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 近十年来，分析研究方法和引入方法取得了实质性进展。 转化研究的新数据来源和数据收集方法提供了巨大的潜力； 改善 2 型糖尿病的预防和管理 作为两个转化研究核心之一。 通过高级多层次糖尿病科学中心进行糖尿病公平研究 转化研究 (DREAMS-CDTR)、方法和数据集成 (MDI) 核心促进 应用创新方法和使用新数据源，促进两个首要优先事项 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定制 促进健康公平和减少不平等的政策，b) 监测护理创新的影响 关于现有健康不平等的交付、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学专业知识：(a) 自然 实验研究；(b) 实施科学；(c) 卫生经济学，包括比较有效性 成本效益分析；(d) 仿真建模；以及 (e) 机器学习。 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，这些技术可应用于 支持 T2-T4 转化研究连续体的干预措施，范围从“实验室到临床”研究， 临床护理和健康服务研究、基于社区的干预研究、实施科学 研究、比较有效性分析，一直到基于代理的模拟模型都会影响 我们将支持传播新统计数据的研究环境。 和分析方法，例如层次模型、因果模型、机器学习和人工 情报技术和数据源的技术进步，例如基于实验室的生物标记物，远程 收集的健康数据和人口健康数据将通过以下方式实现：1) 指导青少年。 我们的 DREAMS-CDTR 研究中心的研究人员，2.) 向 CDTR 提供基于证据的咨询， 卫生系统和社区合作伙伴，以及 3.) 传播新颖研究方法和数据的知识 促进多层次糖尿病转化研究及其对糖尿病公平性影响的分析的资源 在我们的 CTDR、所有 NIDDK 资助的 CDTR 和更广泛的范围内对研究地点进行护理和预防 研究和公共卫生界。