Role of State Medicaid Policies in Improving Access to Dental Care among Low-Income Adults

国家医疗补助政策在改善低收入成年人获得牙科保健机会方面的作用

基本信息

批准号：
10851307
负责人：
Astha Singhal
金额：
$ 6.05万
依托单位：
UNIVERSITY OF FLORIDA
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-07-01 至 2024-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10851307
关键词：
Role State Medicaid Policies Improving

项目摘要

PROJECT SUMMARY The purpose of this study is to examine how access to dental care among low-income adults is impacted by state Medicaid policies regarding eligibility, dental coverage, cost-sharing and dentist reimbursement. Oral health is integral to overall health, economic productivity and well-being. Yet access to dental care continues to be a major public health problem for low-income adults, leading to untreated disease, pain, poor systemic health and substantial economic burden. In recent years, several policy changes under the Affordable Care Act (ACA) such as Medicaid expansion and dependent care coverage could significantly impact access to dental care among the poor non-elderly adults. In addition, there is extensive cross-state variation in terms of dental benefits covered for Medicaid adults. These variations provide natural experiments to examine the effect of Medicaid policies on access to dental care. Moreover, under the current health reform discussions, state Medicaid programs are anticipated to gain autonomy in resource allocation, yet may receive significantly less federal funding, making the need for robust evidence on relative effectiveness of Medicaid policy alternatives available to the states paramount. The overarching goal of this application is to advance the research career of the candidate (Dr. Singhal) by protecting her time for training and research on these critical issues in oral health policy. This goal will be accomplished through additional training in complementary disciplines of econometrics and machine learning, and their application to estimate the impacts of Medicaid coverage and payment generosities on access to dental care. The project brings together complementary secondary data from multiple sources including: large national survey data (National Health Interview Survey), administrative enrollment and claims data (Medicaid Analytic eXtract) and linked survey and claims data. Leveraging these data and training resources, this project will: 1) develop synthetic indices of Medicaid dental coverage and payment generosities; 2) estimate the effect of each policy alternative and combined generosity indices on various measures of access to dental care; and 3) predict the relative effectiveness of policy alternatives and their combinations on access to dental care. We will use econometric methods including instrumental variables, difference-in-difference and regression discontinuity models to develop the generosity indices and to estimate the impact of Medicaid generosity. To develop and validate the predictive model, we will use supervised machine learning approaches (e.g. decision tree learning) using linked survey and claims data. The results will provide evidence needed to inform future strategies to ensure efficient use of health care resources to reduce oral health disparities. The completion of this project will also enable Dr. Singhal to establish a research program as an independent research investigator with support from her multi-disciplinary mentoring and advising teams and the vibrant research community at The University of Florida.

项目概要本研究的目的是调查低收入成年人获得牙科护理的机会如何受到以下因素的影响：州有关资格、牙科保险、费用分摊和牙医报销的医疗补助政策。口服健康是整体健康、经济生产力和福祉的组成部分。然而，获得牙科护理的机会仍然存在成为低收入成年人的一个主要公共卫生问题，导致疾病得不到治疗、疼痛、系统不良健康和沉重的经济负担。近年来，平价医疗法案下的多项政策变化（平价医疗法案），例如医疗补助扩大和家属护理覆盖范围可能会显着影响获得牙科服务的机会照顾贫困非老年人。此外，在牙科方面存在广泛的跨州差异。医疗补助成人承保的福利。这些变化提供了自然实验来检验效果关于获得牙科护理的医疗补助政策。此外，在当前的医疗改革讨论中，国家医疗补助计划预计将获得资源分配的自主权，但获得的资源可能会少得多联邦资金，需要强有力的证据来证明医疗补助政策替代方案的相对有效性对各州来说至关重要。该应用程序的总体目标是促进以下领域的研究事业候选人（Singhal 博士）通过保护她在口语中这些关键问题上的培训和研究时间卫生政策。这一目标将通过补充学科的额外培训来实现计量经济学和机器学习，及其在估计医疗补助覆盖范围和影响方面的应用为获得牙科护理提供慷慨的资助。该项目汇集了互补的二手数据来自多个来源，包括：大型全国调查数据（全国健康访谈调查）、行政数据登记和索赔数据（Medicaid Analytic eXtract）以及链接的调查和索赔数据。利用这些数据和培训资源，该项目将：1）开发医疗补助牙科覆盖率的综合指数和慷慨的付款； 2) 估计每种政策选择和综合慷慨指数对获得牙科护理的各种措施； 3) 预测政策选择的相对有效性他们的组合对获得牙科护理的影响。我们将使用计量经济学方法，包括工具法变量、双重差分和不连续性回归模型来制定慷慨指数并估计医疗补助慷慨的影响。为了开发和验证预测模型，我们将使用使用链接的调查和索赔数据的监督机器学习方法（例如决策树学习）。这结果将提供所需的证据，为未来的战略提供信息，以确保有效利用医疗保健资源减少口腔健康差异。该项目的完成也将使辛哈尔博士能够建立一个在她的多学科指导的支持下，作为独立研究调查员进行研究计划以及佛罗里达大学的咨询团队和充满活力的研究社区。