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Detecting Potential Overbilling in Medicare Reimbursement via Hours Worked: Comment

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  • Brett Matsumoto

Abstract

Fang and Gong (2017) develop a procedure to detect potential overbilling of Medicare by physicians. In their empirical analysis, they use aggregated claims data that can overstate the number of services performed due to features of Medicare billing. In this comment, I show how auditors can use detailed claims-level data to better target improper overbilling.

Suggested Citation

  • Brett Matsumoto, 2020. "Detecting Potential Overbilling in Medicare Reimbursement via Hours Worked: Comment," American Economic Review, American Economic Association, vol. 110(12), pages 3991-4003, December.
    • Handle: RePEc:aea:aecrev:v:110:y:2020:i:12:p:3991-4003
    DOI: 10.1257/aer.20180812
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    Cited by:

    1. 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.

    More about this item

    JEL classification:

    • H51 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Health
    • I13 - Health, Education, and Welfare - - Health - - - Health Insurance, Public and Private
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply
    • J44 - Labor and Demographic Economics - - Particular Labor Markets - - - Professional Labor Markets and Occupations

    Lists

    This item is featured on the following reading lists, Wikipedia, or ReplicationWiki pages:
    1. Detecting Potential Overbilling in Medicare Reimbursement via Hours Worked: Comment (AER 2020) in ReplicationWiki

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