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Exploiting the User Interface for Data Integration in Effectiveness Research

Exploiting the User Interface for Data Integration in Effectiveness Research
利用用户界面进行有效性研究中的数据集成
批准号:
7342370
负责人:
JUDITH R LOGAN
金额:
$20.53万
依托单位国家:
美国
项目类别:
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-09-01 至 2011-08-31

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项目成果

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中文摘要
翻译
描述(由申请人提供):许多临床应用程序,包括报告工具和电子健康记录,都订阅了基于表单的界面范例,其中软件用一系列表单提示用户进行数据输入。在这个范例中。用户界面是数据语义的最终来源,因为用户在屏幕上看到的内容可能会影响他或她输入数据的方式。利用用户界面的语义可以为调查人员和数据分析师提供执行有效性研究的强大工具,特别是在使用多个数据源(每个数据源都有自己的数据语义)执行研究时。该项目的长期目标是开发创新的工具和形式化的计算概念,以满足综合有效性研究的需要。实现这一目标的概念框架包括用于基于用户界面创建数据库的自动化工具、用于分析师直接编写针对用户界面的查询的方法,以及允许分析师以动态方式对来自多个源的数据元素进行分类的工具。当前项目的目标是在此框架内构建当前的概念验证工具。目标#1是为Guava (GUi-As-View)定义、开发、形式化、优化和评估体系结构、数据结构和操作符,以便在用户界面上构建查询界面,并从用户界面生成底层数据库。目标#2是定义、开发、形式化、优化和评估MultiClass (Multiple-Classifications)的体系结构、数据结构和操作符,其中分析师可以使用一组分类器对每个研究描述其信息集成决策。实现这些目标的成功与否将通过从第一个和多个主要来源轻松检索记录以供分析的能力来衡量。
英文摘要
DESCRIPTION (provided by applicant): Many clinical applications, including reporting tools and electronic health records, subscribe to a paradigm of forms-based interfaces, where the software prompts the user with a sequence of forms for data entry. In this paradigm. the user interface is the definitive source for the semantics of the data since what the user sees on the screen may influence how he or she will enter data. Harnessing the semantics of the user interface can give investigators and data analysts powerful tools for performing effectiveness research, especially for performing research using multiple data sources, each with its own data semantics. The long-range goal of this project is to develop innovative tools and the formalized computational concepts that underlie them to meet the needs of integrated effectiveness research. The conceptual framework for meeting this goal includes automated tools for creation of databases based on user interfaces, methods for analysts to directly write queries against the user interface, and tools that allow analysts to classify data elements from multiple sources in a dynamic manner. The aims of the current project are to build on current proof-of-concept tools within this framework. Aim #1 is to define, develop, formalize, optimize and evaluate the architecture, data structures, and operators for Guava (GUi-As-View) to build a query interface over the user interface and generate the underlying database from the user interface. Aim #2 is to define, develop, formalize, optimize, and evaluate the architecture, data structures and operators for MultiClass (Multiple-Classifications) where an analyst can describe her information integration decisions using a set of classifiers, for each study. Success in meeting these aims will be measured by the ability to easily retrieve records for analysis from first one and then multiple primary sources. This research aims to increase the amount and improve the process of effectiveness research performed using data collected in clinical settings. Effectiveness research studies topics such as the delivery of healthcare services, conformance of clinical practice to evidence-based guidelines, and associations in real practice of symptoms and findings, and in all of these ways directly benefit public health.
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