Evidence based Interventions to address Structure, System and Population Inequities in COVID-19 Screening

解决 COVID-19 筛查中的结构、系统和人口不平等问题的循证干预措施

• 批准号: 10447381
• 负责人: Jan Kirk Carney
• 金额: $ 61.9万
• 依托单位: UNIVERSITY OF VERMONT & ST AGRIC COLLEGE
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-01-18 至 2023-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10447381
• 关键词: Address; Adult; American; Behavior; Behavioral; Black, Indigenous, People of Color; COVID-19; COVID-19 disparity; COVID-19 pandemic; COVID-19 screening; COVID-19 testing; COVID-19 treatment; Caring; Centers for Disease Control and Prevention (U.S.); Communication; Communities; Community Health Aides; Complex; Data; Databases; Decision Making; Elderly; Evidence based intervention; Excess Mortality; Focus Groups; Geographic Information Systems; Grant; Health; Health Personnel; Health system; Healthcare; Home; Hospitalization; Individual; Inequality; Inpatients; Intervention; Location; Maine; Measures; Medical; Methods; Modeling; New England; Outcome; Patients; Policies; Population; Predictive Factor; Probability; Provider; Public Health; Qualitative Methods; Ramp; Reduce health disparities; Research; Resources; Risk; Rural; Rural Community; Rural Health; Rural Population; Sampling; Source; Structure; System; Testing; Underserved Population; Vermont; Vulnerable Populations; Work; bed capacity; care delivery; comorbidity; density; design; disadvantaged population; experience; experimental study; health communication; indexing; innovation; medical vulnerability; payment; remote communities; severe COVID-19; social; social vulnerability; vaccine delivery; vulnerable community

The purpose of this proposal is to identify individual, community (population) and structural factors associated with lower rates of Covid-19 testing in Northern New England (NNE), with a focus on underserved and vulnerable populations. Our study includes several COVID-19 medically and/or socially vulnerable populations: communities with high levels of social vulnerability; community-dwelling older adults; individuals with medical comorbidities known to increase risk of severe COVID-19 and, particularly, rural and remote communities. Analytically, we will first qualitatively estimate individual, population and structural factors associated with higher or lower probability of having been tested for COVID-19 by combine comprehensive all- payer claims data across two states with state-level COVID-19 testing data and the CDC vulnerable community index. We will also assess the geospatial distribution of disparities in COVID-19 testing in NNE using geographic information system methods to examine factors like testing center density and distance on testing rates. We will exploit differences in structure between Vermont and Maine to identify system level factors, including provider accessibility, testing availability and provider payment rules. Our key outcomes will be COVID-19 testing, hospitalizations and excess mortality among underserved and vulnerable populations in NNE. We will augment the quantitative analysis with focus groups to identify additional barriers to testing. We will conduct multiple focus groups with individuals from vulnerable populations to identify barriers to COVID-19 testing. Once we have identified the individual, community (population) and structural factors that create barriers to COVID-19 testing and excess mortality, we will test potential interventions in two different ways, First, we will develop and deploy a Discrete Choice Experiment (DCE) both in vulnerable communities in NNE and in a nationally representative sample of rural adults to test optimal strategies to increase testing using hypothetical scenarios. Second, we will test the effect of targeted communication using a rural communication network using optimal communication strategies to facilitate increased testing and test if the communications change individual behavior and reduce health disparities. This study will be conducted in partnership with the Department of Health in both Vermont and Maine and numerous community partners.

该提案的目的是确定个人，社区（人口）和结构性因素 新英格兰北部（NNE）的COVID-19测试率较低，重点是服务不足和 脆弱的人群。我们的研究包括医学和/或社会脆弱的几个Covid-19 人口：社会脆弱性高的社区；居住在社区的老年人；个人 已知的医疗合并症会增加严重的Covid-19风险，尤其是农村和偏远 社区。从分析上，我们将首先定性地估计个人，人口和结构性因素 与通过联合全面的全能测试了Covid-19的较高或更低的概率有关 付款人要求在两个州索赔数据，该州具有州级COVID-19测试数据和CDC脆弱性 社区指数。我们还将评估NNE中Covid-19测试中差异的地理空间分布 使用地理信息系统方法来检查测试中心密度和距离等因素 测试率。我们将利用佛蒙特州和缅因州之间的结构差异来识别系统级别 因素，包括提供商可访问性，测试可用性和提供商付款规则。我们的关键结果将 在服务不足和脆弱的人群中进行19次测试，住院和过量死亡率 nne。我们将通过焦点组增加定量分析，以识别测试的其他障碍。我们 将与来自弱势群体的个人进行多个焦点小组，以识别Covid-19的障碍 测试。 一旦我们确定了个人，社区（人口）和结构性因素，从而造成了障碍 COVID-19测试和过量死亡率，我们将以两种不同的方式测试潜在干预措施，首先，我们将 在NNE和A中开发和部署一个离散选择实验（DCE） 全国代表性的农村成年人样本，以测试最佳策略以使用假设的 方案。其次，我们将使用农村通信网络测试目标通信的效果 使用最佳的沟通策略来促进增加测试并测试通信是否发生变化 个人行为并减少健康差异。这项研究将与 佛蒙特州和缅因州以及众多社区合作伙伴的卫生部。