Geographic Patterns in Recurrent Stroke Rates by Gender and Race

描述(由申请人提供)：美国超过440万中风幸存者面临中风复发的风险，这使这成为美国一个重要的公共卫生问题。鉴于中风的影响，国家健康目标《2010年健康人》的一个关键目标是减轻中风的负担及其后果，特别是在老年人、少数民族和妇女等重点人群中。实现这一目标需要详细了解中风及其在全国各地的结果，以便有效和有效地实施预防工作。中风发病率和死亡率的地理和种族模式已经确定；然而，目前关于中风复发模式的信息很少。这项研究的目的是按性别和种族检查中风复发风险的地理模式，并确定风险因素、患病率以及医疗资源和利用方面的差异是否解释了这些差异。为了做到这一点，我们将使用1993-2002年的纵向关联的医疗保险数据来确定卒中发生后一年内复发的缺血性卒中的比率。我们将使用地理信息系统(GIS)来绘制全美每个县按性别和种族划分的1年复发性中风发生率地图。分析将包括分层建模，以调整个体风险因素，包括患者特征，如年龄、合并症和慢性病。此外，我们将使用分层模型对来自行为风险因素监测研究(BRFSS)的个人风险因素和县级风险因素以及从区域资源文件(ARF)收集的数据进行调整，以研究风险因素患病率和卫生保健资源/利用的变化是否影响再发中风发生率。这项研究提案将为医疗保健提供者、患者、管理者、消费者和政策制定者提供对中风复发风险最大的特定人群的洞察。这些信息对提高卫生工作效率至关重要 护理系统在提供二级中风预防和有针对性地有效预防中风方面的作用 最需要帮助的人。

Description (provided by the applicant): Over 4.4 million stroke survivors in the United States are at risk of a recurrent stroke, making this an important public health issue in the US. Given the impact of stroke, a key goal of the nation's health objectives, Healthy People 2010, is to reduce the burden of stroke and its outcomes especially among priority populations such as the elderly, ethnic minorities and women. Attainment of this goal requires a detailed understanding of stroke and its outcomes across the country so that prevention efforts can be efficiently and effectively implemented. Geographic and racial patterns in stroke incidence and mortality have been identified; however, there is currently little information about patterns of stroke recurrence. The objective of this study is to examine the geographic patterns in the risk of recurrent stroke by gender and race and to determine whether differences in risk factors prevalence and healthcare resources and utilization explain these differences. To do this we will use longitudinally linked Medicare data from 1993-2002 to determine the rate of recurrent ischemic stroke within 1-year of an incident stroke. We will use geographic information systems (GIS) to map the 1-year recurrent stroke rates for each county by gender and race across the United States. Analyses will include hierarchical modeling to adjust for individual risk factors including patient characteristics such as age, comorbid and chronic diseases. In addition, we will use hierarchical modeling to adjust for both individual risk factors as well as county level risk factors from the Behavioral Risk Factor Surveillance Study (BRFSS) and data collected from the Area Resource File (ARF), in order to study whether variations in risk factor prevalence and health care resources/utilization influence recurrent stroke rates. This study proposal will provide health care providers, patients, administrators, consumers, and policymakers with insight into specific populations at the greatest risk of recurrent stroke. This information is of vital importance in improving the efficiency of the health care system in delivering secondary stroke prevention and targeting effective prevention efforts to those individuals in the greatest need.