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Clinical research databases: getting from current state to best practice.
Steven E Waldren1, Joseph Quetsch
1University of Missouri, Department of Healthcare Management and Informatics, Columbia, USA.
AMIA ... Annual Symposium Proceedings. AMIA Symposium
|January 20, 2004
Summary
Managing clinical research data is crucial for health sciences. A new checklist tool helps researchers and data administrators evaluate database operations, mitigating risks and maximizing data value.
Area of Science:
- Health Sciences
- Information Science
- Data Management
Background:
- Clinical research databases are fundamental to health sciences.
- Research data is often managed by individuals outside of information science expertise.
- Improper data management poses significant risks to researchers, participants, and patients.
Purpose of the Study:
- To develop a practical tool for evaluating clinical research database operations.
- To address potential liabilities associated with poor data management.
- To enhance the preservation and maximization of data value.
Main Methods:
- Creation of a comprehensive checklist tool.
- The tool is designed for researchers and data administrators.
- Evaluation of database operations for risks and data value.
Main Results:
- The checklist tool provides a structured approach to database evaluation.
- It identifies potential risks and areas for data value enhancement.
- A systematic method for assessing data management practices is established.
Conclusions:
- Effective data management is essential for the integrity of clinical research.
- The developed checklist tool supports researchers and administrators in optimizing database operations.
- Implementing the checklist can mitigate risks and improve the overall value of clinical research data.