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Related Experiment Videos

Reengineering a database for clinical trials management: lessons for system architects.

C A Brandt1, P Nadkarni, L Marenco

  • 1Center for Medical Informatics, Yale University School of Medicine, New Haven, CT 06520-8009, USA. cynthia.brandt@yale.edu

Controlled Clinical Trials
|October 6, 2000
PubMed
Summary

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This study enhanced the Trial/DB clinical trial management system for better user support and adaptability. Architectural changes enabled secure internet use and customized study design, improving efficiency for researchers and administrators.

Area of Science:

  • Health Informatics
  • Clinical Trial Management Systems
  • Database Architecture

Background:

  • Trial/DB is a database system for clinical studies management.
  • Existing system faced challenges supporting diverse users and study types.
  • Need for efficient and secure internet-based operation and adaptable study design processes.

Purpose of the Study:

  • To enhance the Trial/DB system for improved effectiveness of developers, study designers, and administrators.
  • To adapt the system for efficient and secure internet-based operation.
  • To allow study design and project management processes to adapt to diverse user working styles.

Main Methods:

  • Implemented basic architectural changes for internet efficiency and security.
  • Modified processes for study design and project management to accommodate varied user needs.

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  • Focused on maximizing personnel effectiveness in supporting users, study setup, and administration.

    • Main Results:

    • Trial/DB successfully adapted for internet-based use, enhancing security and efficiency.
    • System modifications improved support for diverse users, including study designers and administrators.
    • Enhanced adaptability to principal investigators' and administrators' working styles for study management.

    Conclusions:

    • The enhanced Trial/DB system improves clinical trial management efficiency and user support.
    • Architectural and process adaptations are crucial for scalable and secure clinical database systems.
    • Lessons learned offer valuable insights for electronic patient record system managers and system architects.