Detecting Potential Overbilling in Medicare Reimbursement via Hours Worked
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- Hanming Fang & Qing Gong, 2017. "Detecting Potential Overbilling in Medicare Reimbursement via Hours Worked," American Economic Review, American Economic Association, vol. 107(2), pages 562-591, February.
- 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.
References listed on IDEAS
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- Hafner, Lucas & Reif, Simon & Seebauer, Michael, 2017. "Physician behavior under prospective payment schemes: Evidence from artefactual field and lab experiments," FAU Discussion Papers in Economics 18/2017, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
- 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.
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American Journal of Health Economics, University of Chicago Press, vol. 5(4), pages 481-508, Fall.
- 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, MIT Press, vol. 5(4), pages 481-508, Fall.
- 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.
- 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.
- 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).
- 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.
- 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.
- 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.
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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
NEP fields
This paper has been announced in the following NEP Reports:- NEP-HEA-2016-04-09 (Health Economics)
- NEP-IAS-2016-04-09 (Insurance Economics)
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