Department of Emergency Medicine, Johns Hopkins University, Baltimore, Maryland, USA.
Systems Institute, Johns Hopkins University, Baltimore, Maryland, USA.
Health Care Manag Sci. 2018 Mar;21(1):119-130. doi: 10.1007/s10729-016-9382-2. Epub 2016 Sep 6.
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.
当前的市场条件促使一些医疗机构以不合理的方式控制患者数据，从而限制其可用性和使用。在这里，我们开发了一种博弈论模型来估计医疗机构加入健康信息交换（HIE）网络的意愿，并展示了其在 HIE 政策设计中的应用。我们将模型制定为一个双层整数规划。提出了一种拟牛顿法来获得策略纳什均衡。我们将我们的建模和求解技术应用于佛罗里达州三个县内的 9 家医院在 7.5 年期间交换信息的 1,093,177 次就诊。在一组假设下，我们发现拟议的联邦罚款最高可达 200 万美元，比当前的联邦货币激励措施对增加 HIE 采用的影响更大。中型医院比大型医院更不愿意采用 HIE。在多家医院串通不采用 HIE 的情况下，联邦激励措施和拟议的罚款都不会增加医院采用 HIE 的意愿。医院对 HIE 采用的冷漠可能会威胁到互联互通的价值，即使有联邦激励措施存在。医院之间的竞争，加上基于数量的支付系统，并没有为较小的医院与竞争对手交换数据创造激励。中型医院需要采取有针对性的行动（例如，外部技术援助、集体采购安排）来减轻不采用 HIE 的市场激励。战略博弈论模型有助于在极其复杂的技术环境中阐明市场条件下的 HIE 采用决策。
