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.

项目总结/摘要 研究核心：统计学，信息学和定性方法核心 统计、信息学和定性方法（SIQM）核心将促进和支持农村卫生保健 配送科学遵循综合的混合方法研究框架，并与 社区参与和外联（CEO）核心，我们寻求优化的严谨性，上下文，和进步 农村卫生保健提供科学中心的研究。SIQM核心的首要目标是 通过定量和定性相结合，提高农村卫生保健重要课题研究的严谨性 数据分析变成一个双向系统，一个输入到另一个。具体的重点领域包括 支持获得和开发独特的数据集，创新的统计建模， 准确的统计推断、信息学和分析学的扩展以及数据的敏锐性和影响力 视觉化 核心将通过开发一个强大的研究数据仓库来支持中心的研究人员， 响应他们的研究目标，并在他们的发展作为研究人员和最终毕业双重援助 独立融资。核心将使用包含健康保险索赔、疾病 登记处，美国人口普查，电子健康记录，地理空间和其他来源和形式的数据。到 作为补充，将通过调查、访谈， 社区参与工作室，以及其他形式的混合方法研究。数据存储库将增长 有时间在广度和深度上支持社区的需求和优先事项，并支持研究人员， 扩大数据的范围，在他们进一步开展工作和准备自己的工作时， 独立提案。除了集成和管理数据外，SIQM Core还将通过以下方式支持项目： 开发和完善先进的统计方法，包括分层，纵向和地理空间 建模;解释观测数据中混杂因素的因果推理方法（差异中的差异 设计，倾向评分方法）;和社会网络分析。核心将创建一个跨 该中心致力于识别、共享和应用创新的统计、地理信息学、数据科学和 质量方法，以协助每个研究项目负责人。一旦建立，SIQM核心将协调 数据和方法，分享新的方法解决方案，并概括这些方法供将来使用。