The Effects of Insurance Benefit Design Innovation on Patient Health

摘要 我在卫生经济学方面的研究主要集中在信息和目标消费者如何分担成本 影响患者如何选择医疗服务提供者，以及激励患者选择低价医疗服务所节省的资金 提供商我也考察了市场的反面，如何耐心地利用信息，有的放矢 消费者的动机刺激了供应商的价格竞争。这些主题为我的研究提供了框架， 我是加州大学伯克利分校卫生经济学的博士生，我和我继续在这些基础上进行研究 在兰德公司担任政策研究员时，我职业生涯的下一步自然是扩大这一点 研究路线，但在更深入的方式和使用更先进的统计方法。执行 在这些领域的指导研究将帮助我成功地从指导过渡到独立 research.拟议的研究将帮助我（1）有助于更深入地了解患者健康影响 一个创新的保险福利设计，特别是与人口老龄化有关;（2）继续 建立处理大型医疗索赔数据集的能力，并发展创新统计方面的专业知识 不同学科的方法;（3）获得与老龄化相关的卫生服务研究方面的培训;（4）扩大我的 接触老龄化，卫生经济学和卫生服务研究社区;（5）发展我的 能力作为一个独立的卫生服务研究人员，并建立基础，成功地竞争， R 01级赠款。 在这个项目中，我建议研究结肠镜检查和药物的参考定价是否 降低了对推荐的结直肠癌筛查和药物治疗的依从性， 老年人口。我还将研究参考定价对患者健康结果和老龄化的影响。 过程为了做到这一点，我打算应用新的机器学习统计方法， 在计算机科学和统计学领域发展起来的。作为这项提议的一部分，我建立了一个正式的培训 计划发展这些方法的专门知识。这个项目将为我提供灵活性和支持， 制定一个长期的研究议程，重点是使用创新的统计方法来评估 消费者成本分担计划的综合效果。虽然这项研究的重点是一个单一的成本- 共享程序，参考定价，我通过这个奖项获得的技能将使我能够独立领导 评估未来的福利设计。机器学习方法在参考文献设置中的应用 定价将提供一个框架，我或其他研究人员可以用来评估其他保险福利设计 或替代患者群体。 !

Abstract My research in health economics has focused on how information and targeted consumer cost-sharing influences how patients choose providers and the financial savings of incentivizing patients to choose low-price providers. I have also examined the opposite side of the market, how patient use of information and targeted consumer incentives spurs provider price competition. These topics provided the framework for my research as a PhD student in Health Economics at the University of California, Berkeley and I continue to build on these topics while a policy researcher at the RAND Corporation. A natural next step for my career is to expand this line of research but in a more in-depth manner and using more advanced statistical methods. Performing mentored research in these areas will help me successfully make the transition from directed to independent research. The proposed study will help me to (1) contribute to a deeper understanding of patient health effects of an innovative insurance benefit design that is particularly relevant for the aging population; (2) continue to build capabilities working with large medical claims data sets and develop expertise in innovative statistical methods from different disciplines; (3) gain training in aging-related health-services research; (4) expand my exposure to the aging, health economics, and health services research communities; and (5) develop my abilities as an independent health services researcher and build the foundations to successfully compete for R01-level grants. In this project, I propose to examine whether reference pricing for colonoscopies and pharmaceuticals decreases adherence to recommended colorectal cancer screening and medication therapies among the near- elderly population. I will also examine the impact of reference pricing on patient health outcomes and the aging process. To do so, I intend to apply novel machine-learning statistical methods that have been recently developed in the computer science and statistics fields. As part of this proposal, I have built a formal training plan to develop expertise in these methods. This project will provide me with the flexibility and support to develop a long-term research agenda that focuses on using innovative statistical methods to evaluate the comprehensive effects of consumer cost- sharing programs. Although this study focuses on a single cost- sharing program, reference pricing, the skills I gain through this award will allow me to independently lead evaluations of future benefit designs. The application of machine-learning methods to the setting of reference pricing will provide a framework that I or other researchers can use to evaluate other insurance benefit designs or alternative patient populations. !