DREAMS Translational Core - Methods and Data Integration (MDI)

DREAMS 转化核心 - 方法和数据集成 (MDI)

• 批准号: 10476573
• 负责人: Andrew John Karter
• 金额: $ 14.71万
• 依托单位: KAISER FOUNDATION RESEARCH INSTITUTE
• 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 2026-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10476573
• 关键词: Area; Artificial Intelligence; Biological Markers; Caring; Clinical; Communities; Community Health; Consult; Cost Effectiveness Analysis; Data; Data Collection; Data Sources; Development; Diabetes Mellitus; Diabetes prevention; Diffuse; Engineering; English Language; Ensure; Environment; Ethnic Origin; Evaluation; Faculty; Funding; Generations; Goals; Health; Health Policy; Health Services Research; Health system; Healthcare Systems; Individual; Inequality; Intervention; Intervention Studies; Knowledge; Longevity; Machine Learning; Mentors; Methodology; Methods; Mission; Modeling; Monitor; National Institute of Diabetes and Digestive and Kidney Diseases; Natural experiment; Neighborhoods; Non-Insulin-Dependent Diabetes Mellitus; Patients; Policies; Policy Research; Population; Prevention; Public Health; Race; Research; Research Methodology; Research Personnel; Research Project Grants; Risk; Running; Rural; Science; Site; Social Policies; Socioeconomic Status; Source; Statistical Methods; System; Techniques; Testing; Translational Research; Translations; Vulnerable Populations; analytical method; base; bench to bedside; care delivery; care systems; causal model; clinical care; comparative effectiveness; comparative effectiveness analysis; data integration; data resource; deprivation; design; diabetes risk; evidence base; health data; health disparity; health economics; health equity; health equity promotion; health inequalities; health literacy; implementation science; improved; innovation; models and simulation; novel; patient population; population health; risk stratification; social; translational potential; translational scientist; uptake

Project Summary/Abstract: Methods and Data Integration (MDI) Core Over the last decade, there have been substantive advances in analytic research methods and the introduction of novel sources and methods of data collection for translational research; these offer tremendous potential for improving the prevention and management of type 2 diabetes. As one of two translational research cores within the Diabetes Research for Equity through Advanced Multilevel Science Center for Diabetes Translational Research (DREAMS-CDTR), the Methods and Data Integration (MDI) Core promote the application of innovative methods and the use of novel data sources that facilitate two overarching priorities of the CDTR: a) design and optimized targeting and tailoring of diabetes-related interventions and public health policy to promote health equity and reduce inequalities, and b) to monitor the impact of innovations in care delivery, public health and social policy on existing health inequalities. Diabetes policy research increasingly relies on methodological expertise in five key areas: (a) natural experiments research; (b) implementation science; (c) health economics including comparative effectiveness and cost-effectiveness analysis; (d) simulation modeling; and (e) machine learning. The MDI core mission is to promote those methods and data to facilitate policy research in diabetes and health equity. The MDI Core will promote technological advances in data and research methods that can be applied to support interventions in the T2-T4 translational research continuum ranging from ‘bench-to-bedside’ research, clinical care and health services research, community-based intervention research, implementation sciences research, comparative effectiveness analysis, all the way to agent-based simulation models that influence policy, systems and environments. We will support a research environment that disseminates new statistical and analytic approaches, such as hierarchical models, causal modeling, machine learning and artificial intelligence techniques, and technological advances in data sources such as lab-based biomarkers, remotely collected health data, and population health data. These goals will be accomplished by 1) Mentoring junior investigators within our DREAMS-CDTR research center, 2.) Providing evidence-based consulting to CDTR, health system, and community partners, and 3.) Disseminating knowledge of novel research methods and data resources facilitating multilevel diabetes translational research and analysis of its impact on equity in diabetes care and prevention to research sites within our CTDR, among all NIDDK-funded CDTRs and the broader research and public health community.

项目摘要/摘要：方法和数据集成(MDI)核心 在过去的十年里，在分析研究方法和引入 为翻译研究收集数据的新来源和方法；这些提供了巨大的潜力 加强2型糖尿病的预防和管理。作为两个翻译研究核心之一 在糖尿病研究中通过先进的多层次糖尿病科学中心实现公平 翻译研究(DREAMS-CDTR)、方法和数据集成(MDI)核心促进 应用创新方法和使用新的数据来源，以促进以下两个总体优先事项 CDTR：a)设计和优化糖尿病相关干预措施和公共卫生的目标和量身定做 促进卫生公平和减少不平等的政策，以及b)监测保健创新的影响 关于现有健康不平等的提供、公共卫生和社会政策。 糖尿病政策研究越来越依赖于五个关键领域的方法专门知识：(A)自然 实验研究；(B)实施科学；(C)保健经济学，包括比较有效性 和成本效益分析；(D)模拟建模；(E)机器学习。MDI的核心任务是 推广这些方法和数据，以促进糖尿病和健康公平方面的政策研究。 MDI核心将促进数据和研究方法的技术进步，可应用于 支持T2-T4转化研究连续体中的干预措施，范围从‘长凳到床边’研究， 临床护理和卫生服务研究、社区干预研究、实施科学 研究、比较效果分析，一直到基于代理的仿真模型的影响 政策、制度和环境。我们将支持一个传播新统计数据的研究环境 以及分析方法，如分层模型、因果建模、机器学习和人工智能 远程智能技术和数据源(如基于实验室的生物标志物)的技术进步 收集的健康数据和人口健康数据。这些目标将通过1)辅导少年来实现 我们梦想中的调查人员-CDTR研究中心，2。)为疾病控制与预防中心提供循证咨询， 卫生系统和社区合作伙伴，以及3.)传播新的研究方法和数据的知识 促进多水平糖尿病转化研究的资源及其对糖尿病股权的影响分析 在NIDDK资助的所有疾病控制与预防中心和更广泛的机构中，对我们CTDR内的研究地点进行护理和预防 研究和公共卫生社区。