IDEAS home Printed from https://ideas.repec.org/p/pen/papers/16-006.html
   My bibliography  Save this paper

Detecting Potential Overbilling in Medicare Reimbursement via Hours Worked

Author

Listed:
  • Hanming Fang

    (Department of Economics, University of Pennsylvania)

  • Qing Gong

    (Department of Economics, UNC Chapel Hill)

Abstract

Medicare over billing refers to the phenomenon that providers report more and/or higher-intensity service codes than actually delivered to receive higher Medicare reimbursement. We propose a novel and easy-to-implement approach to detect potential over billing based on the hours worked implied by the service codes physicians submit to Medicare. Using the Medicare Part B Fee-for-Service (FFS) Physician Utilization and Payment Data in 2012 and 2013 released by the Centers for Medicare and Medicaid Services (CMS), we first construct estimates for physicians' hours spent on Medicare Part B FFS beneficiaries. Despite our deliberately conservative estimation procedure, we find that about 2,300 physicians, or 3% of those with a significant fraction of Medicare Part B FFS services, have billed Medicare over 100 hours per week. We consider this implausibly long hours. As a benchmark, the maximum hours spent on Medicare patients by physicians in National Ambulatory Medical Care Survey data are 50 hours in a week. Interestingly, we also find suggestive evidence that the coding patterns of the flagged physicians seem to be responsive to financial incentives: within code clusters with different levels of service intensity, they tend to submit more higher intensity service codes than unflagged physicians; moreover, they are more likely to do so if the marginal revenue gain from submitting mid- or high-intensity codes is relatively high.

Suggested Citation

  • Hanming Fang & Qing Gong, 2016. "Detecting Potential Overbilling in Medicare Reimbursement via Hours Worked," PIER Working Paper Archive 16-006, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 07 Mar 2016.
  • Handle: RePEc:pen:papers:16-006
    as

