Center for Advancing Multimorbidity Science: Profiling risk and symptom expression to develop customized therapies for adults with multiple chronic conditions (CAMS)

促进多发病科学中心：分析风险和症状表达，为患有多种慢性病的成人开发定制疗法 (CAMS)

• 批准号: 10416004
• 负责人: William Street
• 金额: $ 2.67万
• 依托单位: UNIVERSITY OF IOWA
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-13 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10416004
• 关键词: Address; Adult; Applications Grants; Biometry; Child; Clinical Research; Collaborations; Collection; Communities; Complex; Consultations; Data; Data Analytics; Data Collection; Data Management Resources; Data Set; Data Storage and Retrieval; Development; Discipline of Nursing; Distress; Elements; Faculty; Formulation; Fostering; Goals; Grant; Healthcare; Human Resources; Individual; Infrastructure; Investigation; Machine Learning; Maps; Measurement; Medication Errors; Mentors; Methods; Nurses; Nursing Faculty; Outcome; Pain; Procedures; Publications; Quality Control; Reporting; Research; Research Design; Research Personnel; Research Project Grants; Resources; Risk; Science; Series; Symptoms; Techniques; Testing; Training; Work; advanced analytics; college; data management; data mining; data quality; data sharing; data sharing networks; design; experience; improved; individualized medicine; innovation; interest; member; multidisciplinary; multimodality; multiple chronic conditions; outreach; predictive modeling; programs; research study; statistics; success; symptom science; tool

The Directors of this proposed P20 recognized that innovative, advanced analytical techniques such as predictive modeling and self organizing maps (SOM) are critical to understanding the complex relationships associated with adults experiencing multiple chronic conditions. The overall goal of the Integrative Analytics Core is to serve as a centralized resource for data management and advanced analytical techniques for clinical research projects for the Center. Through faculty and staff with expertise in using advanced analytical techniques, the Integrative Analytics Core serves as a resource for consultation/guidance, data collection, data management and data quality control. Core personnel support the Pilot PIs at all levels of investigation, beginning with the formulation of specific hypotheses, reviewing of study designs, and evaluating utility of measurement techniques. Mentoring and guidance continues with the interpretation, presentation, and publication of results, and fostering development of the projects into successful R-series grants. The specific aims of the Integrative Analytics Core are: 1. Provide multidisciplinary analytics and biostatistical support needed for research questions and/or hypothesis testing and grant proposals. 2. Facilitate the collection, management, dissemination and storage of data for projects. 3. Continue to improve the data analytics infrastructure to better handle large variables of observations and outcome (predictor) variables. 4. Create educational programs that address basic machine learning and biostatistical training needs for large and complex multimodal clinical research studies. Given the complexity of the questions being asked in this Center related to individuals with multiple chronic conditions (MCC), a centralized core for analytics is an essential element to the Center's success. The Integrative Analytics Core will be a resource for all Center Members, making available advanced analytics support and biostatistical consultation useful for both planning and executing projects. Given the current push for collection of big datasets and their re-use, this Core will provide a valuable data sharing resource. In addition, this Integrative Analytics Core will include support to Pilot PIs and offer educational programs and outreach to Center Members.

该提议的P20的董事认识到创新的高级分析技术，例如 预测建模和自我组织地图（SOM）对于理解复合物至关重要 与经历多种慢性疾病的成年人相关的关系。总体目标 综合分析核心是作为数据管理和高级的集中资源 该中心临床研究项目的分析技术。通过具有专业知识的教职员工 在使用高级分析技术时，综合分析核心是 咨询/指导，数据收集，数据管理和数据质量控制。核心人员 从各个级别的调查中支持PIS PI，首先是提出特定假设， 审查研究设计，并评估测量技术的实用性。指导和指导 继续进行解释，演示和发布结果，并促进发展的发展 这些项目成功进行了R系列赠款。综合分析核心的具体目的是： 1。提供研究问题所需的多学科分析和生物统计学支持和/或 假设检验和批准建议。 2。促进项目的收集，管理，传播和存储。 3。继续改善数据分析基础架构，以更好地处理大型变量 观察和结果（预测指标）变量。 4.创建教育计划，以解决基本的机器学习和生物统计培训 大型多模式临床研究的需求。 考虑到该中心中提出的问题的复杂性，与有多个的个人有关 慢性病（MCC），分析的集中核心是该中心的重要因素 成功。综合分析核心将成为所有中心成员的资源，可提供 高级分析支持和生物统计学咨询对计划和执行有用 项目。鉴于当前收集大数据集及其重复使用的推动，此核心将提供一个 有价值的数据共享资源。此外，该综合分析核心将包括对PIS PIS的支持 并向中心成员提供教育计划和宣传。