Data and Code for: Detecting Potential Overbilling in Medicare Reimbursement via Hours Worked
Principal Investigator(s): View help for Principal Investigator(s) Hanming Fang, University of Pennsylvania; Qing Gong, University of Pennsylvania
Version: View help for Version V1
Version Title: View help for Version Title Legacy version
| Name | File Type | Size | Last Modified |
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| code | 05/21/2020 03:53:PM | ||
| input | 05/21/2020 03:59:PM | ||
| output | 05/21/2020 04:09:PM | ||
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text/plain | 14.6 KB | 05/21/2020 11:52:AM |
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application/pdf | 183.3 KB | 05/21/2020 11:52:AM |
Project Citation:
Fang, Hanming, and Gong, Qing. Data and Code for: Detecting Potential Overbilling in Medicare Reimbursement via Hours Worked. Nashville, TN: American Economic Association [publisher], 2020. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2020-05-22. https://doi.org/10.3886/E119565V1
Project Description
Summary:
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We propose a novel and easy-to-implement approach to detect potential overbilling based on the hours worked implied by the service codes which 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, we construct estimates for physicians' hours spent on Medicare beneficiaries. We find that about 2,300 physicians, representing about 3 percent of those with 20 or more hours of Medicare Part B FFS services, have billed Medicare over 100 hours per week. We consider these implausibly long hours.
Scope of Project
JEL Classification:
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H51 National Government Expenditures and Health
I13 Health Insurance, Public and Private
I18 Health: Government Policy; Regulation; Public Health
J22 Time Allocation and Labor Supply
H51 National Government Expenditures and Health
I13 Health Insurance, Public and Private
I18 Health: Government Policy; Regulation; Public Health
J22 Time Allocation and Labor Supply
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