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)
基本信息
- 批准号:10228135
- 负责人:
- 金额:$ 4.37万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 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:
- 关键词:Accident and Emergency departmentAffectAnxietyAutomobile DrivingCaringCase StudyCharacteristicsChronicCommunitiesCommunity HealthComplexCountyDataDatabasesDevelopmentDiabetes MellitusDiagnosticDiagnostic testsDisabled PersonsDiseaseEmergency department visitEmploymentEpilepsyEthnic OriginEthnic groupEvaluationEventFaceFoundationsGeneral PopulationGeographyHealthHealth Services AccessibilityHealthcare IndustryHeart DiseasesHispanic AmericansHispanicsHospitalizationHospitalsIndependent LivingIndividualInterventionIntractable EpilepsyKnowledgeLength of StayLifeLiteratureMedicaidMental DepressionMiningMinorityMinority GroupsModelingNative AmericansNeurologicNeurologistOutcomePharmacotherapyPlayPopulationPopulation HeterogeneityPremature MortalityPrevalenceQuality of lifeRaceResearchRoleRuralRural CommunityRural MinoritySample SizeSchoolsSeizuresSpecialistSubgroupTechniquesTransportationUnited StatesVariantVisitWorkanalytical methodclassification treescommunity settingcomorbiditycostdata miningdiverse dataethnic minority populationexperiencehealth care disparityhealth care service utilizationhealth disparityhealth disparity populationshealth equityhigh riskinterestmedical specialtiesmedication complianceminority healthmortalitynervous system disordernovelracial and ethnicracial health disparityracial minorityregression treesrural Hispanicrural arearuralityservice utilizationsocial relationshipssocial stigmasocioeconomic disadvantagestudy populationtool
项目摘要
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.
项目摘要/摘要
由于个人的相互作用,种族和少数民族人口的健康差异很复杂(例如
合并症和种族/种族),治疗(例如学术,多专科中心)和社区层面因素
(例如,服务的可用性,农村/城市)。对于这些因素的交汇处,例如农村
我声称他们的结果不仅比一般更糟
人口,但比其他西班牙裔人更糟。这些类型的种群通常很难研究
小样本量或同质性(在小组内)进行分析和解释有限 - 或接近
不可能的。
使用癫痫作为案例研究,是最大,最粗糙,种族和地理上多样的案例研究之一
有关癫痫患者(PWE)的数据,该提案旨在基于现场工作
健康差异研究。据估计,癫痫在美国影响340万人(6500万)
在全球范围内),需要专业神经科医生的治疗,进行广泛的诊断测试和
药物治疗。这种疾病对美国的医疗保健行业有重大影响;估计
表明年费用超过150亿美元。 PWE经历了高死亡率的高风险,
学校,社会关系,就业,交通和独立生活中的严重挑战,更多
比一半的PWE具有多个慢性身体和/或精神病。在这些挑战中
日常生活,PWE面临着不良健康结果的脆弱性。
在最近可用的多州上使用传统和新颖的统计和数据挖掘技术
医疗补助索赔数据我将能够在少数人口和多数人口之间确定分布
在监测人群中,在健康状况中,量化条件的星座,并确定哪个
因素在促进负面健康事件(例如住院和较长长度)方面最重要
住宿。这项研究将重点放在历史上服务不足和以前了解的PWE(例如
西班牙裔,美洲原住民和居住在农村地区的人,包括难治性癫痫的人。这些
分析将包括个人,治疗和社区层面的多层次组合,允许
更深入地了解这些差异如何出现。在我们的数据库中,我已经确定了
670,000人癫痫发作或癫痫病,其中包括147,000多名黑人,80,000名西班牙裔,5,000本人
美国人,有36.8%的县涵盖了农村。
这项工作不仅会为患有癫痫患者的成果分配提供信息,而且还可以为
证明这种分析方法的优势和劣势结合了传统和新颖的分析
概念化和量化健康分布的方法。该建议将提供基本知识
需要制定和部署干预措施以减少健康差异。
项目成果
期刊论文数量(0)
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会议论文数量(0)
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Wyatt Peter Bensken其他文献
Wyatt Peter Bensken的其他文献
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{{ truncateString('Wyatt Peter Bensken', 18)}}的其他基金
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:
10414779 - 财政年份:2021
- 资助金额:
$ 4.37万 - 项目类别:
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