IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v69y2023i11p6777-6799.html
   My bibliography  Save this article

Hospital Reimbursement in the Presence of Cherry Picking and Upcoding

Author

Listed:
  • Nicos Savva

    (London Business School, London NW1 4SA, United Kingdom)

  • Laurens Debo

    (Tuck School of Business, Dartmouth College, Hanover, New Hampshire 03755)

  • Robert A. Shumsky

    (Tuck School of Business, Dartmouth College, Hanover, New Hampshire 03755)

Abstract

Hospitals throughout the developed world are reimbursed based on diagnosis-related groups (DRGs). Under this scheme, patients are divided into clinically meaningful groups, and hospitals receive a fixed fee per patient episode tied to the patient DRG. The fee is based on the average cost of providing care to patients who belong to the same DRG across all hospitals. This scheme, sometimes referred to as “yardstick competition,” provides incentives for cost reduction, as no hospital wants to operate at a higher cost than average, and can be implemented using accounting data alone. Nevertheless, if costs within a DRG are heterogeneous, this scheme may give rise to cherry-picking incentives, where providers “drop” patients who are more expensive to treat than average. To address this problem, regulators have tried to reduce within-DRG cost heterogeneity by expanding the number of DRG classes. In this paper, we show that even if cost heterogeneity is eliminated, such expansion will fail to completely eliminate patient cherry picking. In equilibrium, the market will bifurcate into two groups, one of which will continue to cherry-pick patients and underinvest in cost reduction, whereas the other group treats all patients. Furthermore, we show that DRG expansion is particularly problematic if hospitals are also able to “upcode” patients, that is, intentionally assign patients to a more resource-intensive DRG than needed to increase income. Upcoding increases within-DRG cost heterogeneity and amplifies cherry-picking incentives. We examine potential solutions involving yardstick competition based on input statistics.

Suggested Citation

  • Nicos Savva & Laurens Debo & Robert A. Shumsky, 2023. "Hospital Reimbursement in the Presence of Cherry Picking and Upcoding," Management Science, INFORMS, vol. 69(11), pages 6777-6799, November.
  • Handle: RePEc:inm:ormnsc:v:69:y:2023:i:11:p:6777-6799
    DOI: 10.1287/mnsc.2023.4752
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.2023.4752
    Download Restriction: no

    File URL: https://libkey.io/10.1287/mnsc.2023.4752?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ormnsc:v:69:y:2023:i:11:p:6777-6799. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.