Development of Hierarchical Neighborhood Data Regarding Cancer in the Elderly

有关老年人癌症的分层邻域数据的开发

• 批准号: 7493419
• 负责人: ELIZABETH B LAMONT
• 金额: $ 17.02万
• 依托单位: HARVARD MEDICAL SCHOOL
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-15 至 2010-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7493419
• 关键词: Address; Affect; Americas; Area; Atlases; Cancer Patient; Caring; Cause of Death; Censuses; Cessation of life; Characteristics; Clinical; Code; County; Crime; Data; Data Set; Data Sources; Development; Diagnosis; Diagnostic Neoplasm Staging; Disease; Disease Outcome; Economics; Elderly; Environment; Environmental Exposure; Future; Geographic Locations; Geography; Health; Health Policy; Health Service Area; Health Services; Health Services Accessibility; Health Status; Health behavior; Healthcare; Hospitals; Individual; Knowledge; Life; Link; Localized; Malignant Neoplasms; Measures; Mediating; Medical; Medicare; Morbidity - disease rate; Neighborhoods; Outcome; Patients; Personal Satisfaction; Physicians; Population; Poverty; Public Health; Purpose; Race; Range; Reporting; Research; Research Infrastructure; Resolution; Resources; Role; Sampling; Services; Site; Small-Area Variations; Social Sciences; Social support; Socioeconomic Status; Stage at Diagnosis; Staging; Subgroup; Techniques; Work; Zip Code; base; beneficiary; cancer care; cancer therapy; cohort; experience; geographic difference; mortality; neoplasm registry; novel; older patient; residence; social; tumor

DESCRIPTION (provided by applicant): People living in different areas may differ in their health status because the residents differ in characteristics that influence health (e.g., demographic attributes, socioeconomic status, baseline morbidity) and/or because places differ in characteristics that influence the health of residents, such as neighborhood factors (e.g., local wealth, crime, residential stability) or medical service factors (e.g., physician supply, availability of specialized care). Here, we propose to assemble a data set that will allow us, in subsequent work, to examine the impact of place, defined at two different levels of spatial resolution, on cancer course in the elderly. Our first aim is to build a novel, three-level, hierarchical data set about an inception cohort of elderly Medicare beneficiaries diagnosed with cancer in 11 US regions during 1998-2002. There will be 550,000 individual patients drawn from the SEER cancer registry at level I, linked by Census tract of residence to information about their neighborhoods (N=8,790) at level II, and linked by their ZIP code to information about their health service areas (HSAs) (N=304) at level III. Sources of data include the SEER-Medicare data for level I variables, US Census data and other data for level II variables, and Dartmouth Atlas data for level III variables. Individual- level outcome variables include cancer stage at presentation, receipt of recommended anti-cancer therapies, and survival. The data set will also contain information about the hospitals at which individuals received their cancer care. Our second aim is to examine the relationships among variables measured at the two spatial levels in order to describe, for example, whether rich neighborhoods tend to be clustered in HSAs that are well endowed with medical infrastructure. Ultimately, analyses of this data set will allow us to distinguish the role of the individual (level I) from the roles of the two spatially nested geographic areas, i.e., micro neighborhood (level II) and macro health service area (level III) in determining illness course in cancer patients. Other analyses could also ultimately be done in order to evaluate the possible mediating role of the quality of hospitals used by patients in the relationship between place and individual outcomes. This work based on a national sample of cancer patients is relevant to public health since it will: help localize the level (individual versus neighborhood versus health service area) at which deficiencies in cancer care and outcomes in the elderly may arise; help explain racial and economic disparities in health outcomes; and address determinants of the course of patients' cancer, a leading cause of death.

描述（由申请人提供）：居住在不同地区的人们的健康状况可能会有所不同，因为居民影响健康的特征（例如，人口统计属性、社会经济地位、基线发病率）不同，和/或因为地方影响居民健康的特征不同，例如邻里因素（例如，当地财富、犯罪、居住稳定性）或医疗服务因素（例如，医生供应、专业护理的可用性）。在这里，我们建议收集一个数据集，使我们能够在后续工作中检查以两种不同空间分辨率水平定义的地点对老年人癌症病程的影响。我们的第一个目标是建立一个新颖的三级分层数据集，该数据集涉及 1998 年至 2002 年期间美国 11 个地区诊断患有癌症的老年医疗保险受益人的初始队列。将从 I 级 SEER 癌症登记处抽取 550,000 名患者个体，通过人口普查居住区与 II 级的社区信息 (N=8,790) 相关联，并通过邮政编码与 III 级的健康服务区 (HSA) (N=304) 信息相关联。数据来源包括 I 级变量的 SEER-Medicare 数据、II 级变量的美国人口普查数据和其他数据以及 III 级变量的达特茅斯地图集数据。个体水平的结果变量包括就诊时的癌症分期、接受推荐的抗癌治疗以及生存率。该数据集还将包含有关个人接受癌症治疗的医院的信息。我们的第二个目标是检查在两个空间层面测量的变量之间的关系，以便描述富裕社区是否倾向于聚集在医疗基础设施丰富的 HSA 中。最终，对该数据集的分析将使我们能够区分个体（I 级）的作用与两个空间嵌套地理区域（即微观社区（II 级）和宏观卫生服务区（III 级））在确定癌症患者病程中的作用。最终还可以进行其他分析，以评估患者所使用的医院质量在地点和个人结果之间的关系中可能发挥的中介作用。这项基于全国癌症患者样本的工作与公共卫生相关，因为它将： 帮助确定老年人癌症护理和结果可能出现缺陷的水平（个人与社区与卫生服务区）；帮助解释健康结果中的种族和经济差异；并解决患者癌症病程的决定因素，癌症是导致死亡的主要原因。