Detecting Potential Overbilling in Medicare Reimbursement via Hours Worked

Hanming Fang and Qing Gong ()
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Qing Gong: Department of Economics, UNC Chapel Hill

PIER Working Paper Archive from Penn Institute for Economic Research, Department of Economics, University of Pennsylvania

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.

Keywords: Medicare; Overbilling; Hours worked (search for similar items in EconPapers)
JEL-codes: D71 D81 (search for similar items in EconPapers)
Pages: 54 pages
Date: 2016-03-07, Revised 2016-03-07
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Related works:
Journal Article: Detecting Potential Overbilling in Medicare Reimbursement via Hours Worked (2017)
Working Paper: Detecting Potential Overbilling in Medicare Reimbursement via Hours Worked (2016)
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