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.
| Logan, Judith R; Britell, Scott; Delcambre, Lois M L et al. (2010) Representing multi-database study schemas for reusability. AMIA Jt Summits Transl Sci Proc 2010:21-5 |