    Download full text from publisher

    File URL: https://economics.sas.upenn.edu/sites/default/files/filevault/wp16-006.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Dan Zeltzer, 2020. "Gender Homophily in Referral Networks: Consequences for the Medicare Physician Earnings Gap," American Economic Journal: Applied Economics, American Economic Association, vol. 12(2), pages 169-197, April.
    2. 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.
    3. Michael Geruso & Timothy Layton, 2020. "Upcoding: Evidence from Medicare on Squishy Risk Adjustment," Journal of Political Economy, University of Chicago Press, vol. 128(3), pages 984-1026.
    4. Leemore Dafny & David Dranove, 2009. "Regulatory Exploitation and Management Changes: Upcoding in the Hospital Industry," Journal of Law and Economics, University of Chicago Press, vol. 52(2), pages 223-250, May.
    5. 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.
    6. Congressional Budget Office, 2014. "The 2014 Long-Term Budget Outlook," Reports 45471, Congressional Budget Office.
    7. Congressional Budget Office, 2014. "The 2014 Long-Term Budget Outlook," Reports 45471, Congressional Budget Office.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ronelle Burger & Canh Thien Dang & Trudy Owens, 2017. "Better performing NGOs do report more accurately: Evidence from investigating Ugandan NGO financial accounts," Discussion Papers 2017-10, University of Nottingham, CREDIT.
    2. Dang, Canh Thien & Owens, Trudy, 2020. "Does transparency come at the cost of charitable services? Evidence from investigating British charities," Journal of Economic Behavior & Organization, Elsevier, vol. 172(C), pages 314-343.
    3. 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.
    4. Simon Reif & Lucas Hafner & Michael Seebauer, 2020. "Physician Behavior under Prospective Payment Schemes—Evidence from Artefactual Field and Lab Experiments," IJERPH, MDPI, vol. 17(15), pages 1-37, July.
    5. Farbmacher, Helmut & Löw, Leander & Spindler, Martin, 2022. "An explainable attention network for fraud detection in claims management," Journal of Econometrics, Elsevier, vol. 228(2), pages 244-258.
    6. Victoria Perez & Coady Wing, 2019. "Should We Do More to Police Medicaid Fraud? Evidence on the Intended and Unintended Consequences of Expanded Enforcement," American Journal of Health Economics, University of Chicago Press, vol. 5(4), pages 481-508, Fall.
    7. Hanming Fang & Qing Gong, 2020. "Detecting Potential Overbilling in Medicare Reimbursement via Hours Worked: Reply," American Economic Review, American Economic Association, vol. 110(12), pages 4004-4010, December.
    8. 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.
    9. Cook, Amanda & Averett, Susan, 2020. "Do hospitals respond to changing incentive structures? Evidence from Medicare’s 2007 DRG restructuring," Journal of Health Economics, Elsevier, vol. 73(C).
    10. Xidong Guo, 2024. "An analysis of a rural hospital's investment decision under different payment systems," Health Economics, John Wiley & Sons, Ltd., vol. 33(4), pages 714-747, April.
    11. David C Chan & Michael J Dickstein, 2019. "Industry Input in Policy Making: Evidence from Medicare," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 134(3), pages 1299-1342.
    12. David C. Chan, Jr & Michael J. Dickstein, 2018. "Industry Input in Policymaking: Evidence from Medicare," NBER Working Papers 24354, National Bureau of Economic Research, Inc.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bowblis John R. & Brunt Christopher S. & Grabowski David C., 2016. "Competitive Spillovers and Regulatory Exploitation by Skilled Nursing Facilities," Forum for Health Economics & Policy, De Gruyter, vol. 19(1), pages 45-70, June.
    2. Cook, Amanda & Averett, Susan, 2020. "Do hospitals respond to changing incentive structures? Evidence from Medicare’s 2007 DRG restructuring," Journal of Health Economics, Elsevier, vol. 73(C).
    3. Christopher S. Brunt, 2015. "Medicare Part B Intensity and Volume Offset," Health Economics, John Wiley & Sons, Ltd., vol. 24(8), pages 1009-1026, August.
    4. Duncan Ermini Leaf & Bryan Tysinger & Dana P. Goldman & Darius N. Lakdawalla, 2021. "Predicting quantity and quality of life with the Future Elderly Model," Health Economics, John Wiley & Sons, Ltd., vol. 30(S1), pages 52-79, November.
    5. Imtiaz Bhatti & Marvin Phaup, 2015. "Budgeting for Fiscal Uncertainty and Bias: A Federal Process Proposal," Public Budgeting & Finance, Wiley Blackwell, vol. 35(2), pages 89-105, June.
    6. Kazumasa Oguro, 2014. "Challenges confronting Abenomics and Japanese public finance ?Fiscal consolidation must start by squarely facing reality?," Public Policy Review, Policy Research Institute, Ministry of Finance Japan, vol. 10(2), pages 301-318, August.
    7. Robert Garnett & Kimmarie Mcgoldrick, 2014. "A 'Big Think' Approach to Government Debt: Promoting Significant Learning in Introductory Macroeconomics," Review of Political Economy, Taylor & Francis Journals, vol. 26(4), pages 628-647, October.
    8. Martin Feldstein, 2015. "Raising Revenue by Limiting Tax Expenditures," Tax Policy and the Economy, University of Chicago Press, vol. 29(1), pages 1-11.
    9. Thomas Url & Rob J Hyndman & Alexander Dokumentov, 2016. "Long-term forecasts of age-specific participation rates with functional data models," Monash Econometrics and Business Statistics Working Papers 3/16, Monash University, Department of Econometrics and Business Statistics.
    10. Jason L. Saving & Alan D. Viard, 2015. "Are income taxes destined to rise? the fiscal imbalance and future tax policy," Working Papers 1502, Federal Reserve Bank of Dallas.
    11. Michael Clemens, 2021. "The Fiscal Effect of Immigration: Reducing Bias in Influential Estimates," CESifo Working Paper Series 9464, CESifo.
    12. Òscar Jordà & Chitra Marti & Fernanda Nechio & Eric Tallman, 2019. "Inflation: Stress-Testing the Phillips Curve," FRBSF Economic Letter, Federal Reserve Bank of San Francisco.
    13. 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.
    14. Alan J Auerbach, 2016. "Long-Term Fiscal Sustainability in Advanced Economies," Asia and the Pacific Policy Studies, Wiley Blackwell, vol. 3(2), pages 142-154, May.
    15. Holston, Kathryn & Laubach, Thomas & Williams, John C., 2017. "Measuring the natural rate of interest: International trends and determinants," Journal of International Economics, Elsevier, vol. 108(S1), pages 59-75.
    16. Thomas Laubach & John C. Williams, 2015. "Measuring the natural rate of interest redux," Working Paper Series 2015-16, Federal Reserve Bank of San Francisco.
    17. Thomas Url & Rob J. Hyndman & Alexander Dokumentov, 2016. "Long-term Forecasts of Age-specific Labour Market Participation Rates with Functional Data Models," WIFO Working Papers 510, WIFO.
    18. Canyon Bosler & Mary C. Daly & John G. Fernald & Bart Hobijn, 2017. "The Outlook for US Labor-Quality Growth," NBER Chapters, in: Education, Skills, and Technical Change: Implications for Future US GDP Growth, pages 61-110, National Bureau of Economic Research, Inc.
    19. William N. Butos, 2015. "The Bernanke Fed and "Credit Easing" Policies, 2008-2014," Journal of Private Enterprise, The Association of Private Enterprise Education, vol. 30(Winter 20), pages 1-15.
    20. 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.

    More about this item

    Keywords

    Medicare; Overbilling; Hours worked;
    All these keywords.

    JEL classification:

    • D71 - Microeconomics - - Analysis of Collective Decision-Making - - - Social Choice; Clubs; Committees; Associations
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pen:papers:16-006. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Administrator (email available below). General contact details of provider: https://edirc.repec.org/data/deupaus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.