主讲人:
沈逸文（香港科技大学商学院运营管理系助理教授）
主持老师:
（北大全健院）崔知涵
参与老师：
（北大经院）秦雪征、施新政、石菊、姚奕、王耀璟、袁野、梁远宁、庄晨
（北大全健院）刘国恩、黄成、孙宇、吕蓓妮、潘聿航、杨佳楠、林淑君、林昊翔、蒋少翔
时间：
2024年9月25日（周三）
10:00-11:30
地点:
北京大学经济学院107会议室
主讲人简介:
沈逸文博士，香港科技大学商学院运营管理系(ISOM)的助理教授。他在北京大学获得物理学学士学位，并在哥伦比亚大学商学院获得运营管理博士学位。他的研究兴趣主要集中在实证运营管理、数据驱动决策、医疗运营管理、以及金融市场等。研究成果曾发表于
Management Science, Journal of Financial Markets
等杂志。沈逸文博士曾获得2021 INFORMS HAS Student Paper Competition (Second Place) 、2021 INFORMS Best Cluster Paper Award (Finalist) 等国际学术奖项。他目前主持以及参与多项由香港研究资助局（RGC）资助的科研项目。
摘要:
We study the medical reimbursement policy design problem with multiple types of services and random costs. The central planner decides the reimbursement policy for agents’ costs to minimize the total utility loss, subject to a budget constraint. We obtain closed-form optimal solution for both the max-out-of-pocket and ratio reimbursement policies, which are commonly used in practice. We then investigate the effect of cross-sectional pooling when there are multiple heterogenous groups. We find that in general cases, the central planner can achieve the optimal performance by pooling the budgets together and use a common reimbursement policy for all groups. Finally, we consider a dynamic model in which the central planner needs to balance between current and future utilities. We characterize the optimal dynamic policy and show that the benefit of pooling still applies. We conduct multiple numerical analysis, including a real-world example with Chinese medical insurance data, to show the benefits of cross-sectional and dynamic pooling.
