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Health Care Management Science

, Volume 21, Issue 1, pp 119–130 | Cite as

A strategic gaming model for health information exchange markets

  • Diego A. MartinezEmail author
  • Felipe Feijoo
  • Jose L. Zayas-Castro
  • Scott Levin
  • Tapas K. Das
Article

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.

Keywords

Health information exchange Medical record linkage Game theory Market models 

Notes

Acknowledgments

The authors would like to thank the three anonymous reviewers for their thoughtful revision.

Author’s Contribution

DM contributed to the idea conception, study design, model development, and acquisition and analysis of results. FF contributed to the study design, model development and analysis of results. SL, TD and JZ are guarantors and contributed to the idea conception and analysis of results. All authors contributed equally in preparing and reviewing multiple versions of the manuscript and provided significant intellectual content. All authors read and approved the final version of this manuscript.

Compliance with ethical standards

Competing interests

The authors declare no competing interests.

Funding

No funding was provided for the completion of this study.

Supplementary material

10729_2016_9382_MOESM1_ESM.xlsx (3.7 mb)
ESM 1 (XLSX 3805 kb)
10729_2016_9382_MOESM2_ESM.docx (3 mb)
ESM 2 (DOCX 3074 kb)

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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Diego A. Martinez
    • 1
    • 2
    Email author
  • Felipe Feijoo
    • 2
    • 3
    • 4
  • Jose L. Zayas-Castro
    • 5
  • Scott Levin
    • 1
    • 2
  • Tapas K. Das
    • 5
  1. 1.Department of Emergency MedicineJohns Hopkins UniversityBaltimoreUSA
  2. 2.Systems InstituteJohns Hopkins UniversityBaltimoreUSA
  3. 3.Engineering Sciences DepartmentUniversidad Andres BelloSantiagoChile
  4. 4.Department of Civil EngineeringJohns Hopkins UniversityBaltimoreUSA
  5. 5.Department of Industrial and Management Systems EngineeringUniversity of South FloridaTampaUSA

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