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作 者:陈文潇 李娜[1] CHEN Wenxiao;LI Na(School of Mechanical Engineering,Shanghai Jiao Tong University,Shanghai 200240,China)
机构地区:[1]上海交通大学机械与动力工程学院,上海200240
出 处:《工业工程与管理》2024年第4期67-77,共11页Industrial Engineering and Management
基 金:国家自然科学基金资助项目(72171144,72293585,71871138);上海交通大学“交大之星”计划医工交叉研究(YG2022QN004)。
摘 要:互联网诊疗已成为降低医疗成本、改善患者就诊体验的有效途径。公立医院通过对现有资源进行重新分配,来提供互联网诊疗服务;医保局通过对公立医院进行补贴,来影响公立医院的资源分配决策。针对由公立医院和医保局组成的医疗系统,构建了嵌入排队模型的斯坦伯格博弈模型,研究了在不同医保付费机制下,公立医院的最优资源分配策略及医保局的最优补贴策略。捆绑式支付,即对线上、线下服务捆绑付费;按服务付费,即分别对线上、线上服务进行付费;基于惩罚的付费,即对线上患者到线下的重新诊疗进行惩罚的付费机制。对比了不同付费机制下的社会利益。结果表明:只有当公立医院的最优决策恰好与社会利益一致时,捆绑式支付才表现良好;基于惩罚的付费在多数情况下表现良好,按服务付费在部分情况下也有较好的表现;当医保局预算充足,复诊率对资源分配的敏感性、单位线上患者的便利性和健康风险收益都较大时,二者可以产生相同的社会利益。Configuring e-visits has become an effective way to reduce medical costs and improve patients'experience.Public hospitals introduce e-visits by reallocating existing resources.The national healthcare security administration(NHSA)reimburses public hospitals,which affects the resource allocation strategy of public hospitals.A Stackelberg game embedded with a queuing model was formulated for the healthcare system consisting of a public hospital and the NHSA.The optimal resource allocation strategy of the public hospital and the optimal reimbursement strategy of the NHSA were investigated under different payment schemes.Three payment schemes were discussed.Bundled payment(BP)bundled the payment for online and offline service.Fee for service(FFS)separately paid for the online and offline service.Penalty scheme(PS)penalized the public hospital on revisit patients.The social welfare under different payment schemes was compared.The results show that BP performs well only when the optimal decision of public hospitals happens to coincide with the social welfare well.Otherwise,PS performs the best in most cases,while FFS outperforms others in some cases.Both PS and FFS yield the same social welfare when the budget is sufficient,and the sensitivity of revisit rates to resource allocation and the unit convenience-and-risk-reduction gain are large.
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