Data Management

数据管理

• 批准号: 6960270
• 负责人: Peyton A Eggleston
• 金额: $ 11.37万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-05-07 至 2008-10-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6960270
• 关键词: asthma; biomedical facility; children; clinical research; computer data analysis; data collection; data collection methodology /evaluation; data management; experimental designs; health science research support; human data; human subject; patient /disease registry; respiratory disorder epidemiology; statistics /biometry; urban area

Asthma morbidity is high among inner-city children. The factors responsible for this public health problem remain unclear but are probably related to genetics, behavioral factors, and exposures to allergens and pollutants, including ETS. The overall proposal aims to explore the postulated relationships of these factors to childhood asthma and to build upon the findings of the current studies. Of the eight component s proposed, two are epidemiology studies and one is a basic science study. There are two core facilities, one administration core, one community outreach project, and one new investigator project. The Data Management and Analysis Core facility (DMAC) provides the essential infrastructure to support the conduct and monitor performance of all scientific components of the Center and to facilitate the operation of other components. Specifically, the DMAC will collaborate with investigators to develop the study protocols, data collection instruments, and data management system, to ensure quality of the data, to provide interim and final analysis of the data, and to participate in the preparation of manuscripts and reports. To accomplish the objectives, the DMAC will leverage the resources, personnel, and data systems that have been acquired and developed during the past five funding years. The DMAC will improve upon the successful data capture and data management systems. For large data sets, such as the microarray data, new methods (e.g. R package for microarray analysis) will be implemented. With the expanding specimen collection and laboratory tests, new tools will be used to facilitate the labelling and tracking of specimen and results, and to identify early warning signs of trouble or bottleneck. The DMAC has provided valid and timely results of interim and special data analysis to Center and non-Center investigators to prepare abstracts for presentations and manuscripts for submission. The DMAC will constantly monitor performances of data collection and clinical trial processes, and will ensure the quality, integrity, and security of the data. Weekly data management meetings have provided valuable feedback on data issues to the conduct of the scientific studies and will continue to be held in the upcoming funding phase. Overall, the DMAC is essential to the Center through providing data support, monitoring and ensuring quality performance, and supplying scientific input in study design, conduct, analysis, and interpretation.

内城区儿童的哮喘发病率很高。造成这一公共卫生问题的因素尚不清楚，但可能与遗传、行为因素以及接触过敏原和污染物（包括 ETS）有关。总体提案旨在探讨这些因素与儿童哮喘之间的假设关系，并以当前研究的结果为基础。在提议的八个组成部分中，两个是流行病学研究，一个是基础科学研究。有两个核心设施、一个管理核心、一个社区外展项目和一个新调查员项目。数据管理和分析核心设施（DMAC）提供了必要的基础设施，以支持该中心所有科学组成部分的开展和监测性能，并促进其他组成部分的运行。具体来说，DMAC 将与研究人员合作制定研究方案、数据 收集仪器和数据管理系统，确保数据质量，提供数据的中期和最终分析，并参与手稿和报告的准备。为了实现这些目标，DMAC 将利用过去五年资助期间获得和开发的资源、人员和数据系统。 DMAC 将改进成功的数据捕获和数据管理系统。对于大型数据集，例如微阵列数据，将实施新方法（例如用于微阵列分析的 R 包）。随着样本采集和实验室测试的扩大，将使用新工具来促进样本和结果的标记和跟踪，并识别故障或瓶颈的早期预警信号。 DMAC 向中心和非中心研究人员提供了有效且及时的中期和特殊数据分析结果，以准备演示摘要和提交手稿。 DMAC 将持续监控数据收集和临床试验过程的表现，并确保数据的质量、完整性和安全性。每周的数据管理会议为科学研究的进行数据问题提供了宝贵的反馈，并将在即将到来的资助阶段继续举行。总体而言，DMAC 通过提供数据支持、监测和确保质量绩效以及在研究设计、实施、分析和解释方面提供科学投入，对该中心至关重要。