dr. Leder-Luis actively contributes to public policy through:

  1. Testimonies: Provided expert testimony on fraud detection to the Pennsylvania State Government Committee.

  2. Media Contributions:

    • Featured in podcasts and articles, including MarketWatch and the Wall Street Journal.
    • His ability to communicate complex economic ideas to broader audiences underscores his versatility.

  3. Global Anticorruption Blog Contributions:

    • Authored influential pieces on cost-effective anticorruption strategies, whistleblowing, and campaign finance fraud detection.

Impact and Future Directions

  1. Policy Influence:

    • His research has directly informed policies aimed at reducing fraud in Medicare, Medicaid, and other public programs.
    • Contributions to whistleblower policy design and machine learning applications showcase a forward-looking approach to fraud prevention.

  2. Interdisciplinary Reach:

    • By blending economics, law, and data science, his work appeals to policymakers, legal experts, and economists alike.

  3. Future Potential:

    • As emerging fields like AI-driven analytics and healthcare reform evolve, Dr. Leder-Luis is well-positioned to lead groundbreaking studies that shape public policy.

Conclusion

Jetson Leder-Luis exemplifies the modern, interdisciplinary economist. His prolific output, policy relevance, and dedication to impactful research make him a rising star in the fields of public economics and health policy. His work not only addresses pressing societal challenges but also proposes practical, data-driven solutions, establishing him as a thought leader in detecting and deterring public fraud.