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<p>With the rapid advancement of health information technology and growing demand for efficient data sharing, Health Information Exchange (HIE) systems have gained increasing attention. However, research on HIE revenue schemes for asymmetric competitive healthcare providers (HPs) remains limited. This study develops a game-theoretic model to analyze the Health Information Exchange (HIE)’s optimal revenue-scheme selection under asymmetric competition between healthcare providers (HPs). Four combinations of subscription and fee-for-service (FFS) schemes are examined to derive equilibrium pricing, service quality, and welfare outcomes. To verify robustness, we conduct parameter sensitivity and Monte Carlo-based probabilistic analyses, showing that the welfare-optimal configuration (subscription for high-level HPs and FFS for low-level HPs) remains stable under the parameter uncertainty. Furthermore, the model is generalized to an N-HPs market, where the HIE’s revenue-scheme choice is formulated as a 0–1 combinatorial optimization problem. We prove a threshold structure and design a Sorting-and-Threshold Search Algorithm (STSA) that efficiently identifies stable welfare-maximizing assignments. Empirical case studies of U.S. HIEs validate the model and highlight adoption challenges and transitional incentives that promote sustainable implementation.</p>

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Competition between healthcare providers under subscription and fee-for-service: an equilibrium analysis of health information exchange system’s choice

  • 期刊论文

  • 发表日期：

    2026年3月24日

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  • Zhaofang Mao,
  • Yuqiong Jiang,
  • Yufeng Liao

摘要

With the rapid advancement of health information technology and growing demand for efficient data sharing, Health Information Exchange (HIE) systems have gained increasing attention. However, research on HIE revenue schemes for asymmetric competitive healthcare providers (HPs) remains limited. This study develops a game-theoretic model to analyze the Health Information Exchange (HIE)’s optimal revenue-scheme selection under asymmetric competition between healthcare providers (HPs). Four combinations of subscription and fee-for-service (FFS) schemes are examined to derive equilibrium pricing, service quality, and welfare outcomes. To verify robustness, we conduct parameter sensitivity and Monte Carlo-based probabilistic analyses, showing that the welfare-optimal configuration (subscription for high-level HPs and FFS for low-level HPs) remains stable under the parameter uncertainty. Furthermore, the model is generalized to an N-HPs market, where the HIE’s revenue-scheme choice is formulated as a 0–1 combinatorial optimization problem. We prove a threshold structure and design a Sorting-and-Threshold Search Algorithm (STSA) that efficiently identifies stable welfare-maximizing assignments. Empirical case studies of U.S. HIEs validate the model and highlight adoption challenges and transitional incentives that promote sustainable implementation.