Addressing Structural Disparities in Autism Spectrum Disorder through Analysis of Secondary Data (ASD3)

项目总结 自闭症谱系障碍(ASD)在美国每44名儿童中就有1名受到影响，其患病率 在过去10年中有所增加。尽管及早获得自闭症护理可以改善预后，但有色人种儿童 来自低收入家庭的儿童获得护理的时间较晚，并且有未得到满足的护理需求。虽然有一个很宽的 了解社区、社区和州水平的背景因素会影响自闭症健康 尽管存在护理差异，但这些因素在很大程度上尚未得到探索。在这项拟议的研究中，我们将汇编最多 全面且规模最大的自闭症服务使用数据集，将16个州的医疗补助申请与 来自儿童机会指数的社区级数据，以及州教育和医疗保健政策数据。 我们将使用这一强大的新数据集来揭示儿童自闭症服务使用的可修改决定因素 差距。分析将集中在诊断年龄以及药物和行为治疗的使用上。然后 我们将利用研究成果，通过参与社区和研究的共识小组，将研究付诸实施。 专家根据研究结果提出以数据为导向的可行干预措施。我们还将利用我们的研究 为了扩大自闭症差异研究领域的多样性，通过资助以下学者- 代表医学和/或有健康差异研究兴趣的人，使用结果数据集来 进行更多的数据分析。在这个项目结束时，我们希望有证据确凿的发现 关于哪些孩子访问哪些服务，哪些上下文因素影响服务访问，以及哪些 可以采取干预措施来解决自闭症健康方面的不平等问题。

PROJECT SUMMARY Autism Spectrum Disorder (ASD) affects up to 1 in 44 children in the United States, and its prevalence has increased over the past 10 years. Though early access to autism care improves outcomes, children of color and children from low-income families access care later and have unmet care needs. Though there is a broad understanding that contextual factors on the neighborhood, community, and state levels impact autism health care disparities, these factors are largely unexplored. In this proposed research, we will compile the most comprehensive and largest autism service use dataset ever, combining Medicaid claims from 16 states with community-level data from the Child Opportunity Index, as well as state education and health care policy data. We will use this powerful new data set to uncover modifiable determinants of child autism services use disparities. Analyses will focus on age of diagnosis as well as medication and behavioral therapy use. Then we will use findings to bring research to action, by engaging a consensus panel of community and research experts to suggest data-driven, feasible interventions based on study findings. We will also use our research to expand the diversity of the autism disparities research field, by sponsoring scholars who are under- represented in medicine and/or who have health disparities research interests, to use the resulting dataset to pursue additional data analyses. At the end of this project, we expect to have evidence-informed findings regarding which children access which services, which contextual factors affect services access, and which interventions can be deployed to address autism health inequities.