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Design, development, and implementation of a data processing system for multiple controlled trials and epidemiologic

B S Hawkins, S W Singer

    Controlled Clinical Trials
    |June 1, 1986
    PubMed
    Summary
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    A flexible data processing system was developed for diverse epidemiologic studies. This system successfully integrated mainframe and microcomputers, enhancing data management and analysis capabilities.

    Area of Science:

    • Epidemiology
    • Health Informatics
    • Biostatistics

    Background:

    • New research groups require robust data processing systems for multiple epidemiologic studies.
    • Existing data centers were surveyed to understand operational data processing modules.
    • Generalization of data management functions was identified as a key requirement.

    Purpose of the Study:

    • To design and implement a generalizable data processing system for diverse epidemiologic studies.
    • To accommodate varying needs of multiple studies within a single research group.
    • To leverage commercial software and a mixed hardware environment.

    Main Methods:

    • Conducted a survey of 15 operating data centers.
    • Classified data processing into recording/entry, management, and analysis modules.

    Related Experiment Videos

  • Selected a mixed hardware environment (mainframe and microcomputers).
  • Utilized commercially available software (database manager, statistics packages, data entry, communications).
  • Prioritized software selection based on hardware independence, price, and functionality.

    • Main Results:

    • Developed a generalized data management system.
    • Successfully integrated mainframe and microcomputer environments using commercial software.
    • The system demonstrated flexibility and was successfully applied to three distinct epidemiologic studies.
    • Hardware selection was guided by software availability, budget, and computing resources.

    Conclusions:

    • A generalized data processing system can be effectively implemented using commercial software and a mixed hardware approach.
    • The developed system successfully supported diverse epidemiologic studies with varying requirements.
    • This approach offers a cost-effective and adaptable solution for research data management.