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

这个博士论文研究项目将测试是否州级医疗补助计划的设计和利用解释在医疗补助不足的变化。医疗补助计划是美国公共医疗保险的最大来源。与行政记录相比，人口普查调查明显低估了医疗补助的使用情况。在人口普查调查中少报医疗补助的使用是有问题的，特别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和确定立法的预算影响。不准确的医疗补助测量会导致低效的项目实施和不正确的预算预测。在以前的研究中，统计不足主要归因于问题措辞和调查设计。然而，缺乏对医疗补助计划设计是否会在调查自我报告中产生反应错误的研究。本研究将使用关联的人口普查调查和管理数据来生成用于人口普查的医疗补助使用的正确预测概率。这些预测的概率有可能帮助政策制定者更好地理解和解释医疗补助人群的需求。虽然这项研究主要集中在医疗补助上，但它可能会对其他情况下影响误报率的因素提供一些见解。作为博士论文研究进步奖，该项目将使有前途的学生建立一个强大的，独立的研究生涯。该项目将把人口普查数据与医疗补助管理记录联系起来，以检验在人口普查调查中误报医疗补助使用情况是医疗补助计划设计变化的一个功能的理论。研究人员将对这些关联数据进行一系列的逻辑和固定效应逻辑回归，以分离出哪些项目特征与误报医疗补助使用有关。该项目还将使用差异中的差异设计，以更好地隔离政策变化是否在医疗补助计划中起因果作用。将产生可用于预测医疗补助登记概率的系数。这些纠正措施将向人口普查局、政府机构和公众提供。

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.