Statistical Infrastructure for Combining Information from Multiple Data Sources

用于组合来自多个数据源的信息的统计基础设施

• 批准号: 7815586
• 负责人: TRIVELLORE E RAGHUNATHAN
• 金额: $ 40.24万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-24 至 2011-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7815586
• 关键词: Address; Area; Biological; Cardiovascular system; Clinical Research; Clinical Trials; Complex; Computer Systems; Computer software; Confidentiality; Data; Data Analyses; Data Coordinating Center; Data Set; Data Sources; Databases; Directories; Disclosure; Economics; Electronic Health Record; Environmental Risk Factor; Epidemiologic Studies; Epidemiologist; Epidemiology; Funding; Goals; Health; Healthcare; Hematological Disease; Information Technology; Internet; Linux; Location; Lung; Mails; Manuals; Meta-Analysis; Methodology; Methods; Modeling; Online Systems; Outcome; Output; Policies; Principal Investigator; Process; Public Health; Published Directory; Research; Research Infrastructure; Research Personnel; Source; Specific qualifier value; Statistical Models; Surveys; System; Teaching Materials; Testing; Work; base; comparative; computer infrastructure; data sharing; design; experience; improved; population health; programs; psychologic; psychosocial; public health research; repository; social; software development; software systems; tool; treatment effect; web interface

DESCRIPTION (provided by applicant): This application addresses broad Challenge Area of "Information Technology for Processing Health Care Data" (Area # 10) and two specific Challenge topics (10-RR-101): Information Technology Demonstration Projects Facilitating Secondary Use of Healthcare Data for Research and (10-HL-101): Develop data sharing and analytic approaches to obtain from large- scale observational data, especially those derived from electronic health records, reliable estimates of comparative treatment effects and outcomes of cardiovascular, lung, and blood diseases. Several challenge areas in this request suggest that there is no single data set for addressing the complex interplay of biological, social, psychological, economic and environmental determinants of health. Still, deeper understanding of these facets is needed to make informed policy decisions. The principal investigator of this proposal has been involved in developing methods for combining information from multiple data sources. These methods can be enhanced and become more useful if a proper computational infrastructure implementing them were made available to substantive researchers. The goal of this proposal is to develop a statistical infrastructure to facilitate pooling of data from multiple sources, create data sets for analytical purposes and provide software for properly analyzing such combined data sets. Under this approach the two or more data sets will be concatenated, common variables across the data sources will be aligned and the nonaligned variables will be treated as missing data in one or more data sets. The multiple imputation methodology will be tailored to combine information from multiple sources using fairly general and semi-parametric models. The end product will be two modes of software will be built upon the existing infrastructure developed by the principal investigator. In the first mode, the user will input two or more data sets, list all the variables to be analyzed from these data sets, specify the statistical model to test a research hypothesis and the software will then properly analyze the data and disseminate the results. When data cannot be freely distributed to researchers due to confidentiality concerns, the second mode will add a web-based remote data analysis tool for the computer system holding the confidential data sets. The legitimate users will then be able to log-in to the system through web and specify the analytical request as before. Two versions of the software will be developed one as an add-on to SAS, popular software used by many researchers. The second version will be a stand alone version which can be used by researchers who do not have access to SAS. The software will be developed to work under both Windows and Linux platforms. The purpose of this research is to build a statistical software system that allow biostatisticians, clinicians, epidemiologists and other public health researchers to fit statistical models that call for combining information from multiple data sources. The aim is pool information from administrative, epidemiological and clinical study databases to address public health research. The software system can be used by the Data Coordinating Centers where the analysis requests can be remotely submitted by network researchers. The system will also be useful for data repositories where data sets cannot be released due to confidentiality concerns but allow researchers to request analysis based on those data sets. The statistical software system will be distributed via web freely to the public.

描述（由申请人提供）： 此应用程序解决了“处理医疗保健数据的信息技术”的广泛挑战领域（区域#10）和两个特定的挑战主题（10-RR-101）：信息技术示范项目，促进医疗保健数据的二次利用，（10-HL-101）：制定数据共享和分析方法，从大规模观察数据中获取，特别是从电子健康记录中获取，心血管、肺和血液疾病的比较治疗效果和结局的可靠估计。该请求中的几个挑战领域表明，没有一个单一的数据集可用于处理健康的生物、社会、心理、经济和环境决定因素之间复杂的相互作用。然而，需要更深入地了解这些方面，以做出明智的政策决定。该提案的主要研究者参与制定了将多个数据来源的信息结合起来的方法。这些方法可以得到加强，变得更加有用，如果一个适当的计算基础设施，实现它们提供给实质性的研究人员。这项建议的目标是建立一个统计基础设施，以便利汇集来自多个来源的数据，建立用于分析目的的数据集，并提供适当分析这种综合数据集的软件。在这种方法下，两个或多个数据集将被连接，跨数据源的共同变量将被对齐，而不对齐的变量将被视为一个或多个数据集中的缺失数据。多重插补方法将采用相当通用的半参数模型，对来自多个来源的联合收割机信息进行调整。最终产品将是两种模式的软件，将建立在主要研究者开发的现有基础设施上。在第一种模式中，用户将输入两个或更多的数据集，列出从这些数据集中分析的所有变量，指定统计模型来测试研究假设，然后软件将正确分析数据并传播结果。当数据因保密问题而不能自由分发给研究人员时，第二种模式将为保存机密数据集的计算机系统增加一个基于网络的远程数据分析工具。然后，合法用户将能够通过Web登录到系统，并像以前一样指定分析请求。该软件将开发两个版本，一个是作为SAS的附加软件，SAS是许多研究人员使用的流行软件。第二个版本将是一个独立的版本，可以使用的研究人员谁没有访问SAS。该软件将开发为在Windows和Linux平台下工作。本研究的目的是建立一个统计软件系统，使生物统计学家，临床医生，流行病学家和其他公共卫生研究人员，以适应统计模型，要求结合来自多个数据源的信息。其目的是汇集行政、流行病学和临床研究数据库的信息，用于公共卫生研究。该软件系统可由数据协调中心使用，网络研究人员可在数据协调中心远程提交分析请求。该系统还将对数据储存库有用，因为在这些数据储存库中，由于保密问题，数据集不能公布，但研究人员可以要求根据这些数据集进行分析。统计软件系统将通过网络免费向公众发布。