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The effect of a law limiting upcoding on hospital admissions: evidence from Italy

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  • Giorgio Vittadini
  • Paolo Berta

    ()

  • Gianmaria Martini
  • Giuditta Callea

Abstract

Policy makers have made several attempts to limit hospitals upcoding. We investigate the impact on discharges with and without complications of a law introducing a minimum length of stay to discharges with complications. We implement a DID econometric model to assess the impact of the law and a logistic multilevel model to estimate whether hospitals reacted strategically to it by varying the patients’ length of stay. We show that the policy has been effective in limiting upcoding, since the number of discharges with complications is significantly lower in 2008. We also show that hospitals have reacted strategically to the law by modifying the distribution of discharges’ length of stay in DRGs with complications, in order to continue practicing upcoding. Furthermore, we provide evidence that upcoding is greater in private for–profit hospitals, that have been more affected by the law.
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Suggested Citation

  • Giorgio Vittadini & Paolo Berta & Gianmaria Martini & Giuditta Callea, 2012. "The effect of a law limiting upcoding on hospital admissions: evidence from Italy," Empirical Economics, Springer, vol. 42(2), pages 563-582, April.
  • Handle: RePEc:spr:empeco:v:42:y:2012:i:2:p:563-582
    DOI: 10.1007/s00181-012-0548-6
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    References listed on IDEAS

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    1. Blundell, Richard & Macurdy, Thomas, 1999. "Labor supply: A review of alternative approaches," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 27, pages 1559-1695, Elsevier.
    2. Berta, Paolo & Callea, Giuditta & Martini, Gianmaria & Vittadini, Giorgio, 2010. "The effects of upcoding, cream skimming and readmissions on the Italian hospitals efficiency: A population-based investigation," Economic Modelling, Elsevier, vol. 27(4), pages 812-821, July.
    3. Leemore S. Dafny, 2005. "How Do Hospitals Respond to Price Changes?," American Economic Review, American Economic Association, vol. 95(5), pages 1525-1547, December.
    4. Leemore Dafny & David Dranove, 2009. "Regulatory Exploitation and Management Changes: Upcoding in the Hospital Industry," Journal of Law and Economics, University of Chicago Press, vol. 52(2), pages 223-250, May.
    5. Mark McClellan, 1997. "Hospital Reimbursement Incentives: An Empirical Analysis," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 6(1), pages 91-128, March.
    6. Silverman, Elaine & Skinner, Jonathan, 2004. "Medicare upcoding and hospital ownership," Journal of Health Economics, Elsevier, vol. 23(2), pages 369-389, March.
    7. Liu, Zhimei & Dow, William H. & Norton, Edward C., 2004. "Effect of drive-through delivery laws on postpartum length of stay and hospital charges," Journal of Health Economics, Elsevier, vol. 23(1), pages 129-155, January.
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    Cited by:

    1. Paolo Berta & Gianmaria Martini & Francesco Moscone & Giorgio Vittadini, 2016. "The association between asymmetric information, hospital competition and quality of healthcare: evidence from Italy," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(4), pages 907-926, October.

    More about this item

    Keywords

    Upcoding; Length of stay; Logit model; Difference-in-difference model; C51; I11; I18; L33;

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • L33 - Industrial Organization - - Nonprofit Organizations and Public Enterprise - - - Comparison of Public and Private Enterprise and Nonprofit Institutions; Privatization; Contracting Out

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