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How do Hospitals Respond to Payment Incentives?

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  • Gautam Gowrisankaran
  • Keith A. Joiner
  • Jianjing Lin

Abstract

Over the past decades, Medicare has developed payment reforms that incentivize quality care, by reimbursing fixed amounts for ex ante similar patients. While these reforms may add value, they require providers to code more information on patient health conditions, which is costly. We evaluate the role of revenues and costs in coding intensity for Medicare hospitalized inpatients. We examine the role of costs by estimating hospitals’ changes in coding intensity following a 2007 reform based on whether they had adopted electronic medical records (EMRs). EMR hospitals documented relatively more top billing codes after the reform with the increase occurring only for non-surgical admissions, consistent with the hypotheses that costs became an important determinant of the coding decision and EMRs lower these costs, particularly for medical admissions. We further examine whether increased reimbursements from reporting complex diagnoses led hospitals to report more of these diagnoses. We find evidence in favor of this hypothesis before the reform but not after, suggesting that increased billing complexity post-reform made coding costs a more important driver of coding decisions. Our findings suggests that recent payment innovations might add cost to providers, who may want to consider reimbursements in their technology adoption and usage decisions.

Suggested Citation

  • Gautam Gowrisankaran & Keith A. Joiner & Jianjing Lin, 2019. "How do Hospitals Respond to Payment Incentives?," NBER Working Papers 26455, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:26455
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    1. Gowrisankaran, Gautam & Lucarelli, Claudio & Schmidt-Dengler, Philipp & Town, Robert, 2018. "Can amputation save the hospital? The impact of the Medicare Rural Flexibility Program on demand and welfare," Journal of Health Economics, Elsevier, vol. 58(C), pages 110-122.
    2. Jason Brown & Mark Duggan & Ilyana Kuziemko & William Woolston, 2014. "How Does Risk Selection Respond to Risk Adjustment? New Evidence from the Medicare Advantage Program," American Economic Review, American Economic Association, vol. 104(10), pages 3335-3364, October.
    3. Clément de Chaisemartin & Xavier D'Haultfœuille, 2020. "Two-Way Fixed Effects Estimators with Heterogeneous Treatment Effects," American Economic Review, American Economic Association, vol. 110(9), pages 2964-2996, September.
    4. Thompson, Samuel B., 2011. "Simple formulas for standard errors that cluster by both firm and time," Journal of Financial Economics, Elsevier, vol. 99(1), pages 1-10, January.
    5. Jinhyung Lee & Jeffrey S. McCullough & Robert J. Town, 2013. "The impact of health information technology on hospital productivity," RAND Journal of Economics, RAND Corporation, vol. 44(3), pages 545-568, September.
    6. Jeffrey Clemens & Joshua D. Gottlieb, 2014. "Do Physicians' Financial Incentives Affect Medical Treatment and Patient Health?," American Economic Review, American Economic Association, vol. 104(4), pages 1320-1349, April.
    7. Sacarny, Adam, 2018. "Adoption and learning across hospitals: The case of a revenue-generating practice," Journal of Health Economics, Elsevier, vol. 60(C), pages 142-164.
    8. Seth Freedman & Haizhen Lin & Jeffrey Prince, 2018. "Information Technology and Patient Health: Analyzing Outcomes, Populations, and Mechanisms," American Journal of Health Economics, MIT Press, vol. 4(1), pages 51-79, Winter.
    9. David Dranove & Chris Forman & Avi Goldfarb & Shane Greenstein, 2014. "The Trillion Dollar Conundrum: Complementarities and Health Information Technology," American Economic Journal: Economic Policy, American Economic Association, vol. 6(4), pages 239-270, November.
    10. Leemore S. Dafny, 2005. "How Do Hospitals Respond to Price Changes?," American Economic Review, American Economic Association, vol. 95(5), pages 1525-1547, December.
    11. Amalia R. Miller & Catherine Tucker, 2009. "Privacy Protection and Technology Diffusion: The Case of Electronic Medical Records," Management Science, INFORMS, vol. 55(7), pages 1077-1093, July.
    12. Jeffrey S. McCullough & Stephen T. Parente & Robert Town, 2016. "Health information technology and patient outcomes: the role of information and labor coordination," RAND Journal of Economics, RAND Corporation, vol. 47(1), pages 207-236, February.
    13. Jeffrey Clemens & Joshua D. Gottlieb, 2017. "In the Shadow of a Giant: Medicare’s Influence on Private Physician Payments," Journal of Political Economy, University of Chicago Press, vol. 125(1), pages 1-39.
    14. Sun, Liyang & Abraham, Sarah, 2021. "Estimating dynamic treatment effects in event studies with heterogeneous treatment effects," Journal of Econometrics, Elsevier, vol. 225(2), pages 175-199.
    15. Agha, Leila, 2014. "The effects of health information technology on the costs and quality of medical care," Journal of Health Economics, Elsevier, vol. 34(C), pages 19-30.
    16. Amalia R. Miller & Catherine E. Tucker, 2011. "Can Health Care Information Technology Save Babies?," Journal of Political Economy, University of Chicago Press, vol. 119(2), pages 289-324.
    17. Silverman, Elaine & Skinner, Jonathan, 2004. "Medicare upcoding and hospital ownership," Journal of Health Economics, Elsevier, vol. 23(2), pages 369-389, March.
    18. Or., Zeynep, 2014. "Implementation of DRG Payment in France: Issues and recent developments," Health Policy, Elsevier, vol. 117(2), pages 146-150.
    19. Abe Dunn & Joshua D. Gottlieb & Adam Hale Shapiro & Pietro Tebaldi, 2020. "The Costs of Payment Uncertainty in Healthcare Markets," Working Paper Series 2020-13, Federal Reserve Bank of San Francisco.
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    Cited by:

    1. Abe Dunn & Joshua D. Gottlieb & Adam Shapiro & Daniel J. Sonnenstuhl & Pietro Tebaldi, 2021. "A Denial a Day Keeps the Doctor Away," NBER Working Papers 29010, National Bureau of Economic Research, Inc.
    2. Yaping Wu & David Bardey & Yijuan Chen & Sanxi Li, 2021. "Health care insurance policies When the provider and patient may collude," Health Economics, John Wiley & Sons, Ltd., vol. 30(3), pages 525-543, March.
    3. 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).

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    More about this item

    JEL classification:

    • H51 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Health
    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets
    • I13 - Health, Education, and Welfare - - Health - - - Health Insurance, Public and Private
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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