The Effects of Insurance Benefit Design Innovation on Patient Health

摘要 我在健康经济学方面的研究重点是信息和有针对性的消费者成本分担 影响患者选择供应商的方式，以及激励患者选择低价产品的财务节省 供应商。我还考察了市场的另一面，如何耐心地利用信息和针对性 消费者激励措施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，如 我和加州大学伯克利分校的一名卫生经济学博士生继续在这些基础上继续发展 在兰德公司担任政策研究员期间的话题。对于我的职业生涯来说，自然的下一步是扩大这一点 研究方向不同，但以更深入的方式和使用更先进的统计方法。表演 这些领域的指导研究将帮助我成功地从指导性研究过渡到独立研究 研究。这项拟议的研究将帮助我(1)有助于更深入地了解患者的健康影响 与老龄化人口特别相关的创新保险福利设计；(2)继续 建立处理大型医疗索赔数据集的能力，并开发创新统计方面的专业知识 来自不同学科的方法；(3)获得与老龄化相关的健康服务研究的培训；(4)扩大我的 接触老龄化、卫生经济学和卫生服务研究社区；以及(5)发展我的 作为一名独立的卫生服务研究人员的能力，并为成功竞争奠定基础 R01级助学金。 在这个项目中，我建议检查结肠镜检查和药品的参考定价 减少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 进程。为此，我打算应用最近出现的新的机器学习统计方法 在计算机科学和统计领域发展起来。作为这个提议的一部分，我已经建立了一个正式的培训 计划发展这些方法方面的专业知识。这个项目将为我提供灵活性和支持，以 制定长期研究议程，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。尽管这项研究关注的是单一成本- 分享计划，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 对未来福利设计的评估。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，供我或其他研究人员用来评估其他保险福利设计 或另类患者群体。 好了！

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. !