Date

December 2010

Document Type

Capstone

Degree Name

M.B.I.

Department

Dept. of Medical Informatics and Clinical Epidemiology

Institution

Oregon Health & Science University

Abstract

A clinical trial is a research method for studying the risks and efficiencies of the medical products or procedures under analysis. The integration of data from multiple clinical trials can provide much-needed help in answering research questions, since the combined enrollment from the individual trials increases the significance of the research results. Previous research by Logan et. al. [ (1), (2), (3)] analyzed the usage, advantages, and effectiveness of what they call "dynamic data integration" in the context of multiple disparate electronic medical record databases. Both the theoretical framework and tools used in this project were developed as part of that work. This model of data integration presents many advantages for a data analysts. For example, it includes methods such that the query interface used by data analysts is essentially the user interface through which data was collected. This method provides maximal contextual information about that data that can improve query accuracy. In addition, by using these methods and tools, data analysts do not need to be cognizant of the underlying data schemas or to be database experts. Our current work extends the previous research by evaluating and enhancing the efficacy of the existing tools in the setting of clinical trials. As a first step for enhancing the existing tools, we searched for data transformation operators used with clinical trials data. To do this, we repurposed results from a previously published study (Cognitive load required for completion of case report forms (4)) performed by the Duke Translational and Research Institute. These data transformation operators were then implemented in the query interface. Additionally, we created a new prototype user interface, to showcase the tools to different analysts for evaluating effectiveness in clinical trials data integration. We also created tools to assist in pre-integration steps including a tool to transform data in REDCap (5) to a known format (g-tree (1)), so that the existing tools can directly consume the data, without any changes to the framework or existing tools. This project demonstrates the use of the aforementioned enhancements, by integrating the data captured using two different systems (REDCap (5) and Cardiff TeleForm (6)) during the performance of a clinical trial. Integration of this data simulates integration of multiple clinical trials, since it presents similar complexity due to varied database and coding schemas.

Identifier

doi:10.6083/M4W093W6

School

School of Medicine

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