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A strategic gaming model for health information exchange markets

Author

Listed:
  • Diego A. Martinez

    (Johns Hopkins University
    Johns Hopkins University)

  • Felipe Feijoo

    (Johns Hopkins University
    Universidad Andres Bello
    Johns Hopkins University)

  • Jose L. Zayas-Castro

    (University of South Florida)

  • Scott Levin

    (Johns Hopkins University
    Johns Hopkins University)

  • Tapas K. Das

    (University of South Florida)

Abstract

Current market conditions create incentives for some providers to exercise control over patient data in ways that unreasonably limit its availability and use. Here we develop a game theoretic model for estimating the willingness of healthcare organizations to join a health information exchange (HIE) network and demonstrate its use in HIE policy design. We formulated the model as a bi-level integer program. A quasi-Newton method is proposed to obtain a strategy Nash equilibrium. We applied our modeling and solution technique to 1,093,177 encounters for exchanging information over a 7.5-year period in 9 hospitals located within a three-county region in Florida. Under a set of assumptions, we found that a proposed federal penalty of up to $2,000,000 has a higher impact on increasing HIE adoption than current federal monetary incentives. Medium-sized hospitals were more reticent to adopt HIE than large-sized hospitals. In the presence of collusion among multiple hospitals to not adopt HIE, neither federal incentives nor proposed penalties increase hospitals’ willingness to adopt. Hospitals’ apathy toward HIE adoption may threaten the value of inter-connectivity even with federal incentives in place. Competition among hospitals, coupled with volume-based payment systems, creates no incentives for smaller hospitals to exchange data with competitors. Medium-sized hospitals need targeted actions (e.g., outside technological assistance, group purchasing arrangements) to mitigate market incentives to not adopt HIE. Strategic game theoretic models help to clarify HIE adoption decisions under market conditions at play in an extremely complex technology environment.

Suggested Citation

  • Diego A. Martinez & Felipe Feijoo & Jose L. Zayas-Castro & Scott Levin & Tapas K. Das, 2018. "A strategic gaming model for health information exchange markets," Health Care Management Science, Springer, vol. 21(1), pages 119-130, March.
    • Handle: RePEc:kap:hcarem:v:21:y:2018:i:1:d:10.1007_s10729-016-9382-2
    DOI: 10.1007/s10729-016-9382-2
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    References listed on IDEAS

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    1. repec:mpr:mprres:7285 is not listed on IDEAS
    2. Raith, Michael A., 1993. "A general model of information sharing in oligopoly," LSE Research Online Documents on Economics 19370, London School of Economics and Political Science, LSE Library.
    3. Julia Adler-Milstein & Catherine M. DesRoches & Ashish K. Jha, 2011. "Health Information Exchange Among US Hospitals," Mathematica Policy Research Reports bcb4110b4fec4921a6e0d1e25, Mathematica Policy Research.
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    8. repec:cep:stitep:/1993/260 is not listed on IDEAS
    9. Michael A. Raith, 1993. "A General Model of Information Sharing in Oligopoly," STICERD - Theoretical Economics Paper Series 260, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    10. Feijoo, Felipe & Das, Tapas K., 2014. "Design of Pareto optimal CO2 cap-and-trade policies for deregulated electricity networks," Applied Energy, Elsevier, vol. 119(C), pages 371-383.
    11. Bruce C. Greenwald & Joseph E. Stiglitz, 1986. "Externalities in Economies with Imperfect Information and Incomplete Markets," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 101(2), pages 229-264.
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    Cited by:

    1. Acuna, Jorge A. & Zayas-Castro, Jose L. & Feijoo, Felipe, 2022. "A bilevel Nash-in-Nash model for hospital mergers: A key to affordable care," Socio-Economic Planning Sciences, Elsevier, vol. 83(C).

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