LEAP Methods Core

LEAP 方法核心

• 批准号: 10623804
• 负责人: MIGUEL HERNAN
• 金额: $ 45.69万
• 依托单位: MCLEAN HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-05-15 至 2028-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10623804
• 关键词: Address; Algorithms; Area; Caring; Characteristics; Classification; Clinic; Clinical; Clinical Data; Clinical Management; Collaborations; Collection; Communities; Comparative Effectiveness Research; Data; Data Analyses; Data Collection; Data Security; Data Set; Data Sources; Databases; Decision Making; Development; Discipline; Electronic Health Record; Empirical Research; Ensure; Epidemiology; Funding; Generations; Health Insurance; Health Policy; Health system; Healthcare; Incubators; Infrastructure; Knowledge; Laboratories; Lead; Link; Machine Learning; Massachusetts; Medicine; Mental Health; Methodology; Methods; Modeling; National Institute of Mental Health; Outcome; Patients; Population; Procedures; Prospective cohort; Psychiatry; Public Health Schools; Randomized, Controlled Trials; Research; Research Design; Research Methodology; Research Personnel; Research Project Grants; Resources; Secure; Services; Techniques; Technology; Thinness; Time; Training; Translational Research; Work; analytical method; clinical database; clinical predictors; compare effectiveness; computerized tools; computing resources; data integration; data management; data repository; data resource; data submission; diverse data; early psychosis; effective intervention; first episode psychosis; high dimensionality; improved; innovation; insurance claims; large datasets; longitudinal dataset; machine learning algorithm; novel; randomized trial; response; socioeconomics; statistics; theories

1. Abstract The Methods Core of the LEAP Center will continue to work on a data platform that integrates information obtained at different levels of care of First Episode Psychosis (FEP) patients and will develop the computational tools that will allow Center investigators to access and analyze the integrated databases. Specifically, the Methods Core will provide the methodological expertise for the application of state-of-the-art machine leaning algorithms for clinical prediction, and for the application of cutting-edge causal inference techniques for comparative effectiveness research. First, the Methods Core will provide the database infrastructure to securely store, harmonize, link, manage, and analyze the high-dimensional databases that will be used by Center investigators. These databases include detailed clinical, demographic, socioeconomic information for each FEP patient, plus randomized controlled trial data, electronic health records and insurance claims, and longitudinal datasets on clinics characteristics and services offered. Many of these data sources have never been used for mental health research, either independently or in concert. We will create the only U.S.-based consortium approaching a thousand FEP patients. Second, the Methods Core will ensure that recent advances in clinical prediction and comparative effectiveness research can be applied to large databases of FEP patients and will be an incubator of methodological research in response to the requirements of the Center projects. It will serve as a platform for a synergistic collaboration between experts in several disciplines—psychiatry, statistics, epidemiology, and health policy—who will engage in high-impact studies to improve the clinical outcomes of FEP patients. Our project also provides a potential model for data consolidation and expertise sharing across multiple NIMH Alacrity P50 Centers. In summary, the Methods Core will support the data analysis activities throughout all projects, and will disseminate methodological advances amongst the community of mental health researchers and will therefore function as a national resource that facilitates the use of innovative methods beyond the Center investigators.

1.摘要 LEAP中心的方法核心将继续致力于整合信息的数据平台 获得不同层次的照顾首发精神病（FEP）患者，并将制定 这些计算工具将允许中心研究人员访问和分析综合数据库。 具体而言，方法核心将为应用最先进的方法提供方法学专业知识。 用于临床预测的机器学习算法，以及尖端因果推理的应用 比较有效性研究的技术。首先，方法核心将提供数据库 安全存储、协调、链接、管理和分析高维数据库的基础设施， 供中心研究人员使用。这些数据库包括详细的临床，人口统计，社会经济 每个FEP患者的信息，加上随机对照试验数据，电子健康记录和保险 索赔和关于诊所特征和提供的服务的纵向数据集。这些数据源中的许多 从来没有被用于心理健康研究，无论是独立的还是一致的。我们将创造唯一 美国--一个基于财团的方法接近一千FEP患者。第二，核心方法将确保 临床预测和比较有效性研究的最新进展可以应用于大规模 FEP患者的数据库，并将成为方法学研究的孵化器，以响应 中心项目的要求。它将成为专家之间协同合作的平台 在精神病学、统计学、流行病学和卫生政策等几个学科中，世卫组织将参与高影响力的 改善FEP患者临床结局的研究。我们的项目还提供了一个潜在的数据模型 在多个NIMH Alacrity P50中心之间进行整合和专业知识共享。总之，方法 核心方案将支持所有项目的数据分析活动，并将传播方法论， 在精神卫生研究人员社区中取得进展，因此将作为一个国家 这是一种资源，有助于使用中心研究人员以外的创新方法。