Development of a Health Policy Tool for Prioritizing Health Disparities Targets
Development of a Health Policy Tool for Prioritizing Health Disparities Targets
批准号:
7803942
负责人:
Andrew H. Soll
金额:
$18.52万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-09-30 至 2011-09-29
关键词:
AcuteAddressAdministratorAdultAffectAfricanAfrican AmericanApplications GrantsAreaAssimilationsBehavioralBeliefBusinessesCaliforniaCaringCause of DeathCessation of lifeCharacteristicsChronic DiseaseCigaretteCommunitiesConsultCountyDataData ElementData SourcesDecision MakingDemographic ImpactDevelopmentDiabetes MellitusDiabetes preventionDiseaseEventFutureGeographic LocationsGoalsHIVHealthHealth PolicyHealth behaviorHealthcareHomicideHypertensionIncidenceIndividualInstitutionInterventionLettersLife Cycle StagesLife ExpectancyLongevityLos AngelesMalignant NeoplasmsMeasuresMethodsModelingMyocardial IschemiaObesityOutcomePhasePoliciesPolicy MakingPopulationPopulation ResearchPrevalencePreventiveProcessPublic HealthPublishingQuality of CareRelative (related person)ReportingResearchResourcesRisk EstimateRisk FactorsScreening procedureSimulateSmall Business Technology Transfer ResearchSmokeSystemTarget PopulationsTechnology TransferTestingTimeTobacco useUnited States National Institutes of HealthVital StatisticsWorkbasecancer typecostdemographicsdisorder riskevidence basegeographic differencehealth disparityhypercholesterolemiaimprovedinterestmetropolitanmodels and simulationmortalitypatient populationpopulation healthpublic health prioritiespublic health relevanceracial and ethnicracial and ethnic disparitiesracial differenceresponserural areasimulationsmoking cessationsocialsocioeconomicstool
中文摘要
描述(由申请人提供):消除健康方面的种族差异是公共卫生的首要目标。非裔美国人的健康状况更差,在各种疾病中获得的护理质量也更差,但解决所有这些健康和医疗保健方面的各种差异是不可行的。相反,我们必须明智地利用有限的资源,并把保健工作的那些方面作为最大限度地减少保健差距的目标。简而言之,迫切需要一项以证据为基础的消除健康方面种族差异的战略,并应优先考虑那些对减少预期寿命方面的种族差距影响最大的保健方面。然而,目前还缺乏支持这一战略的证据基础。我们以前发现,在国家一级,造成种族预期寿命差距最大的死亡原因是高血压、艾滋病毒和凶杀。在美国,人口统计和健康行为存在着巨大的地理差异。因此,人们可能会认为,造成种族健康差异的死亡原因和风险因素在地理区域以及大都市和农村地区之间也存在着巨大的差异。事实上,我们有初步数据表明,造成种族预期寿命差距的主要死因在各州之间差别很大。因此,在州和地方一级制定战略方针不仅必须确定要针对哪些风险因素和健康问题,而且还必须为适当的人口确定适当的目标。在之前的工作中,我们已经开发了差异健康政策模型,该模型模拟疾病和死亡事件,以了解种族,民族和社会经济在健康方面的差异如何在整个生命周期中发展。在第一阶段的STTR研究中,我们将测试调整该模型的可行性,并将其作为一种工具,帮助公共卫生官员就未来的研究和人口水平的干预措施做出政策决定,以减少健康差距。在这项研究中,我们将咨询加州和洛杉矶县的公共卫生官员,确定他们现有的评估健康差异和确定干预目标的方法。然后,我们将使用差异健康政策模型来确定消除美国、加利福尼亚州和洛杉矶县种族差异的优先事项。我们将重点关注具体的死亡原因,以及4种常见疾病风险因素(烟草使用、糖尿病、高血压和高胆固醇血症)、缺血性心脏病和17种特定类型的癌症对预期寿命种族差异的绝对和相对影响。我们将用美国生命统计数据中已知的预期寿命估计来检验我们预测的有效性。最后,将根据我们的模拟模型,为加州和洛杉矶县的公共卫生官员提供一份报告,确定消除预期寿命种族差异的关键优先事项。
英文摘要
DESCRIPTION (provided by applicant): Eliminating racial disparities in health is a top priority public health goal. African Americans have worse health outcomes and receive worse quality of care for a wide range of diseases, but addressing all of these various disparities in health and health care is not feasible. Instead, we must make judicious use of limited resources and target those aspects of health care that will produce the greatest reduction in health disparities. In short, an evidence- based strategy for eliminating racial disparities in health is critically needed and should prioritize those aspects of care that will have the biggest impact on reducing the racial gap in life expectancy. The evidence base to support such a strategy is currently lacking, however. We have previously found that, at the national level, the causes of death contributing most to the racial disparity in life expectancy are hypertension, HIV and homicide. Substantial geographic variations in demographics and health behaviors exist in the U.S. Thus one might expect that the causes of death and risk factors contributing most to racial disparities in health would also vary substantially by geographic region and between metropolitan and rural areas. In fact, we have preliminary data suggesting that the causes of death contributing most to the racial gap in life expectancy differ greatly from state to state. Thus, developing a strategic approach at the state and local level must not only identify which risk factors and health problems to target, but must also identify the right targets for the right population. In prior work, we have developed the Disparities Health Policy Model, which simulates disease and mortality events, to understand how racial, ethnic and socioeconomic disparities in health develops over the lifespan. In this Phase I STTR study, we will test the feasibility of adapting this model and using it as a tool to help public health officials make policy decisions about future research and population-level interventions to reduce health disparities. In this study, we will consult with public health officials with the State of California and Los Angeles County and determine their existing methods for assessing health disparities and identifying targets for interventions. We will then use the Disparities Health Policy Model to identify priorities for eliminating racial disparities in the US, California and Los Angeles County. We will focus on specific causes of death as well as the absolute and relative impact of 4 common disease risk factors (tobacco use, diabetes, hypertension and hypercholesterolemia), ischemic heart disease, and 17 specific types of cancer on the racial difference in life expectancy. We will test the validity of our projections with known life expectancy estimates from US Vital Statistics data. Finally, will produce a report for California and Los Angeles County public health officials identifying key priorities for eliminating racial disparities in life expectancy based on our simulation model.
PUBLIC HEALTH RELEVANCE: The proposed study will test the feasibility of using the Disparities Health Policy Simulation Model as a tool for setting priorities and policy decision making about future research and population-level interventions to reduce health disparities. This model estimates the contribution of various diseases, risk factors and aspects of care to racial disparities in life expectancy. This model can be tailored to a specific population, so that public health officials, policymakers, community leaders and healthcare administrators can use the results of this study to identify which diseases, risk factors and aspects of care should be prioritized as targets in future interventions and research to reduce the racial gap in life expectancy in their local populations.
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