Doctoral Dissertation Research: The Medicaid Undercount and the Role of Program Design

博士论文研究：医疗补助计数不足和项目设计的作用

• 批准号: 1534388
• 负责人: Marc Meredith
• 金额: $ 1.6万
• 依托单位: University of Pennsylvania
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-07-15 至 2017-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1534388&HistoricalAwards=false
• 关键词: Doctoral; Dissertation; Research; Medicaid; Undercount

This doctoral dissertation research project will test whether state-level Medicaid program design and utilization explains variation in the Medicaid undercount. Medicaid is the largest source of public health insurance in the United States. Census surveys significantly underreport Medicaid use compared to administrative records. The underreporting of Medicaid use in census surveys is problematic, particularly because governmental bodies and researchers rely on this data to make administrative decisions and to determine the budgetary impacts of legislation. Inaccurate Medicaid measurement can lead to inefficient program implementation and incorrect budgetary projections. In previous studies, the undercount has been attributed largely to question wording and survey design. However, there is a lack of research into whether Medicaid program design generates response error in survey self-reports. This research will use linked census survey and administrate data to generate corrective predicted probabilities of Medicaid use for census surveys. These predicted probabilities have the potential to help policy makers better understand and account for the needs of the Medicaid population. Although focused on Medicaid in particular, this study may provide insights into the factors that affect rates of misreporting in other contexts. As a Doctoral Dissertation Research Improvement award, the project will enable a promising student to establish a strong, independent research career.This project will link census data to Medicaid administrative records to test the theory that the misreporting of Medicaid usage in census surveys is a function of variation in Medicaid program design. The investigators will run a series of logistic and fixed effects logistic regressions on this linked data to isolate which program features are related to the misreporting of Medicaid usage. The project also will use a difference-in-differences design to better isolate whether policy shifts play a causal role in the Medicaid undercount. Coefficients will be generated that can be used to predict the probability of Medicaid enrollment. These corrective measures will be made available to the Census Bureau, government agencies, and the general public.

该博士学位论文研究项目将测试州级医疗补助计划的设计和利用率是否解释了医疗补助案件的差异。 医疗补助是美国公共卫生保险的最大来源。 与行政记录相比，人口普查调查的医疗补助使用情况大大不足。 在人口普查调查中，医疗补助使用不足是有问题的，尤其是因为政府机构和研究人员依靠这些数据来做出行政决策并确定立法的预算影响。 医疗补助测量不准确会导致计划实施效率低下和预算预测不正确。 在先前的研究中，底部底部主要归因于询问措辞和调查设计。 但是，缺乏研究医疗补助计划设计是否会在调查自我报告中产生响应错误。 这项研究将使用链接的人口普查调查和管理数据来产生对人口普查调查的医疗补助使用概率的纠正概率。 这些预测的概率有可能帮助政策制定者更好地理解并满足医疗补助人群的需求。 尽管尤其是专注于医疗补助，但这项研究可能会提供有关影响其他情况下误会率的因素。 作为博士学位论文研究改进奖，该项目将使有前途的学生能够建立强大的独立研究职业。此项目将将人口普查数据与医疗补助行政记录联系起来，以测试以下理论，即在人口普查调查中错误地报告医疗补助的使用是医疗补助计划设计变化的函数。 调查人员将对此链接数据进行一系列逻辑和固定效果的逻辑回归，以隔离哪些程序功能与医疗补助使用情况的错误报告有关。 该项目还将使用差异差异设计来更好地隔离政策变化是否在医疗补助案中起因果作用。 将生成系数，可用于预测医疗补助入学率的可能性。 这些纠正措施将提供给人口普查局，政府机构和公众。