Research Design, Data, and Analytics Core

研究设计、数据和分析核心

• 批准号: 10683191
• 负责人: ELBERT S. HUANG
• 金额: $ 13.79万
• 依托单位: UNIVERSITY OF CHICAGO
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-01 至 2026-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10683191
• 关键词: Aging; All of Us Research Program; Area; Biometry; Black race; Businesses; Caring; Chicago; Clinical Trials; Collaborations; Communities; Community Health; Computer software; Cost Effectiveness Analysis; Data; Data Sources; Data Storage and Retrieval; Decision Analysis; Diabetes Mellitus; Diabetes prevention; Discipline; Economics; Elderly; Electronic Health Record; Epidemiology; Evaluation; Fertilization; Foundations; Genetic study; Geriatrics; Goals; Guidelines; Health; Health Care Costs; Health Insurance; Healthcare; Informatics; Infrastructure; Insurance Claim Review; Intervention; Laboratories; Life; Link; Longevity; Methodology; Methods; Modeling; National Health Insurance; Natural experiment; Outcome; Outcome Assessment; Pathway Analysis; Patient Preferences; Patients; Play; Policies; Policy Analysis; Population; Program Evaluation; Quality of Care; Quality of Life Assessment; Quality of life; Quasi-experiment; Recommendation; Recording of previous events; Research; Research Design; Research Institute; Research Methodology; Research Personnel; Research Project Summaries; Research Support; Resource-limited setting; Resources; Role; Science; Scientist; Series; Social Network; Social Sciences; Sociology; Solid; Technical Expertise; Translating; Translational Research; Universities; Vulnerable Populations; clinical epidemiology; economic evaluation; forging; genetic testing; glycemic control; health care service utilization; health economics; improved; innovation; insight; insurance claims; interest; models and simulation; novel; personalized medicine; pragmatic trial; preference; prevent; programs; psychobiology; social

PROJECT SUMMARY – Research Design, Data, and Analytics Core Quantitative analysis methods are essential for almost all forms of diabetes translational research. Along with traditional biostatistics, it has become essential to include methods from the social sciences (e.g., economics, sociology, decision sciences) in order to evaluate observational data and quasi-experimental studies, to assess outcomes such as health care costs and health care utilization, and to fully understand the long-term population level impact of novel interventions and policies. Diabetes translation research can also extend into specialized data sources such as health insurance claims data and electronic health records. At the Chicago Center for Diabetes Translation Research (CDTR), our close proximity and active collaboration with investigators based in social science departments as well as research institutes and laboratories of the University of Chicago and Northwestern University helps to ensure that our research methods have a solid theoretical foundation and a close link to innovations. The Research Design, Data, and Analytics (RDDA) Core has a strong history of accomplishments that have helped to advance quantitative methods in cost-effectiveness analysis, decision analysis, quality of life assessment, personalized medicine, and informatics. The RDDA Core provides support to numerous new and established investigators affiliated with the CCDTR as well as external diabetes investigators across the U.S. Many of our ongoing studies are the byproduct of cross- fertilization of investigators from different disciplines that leads to innovative studies of diabetes prevention and care. For this renewal, the RDDA Core will continue to provide cutting-edge analytic support for a wide range of projects in diabetes translation research ranging from clinical and pragmatic trials to cost-effectiveness analysis to natural experiments. This support is available in terms of technical expertise and material resources for analysis such as data storage and computational processing capacity, software, and simulation models. Ongoing methodological areas of support include Biostatistical Analysis, Economic Analysis (Diabetes Simulation Modeling and Business Case Analysis), Health Care Claims Analysis, Social Network Analysis, and Agent- Based Modeling. New methodological areas of support will include Informatics and Natural Experiments. The aims of the RDDA Core are: 1) To provide cutting edge quantitative analysis support for a wide range of diabetes translation research focused on improving the care and outcomes of vulnerable populations in resource- constrained settings; 2) To facilitate access to and support for analysis of specialized data sources such as national health insurance claims and electronic health records; 3) To strengthen and forge new partnerships, connections, and collaborations with leading methodologists and investigators of the CCDTR. The innovations and support of the RDDA core will help the CCDTR expand its role as one of the pioneering national leaders investigating how to translate diabetes research findings into real-world practice, with an emphasis on improving the quality of care and outcomes for vulnerable populations.

项目摘要 - 研究设计，数据和分析核心 定量分析方法对于几乎所有形式的糖尿病转化研究至关重要。以及 传统的生物统计学，包括社会科学的方法（例如经济学，， 社会学，决策科学），以评估观察数据和准实验研究，以评估 诸如医疗保健成本和医疗保健利用之类的结果，并充分了解长期人口 新颖的干预措施和政策的水平影响。糖尿病翻译研究也可以扩展到专业 健康保险索赔数据和电子健康记录等数据源。在芝加哥中心 糖尿病翻译研究（CDTR），我们与基于的研究人员的紧密近端和积极合作 社会科学系以及芝加哥大学的研究机构和实验室 西北大学有助于确保我们的研究方法具有坚实的理论基础和 与创新的紧密链接。研究设计，数据和分析（RDDA）核心具有很强的历史 在成本效益分析中有助于推进定量方法的成就，决策 分析，生活质量评估，个性化医学和信息信息。 RDDA核心为CCDTR的众多新的和已建立的调查人员提供了支持 以及美国各地的外部糖尿病研究人员，我们正在进行的许多研究是跨越的副产品 来自不同学科的研究人员的受精，导致对糖尿病预防和 关心。对于此续约，RDDA核心将继续为广泛的范围提供尖端的分析支持 糖尿病翻译研究的项目，从临床和务实试验到成本效益分析 进行自然实验。此支持可从技术专长和物质资源来获得 分析，例如数据存储和计算处理能力，软件和仿真模型。正在进行 方法学领域的支持包括生物统计分析，经济分析（糖尿病模拟） 建模和业务案例分析），医疗保健索赔分析，社交网络分析和代理 - 基于建模。支持的新方法领域将包括信息学和自然实验。 RDDA核心的目的是：1）为广泛的范围提供最先进的定量分析支持 糖尿病翻译研究的重点是改善资源中脆弱人群的护理和结果 - 设置约束； 2）促进并支持分析专业数据源的分析 国家健康保险索赔和电子健康记录； 3）加强和建立新的伙伴关系， 与CCDTR的领先方法学家和研究人员的联系以及合作。创新 RDDA核心的支持将有助于CCDTR扩大其作为开创性国家领导人之一的作用 调查如何将糖尿病研究结果转化为现实世界实践，重点是改善 脆弱人群的护理质量和结果。