An Innovative Model to Predict Readmissions in Adults with Cardiovascular Disease

预测成人心血管疾病再入院的创新模型

• 批准号: 8722596
• 负责人: Matthew E. Dupre
• 金额: $ 11.58万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-08-19 至 2018-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8722596
• 关键词: Accounting; Acute; Address; Adult; Age; Aging; Attention; Award; Behavioral; Calibration; Cardiovascular Diseases; Cardiovascular system; Cessation of life; Characteristics; Chronic; Classification; Clinical; Commit; Comorbidity; Confounding Factors (Epidemiology); Cox Proportional Hazards Models; Data; Degenerative Disorder; Development; Diagnosis; Disadvantaged; Discrimination; Disease; Disease model; Documentation; Educational workshop; Effectiveness; Elderly; Environment; Etiology; Event; Faculty; Financial cost; Foundations; Funding; Geographic Locations; Goals; Hazard Models; Health; Health behavior; Healthy People 2020; Heart failure; Heterogeneity; Hospitals; Human; Individual; Interdisciplinary Study; Intervention; Knowledge; Link; Measures; Medicare claim; Mentored Research Scientist Development Award; Mentors; Mentorship; Modeling; Multivariate Analysis; Myocardial Ischemia; National Heart, Lung, and Blood Institute; Outcome; Pathogenesis; Patients; Performance; Population; Procedures; Psychosocial Factor; Public Health; Race; Research; Research Personnel; Risk; Risk Factors; Role; Science; Scientist; Series; Sex Characteristics; Socioeconomic Factors; Stroke; Surveys; Testing; Time; Training; Transient Ischemic Attack; Trees; United States; Universities; Validation; Variant; Work; adverse outcome; base; burden of illness; career; cerebrovascular; clinical risk; demographics; disease classification; exhaust; flexibility; geographic difference; high risk; hospital readmission; innovation; insight; interest; member; mortality; multidisciplinary; novel; programs; psychosocial; public health relevance; racial difference; social; socioeconomics; statistics; success; tool

DESCRIPTION (provided by applicant): The proposed project initiates a program of highly innovative interdisciplinary research that will advance our understanding of how socioeconomic, psychosocial, behavioral, and clinical factors predict hospital readmissions in adults with cardiovascular disease (CVD). Using nationally representative biennial panel data of U.S. older adults (1992-2010) that are linked with Medicare claims data, the specific aims of this research are threefold: First, describe the characteristics of adults hospitalized for one of three major forms of CVD [heart failure (HF), ischemic heart disease (IHD), and stroke] and examine how an array of largely untested patient characteristics are associated with unadjusted 30-day and 180-day all-cause readmission (or death) after discharge. Second, develop a robust risk model to predict readmissions in CVD patients using a series of multivariate hazard models and performance criteria (calibration and discrimination) to assess the non-clinical and clinical risk factors. Third, evaluate models for specific classifications of CVD (i.e., HF, IHD, and stroke) to determine whether separate models are needed to effectively predict adverse outcomes and stratify risks among cardiovascular patients. Sex, race, and geographic differences will be tested in the CVD model(s) to assess its flexibility and effectiveness for potential use in diverse clinical settings. The foundation for this application is an extension of my interests in how socia and behavioral factors impact human health and aging. However, this research marks a shift from my previous work because it demands new training in the study of CVD and the guidance necessary to integrate Medicare claims data with social survey data. Under the direction of a multidisciplinary and complementary team of mentors (Drs. Eric Peterson and Lesley Curtis) and advisors (Drs. Gerardo Heiss, Kenneth Land, and Redford Williams) who are committed to my development and the success of my research, the K01 award will provide me protected time to acquire new competency in the study of cardiovascular disease and to develop as an independent scientist. Duke University provides an ideal environment to accomplish my proposed research and career goals through intensive mentorship, specialized coursework, didactic workshops, and collaborative interactions with multidisciplinary faculty. As part of my immediate career objectives, I will use the award to accelerate my development as an independent researcher and pursue R01 funding as a junior faculty member at Duke University. My long-term goal is to establish a career pioneering the interdisciplinary study of CVD. Understanding the social, psychosocial, and behavioral determinants of adverse outcomes in adults with CVD is a major goal of Healthy People 2020 and the National Heart, Lung, and Blood Institute. I am confident that the proposed research will provide the science necessary to help identify high-risk patients and will provide new knowledge to develop innovative tools to reduce the excess burden of disease in vulnerable segments of the population.

描述（由申请人提供）：提议的项目启动了一个高度创新的跨学科研究项目，将促进我们对社会经济、心理社会、行为和临床因素如何预测成人心血管疾病（CVD）再入院的理解。使用与医疗保险索赔数据相关的具有全国代表性的两年一次的美国老年人面板数据（1992-2010），本研究的具体目的有三个：首先，描述因三种主要CVD（心力衰竭（HF）、缺血性心脏病（IHD）和中风）之一住院的成年人的特征，并检查一系列基本上未经测试的患者特征与出院后未经调整的30天和180天全因再入院（或死亡）之间的关系。其次，利用一系列多变量风险模型和性能标准（校准和区分）来评估非临床和临床风险因素，建立一个稳健的风险模型来预测心血管疾病患者的再入院情况。第三，评估CVD特定分类（如心衰、IHD和卒中）的模型，以确定是否需要单独的模型来有效预测心血管患者的不良结局和风险分层。性别、种族和地理差异将在CVD模型中进行测试，以评估其在多种疾病中潜在使用的灵活性和有效性