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Related Experiment Videos

A microcomputer-based clinical trial database incorporated with an 'audit trail' for correction process.

Y L Hsu1, D J Reda

  • 1Cooperative Studies Program Coordinating Center, Hines VA Hospital, IL 60141.

Computer Methods and Programs in Biomedicine
|December 1, 1989
PubMed
Summary
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Microcomputers can now manage complex clinical trial data, reducing costs and improving efficiency. This Veterans Administration system offers enhanced data verification and automated maintenance for research projects.

Area of Science:

  • Clinical research informatics
  • Database management systems
  • Health services research

Background:

  • Multicenter clinical trials generate vast datasets requiring significant computational resources.
  • Traditional data management often relies on mainframe computers, posing accessibility and cost challenges.

Purpose of the Study:

  • To demonstrate the feasibility of using microcomputers for managing complex multicenter clinical trial data.
  • To present a novel Database Management System (DBMS) designed for enhanced data verification and audit trails on microcomputers.

Main Methods:

  • Implementation of the SIR/PC Database Management System (DBMS) on an IBM PC AT at the Veterans Administration Cooperative Studies Program Coordinating Center (CSPCC).
  • Development of a custom data verification and update method providing a detailed audit trail.

Related Experiment Videos

  • Automation of DBMS operation and maintenance through menu systems and prestored utility programs.

    • Main Results:

    • Successful implementation of three complex studies using the microcomputer-based DBMS.
    • The CSPCC DBMS provides a more detailed audit trail than standard SIR facilities.
    • Early data validation is facilitated, enabling timely error identification.

    Conclusions:

    • Microcomputer-based systems are viable for managing large-scale clinical trial data.
    • The developed DBMS enhances data integrity, streamlines operations, and reduces development costs.
    • This approach offers a cost-effective and efficient alternative to mainframe systems for clinical research data management.