Statistics, Informatics & Qualitative Methods (SIQM) Core

统计学、信息学

• 批准号: 10555007
• 负责人: Alistair James O'MALLEY
• 金额: $ 38.44万
• 依托单位: DARTMOUTH-HITCHCOCK CLINIC
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-04-01 至 2028-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10555007
• 关键词: Address; Area; Censuses; Characteristics; Clinic; Collaborations; Communities; Community Outreach; Complement; Consultations; Data; Data Analyses; Data Collection; Data Science; Data Set; Data Sources; Dependence; Development; Disease; Disparity population; Electronic Health Record; Ensure; Environment; Feeds; Fostering; Funding; Future; Goals; Health; Health Care Research; Health Insurance; Healthcare; Heterogeneity; Informatics; Infrastructure; Interview; Link; Maine; Maps; Measures; Medical center; Methodology; Methods; Modeling; Nature; New England; New Hampshire; Pathway Analysis; Persons; Population; Qualitative Methods; Reporting; Research; Research Design; Research Methodology; Research Personnel; Research Project Grants; Research Support; Resources; Rural; Rural Community; Rural Health; Rural Health Centers; Rural Population; Sample Size; Science; Scoring Method; Services; Social Network; Source; Statistical Methods; Statistical Models; Structure; Surveys; System; Time; Vermont; Visualization; Work; analytical method; clinical care; community engagement; data infrastructure; data management; data repository; data visualization; data warehouse; design; disease registry; diverse data; health care delivery; health care service; improved; innovation; insurance claims; interest; novel; practice-based research network; primary care practice; repository; rural healthcare; rural patients; social health determinants; statistics

PROJECT SUMMARY/ABSTRACT Research Core: The Statistics, Informatics, and Qualitative Methods Core The Statistics, Informatics, and Qualitative Methods (SIQM) Core will promote and support rural health care delivery science. Following an integrated mixed-methods research framework and partnering with the Community Engagement and Outreach (CEO) Core, we seek to optimize the rigor, context, and advancement of research across the Center for Rural Health Care Delivery Science. The SIQM Core’s overarching goal is to improve the rigor of the research on important rural health care topics by integrating quantitative and qualitative data analyses into a two-way system where one feeds into the other. The specific areas of focus include supporting the attainment and development of unique datasets, innovative statistical modeling, the construction of accurate statistical inferences, the expansion of informatics and analytics, and the acuity and impact of data visualization. The Core will support the Center’s researchers by developing a robust research data warehouse that responds to their research goals and dually aids in their development as researchers and ultimate graduation to independent funding. The Core will work with datasets that incorporate health insurance claims, disease registry, US Census, electronic health records, geospatial and other sources and forms of data. To complement this, de novo data will be obtained from community stakeholders using surveys, interviews, Community-Engagement Studios, and other forms of mixed-methods research. The data repository will grow with time in breadth and depth to support community needs and priorities and support researchers by expanding the scope of data, to which they will have access as they further their work and prepare their own independent proposals. In addition to integrating and managing data, the SIQM Core will support projects by developing and refining cutting-edge statistical methods, including hierarchical, longitudinal, and geospatial modeling; causal inference methods to account for confounding in observational data (difference-in-difference designs, propensity score methods); and social network analysis. The Core will create an environment across the Center for identifying, sharing, and applying innovative statistical, geoinformatics, data science, and qualitative methods to assist each Research Project Leader. Once established, the SIQM Core will coordinate data and methods, share novel methodological solutions, and generalize these methods for future use.

项目摘要/摘要 研究核心：统计，信息学和定性方法核心 统计，信息学和定性方法（SIQM）核心将促进和支持粗糙的医疗保健 交付科学。遵循集成的混合方法研究框架，并与 社区参与和外展（CEO）核心，我们试图优化严格，背景和进步 农村卫生保健分娩中心的研究。 SIQM核心的总体目标是 通过整合定量和定性，改善有关重要粗糙医疗保健主题的严格研究 数据分析到一个双向系统中，一个系统将其输入另一个系统。重点的特定领域包括 支持独特数据集的尝试和开发，创新的统计建模，构造 准确的统计推断，信息和分析的扩展以及数据的敏锐和影响 可视化。 核心将通过开发强大的研究数据仓库来支持该中心的研究人员 回应他们的研究目标，并双重地帮助他们作为研究人员的发展和最终毕业 获得独立资金。核心将与包含健康保险索赔，疾病的数据集合作 注册表，美国人口普查，电子健康记录，地理空间以及其他资料和形式的数据。到 补充这一点，将使用调查，访谈， 社区参与工作室和其他形式的混合方法研究。数据存储库将增长 随着时间的广度和深度，以支持社区需求和优先事项，并支持研究人员 扩大数据范围，他们将在进一步的工作中可以访问并准备自己的工作范围 独立的建议。除了集成和管理数据外，SIQM核心还将支持项目 开发和完善尖端统计方法，包括等级，纵向和地理空间 造型;因果推理方法，以说明观察数据中的混杂（差异差异） 设计，承诺得分方法）；和社交网络分析。核心将在跨越环境 识别，共享和应用创新统计，地球信息学，数据科学和数据的中心 为每个研究项目负责人提供帮助的定性方法。建立后，SIQM核心将协调 数据和方法，共享新颖的方法论解决方案，并概括这些方法以供将来使用。