Evaluating and Quantifying the Magnitude and Multilevel Causes of Health Disparities in Understudied Minority People with Epilepsy (EQU-ity)

评估和量化未充分研究的少数民族癫痫患者健康差异的严重程度和多层次原因 (EQU-ity)

• 批准号: 10228135
• 负责人: Wyatt Peter Bensken
• 金额: $ 4.37万
• 依托单位: CASE WESTERN RESERVE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-06-01 至 2023-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10228135
• 关键词: Accident and Emergency department; Affect; Anxiety; Automobile Driving; Caring; Case Study; Characteristics; Chronic; Communities; Community Health; Complex; County; Data; Databases; Development; Diabetes Mellitus; Diagnostic; Diagnostic tests; Disabled Persons; Disease; Emergency department visit; Employment; Epilepsy; Ethnic Origin; Ethnic group; Evaluation; Event; Face; Foundations; General Population; Geography; Health; Health Services Accessibility; Healthcare Industry; Heart Diseases; Hispanic Americans; Hispanics; Hospitalization; Hospitals; Independent Living; Individual; Intervention; Intractable Epilepsy; Knowledge; Length of Stay; Life; Literature; Medicaid; Mental Depression; Mining; Minority; Minority Groups; Modeling; Native Americans; Neurologic; Neurologist; Outcome; Pharmacotherapy; Play; Population; Population Heterogeneity; Premature Mortality; Prevalence; Quality of life; Race; Research; Role; Rural; Rural Community; Rural Minority; Sample Size; Schools; Seizures; Specialist; Subgroup; Techniques; Transportation; United States; Variant; Visit; Work; analytical method; classification trees; community setting; comorbidity; cost; data mining; diverse data; ethnic minority population; experience; health care disparity; health care service utilization; health disparity; health disparity populations; health equity; high risk; interest; medical specialties; medication compliance; minority health; mortality; nervous system disorder; novel; racial and ethnic; racial health disparity; racial minority; regression trees; rural Hispanic; rural area; rurality; service utilization; social relationships; social stigma; socioeconomic disadvantage; study population; tool

Project Summary/Abstract Health disparities for racial and ethnic minority populations are complex due to the interplay of individual (e.g. comorbidities and race/ethnicity), treatment (e.g. academic, multi-specialty centers), and community level factors (e.g. availability of services, rural/urban). For individuals at the intersection of these factors, such as rural Hispanic individuals with a high comorbidity profile, I posit that their outcomes are not only worse than the general population, but worse than other Hispanic individuals. These types populations are often difficult to study due to small sample sizes or homogeneity (within the group) making analysis and interpretation limited – or near impossible. Using epilepsy as a case study, with one of the largest and most racially, ethnically, and geographically diverse data available on people with epilepsy (PWE) this proposal seeks to build upon previous work in the field of health disparities research. Epilepsy is estimated to affect 3.4 million people in the United States (65 million worldwide) and requires treatment by specialized neurologists, with extensive diagnostic testing and pharmacotherapy. This disease has a significant impact on the United States healthcare industry; with estimates indicating an annual costs of over $15 billion. PWE experience a high risk of premature mortality, as well as serious challenges in school, social relationships, employment, transportation, and independent living, with more than half of PWE having multiple chronic physical and/or psychiatric conditions. With these challenges in everyday life, PWE are at a heightened vulnerability for poor health outcomes. Using both traditional and novel statistical and data mining techniques on the most recently available multi-state Medicaid claims data I will be able to identify disparities, both between minority and majority populations as well as within monitory populations, in health outcomes, quantify constellations of conditions, and identify which factors are most important in contributing to negative health events, such as hospitalizations and longer length of stay. This study will have an emphasis on historically underserved and previously understudied PWE such as Hispanics, Native Americans, and those living in rural areas, including those with refractory epilepsy. These analyses will include multi-level combinations at the individual, treatment, and community level allowing for a deeper understanding of how these disparities emerge. In our database of 17 states I have identified over 670,000 people with seizure or epilepsy including over 147,000 Black individuals, 80,000 Hispanics, 5,000 Native Americans, with 36.8% of the counties covered being rural. This work will inform not just the disparities in outcomes for people living with epilepsy, but also serves to demonstrate the strengths and weakness of this analytic approach which combines traditional and novel analytic methods to conceptualize and quantify health disparities. This proposal will provide the foundational knowledge needed to develop and deploy interventions to reduce health disparities.

项目总结/摘要 由于个体（例如，种族和族裔）之间的相互作用，种族和族裔少数群体的健康差异是复杂的。 合并症和人种/种族）、治疗（例如学术、多专科中心）和社区水平因素 (e.g.农村/城市的服务提供情况）。对于处于这些因素交叉点的个人，如农村 西班牙裔个体具有高comorbidity轮廓，我认为他们的结果不仅比一般更糟， 比其他西班牙人更糟糕。这些类型的人群往往很难研究，因为 小样本量或同质性（组内）使得分析和解释有限-或接近 不可能的 使用癫痫作为一个案例研究，其中一个最大的和最种族，民族和地理多样性 癫痫患者（PWE）的现有数据，该提案旨在建立在以前在以下领域的工作基础上： 健康差异研究。据估计，美国有340万人（6500万人）患有癫痫病。 世界各地），需要由专门的神经科医生进行治疗，进行广泛的诊断测试， 药物治疗.这种疾病对美国医疗保健行业产生了重大影响;估计 表明每年的成本超过150亿美元。PWE经历过早死亡的高风险，以及 在学校、社会关系、就业、交通和独立生活方面面临严重挑战， 超过一半的PWE患有多种慢性身体和/或精神疾病。面对这些挑战， 在日常生活中，PWE更容易受到不良健康结果的影响。 使用传统的和新的统计和数据挖掘技术对最近可用的多状态 医疗补助索赔数据我将能够确定差异，无论是少数民族和多数人口以及 在监测人群中，在健康结果中，量化条件的星座，并确定 在导致负面健康事件方面，最重要的因素是住院和较长的时间。 留下来。这项研究将重点放在历史上服务不足和以前研究不足的PWE，如 西班牙裔，美洲原住民，以及生活在农村地区的人，包括那些患有难治性癫痫的人。这些 分析将包括个人、治疗和社区层面的多层次组合， 更深入地了解这些差异如何出现。在我们的17个州的数据库中， 670，000名癫痫发作或癫痫患者，包括147，000多名黑人，80，000名西班牙裔，5，000名原住民 美国，36.8%的县覆盖农村。 这项工作不仅将告知癫痫患者结果的差异，而且还将有助于 论证了这种分析方法的优点和缺点，它结合了传统的和新的分析方法， 概念化和量化健康差距的方法。该提案将提供基础知识 需要制定和部署干预措施，以减少健康差距。