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From micro to mainframe. A practical approach to perinatal data processing.

S Y Yeh, T Lincoln

    American Journal of Perinatology
    |April 1, 1985
    PubMed
    Summary
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    A novel microcomputer and mainframe approach efficiently processes perinatal data for large obstetric populations. This practical, flexible, and economical system enhances data management and analysis.

    Area of Science:

    • Obstetrics and Gynecology
    • Medical Informatics
    • Health Data Management

    Background:

    • Large-scale perinatal data processing presents significant logistical challenges.
    • Efficient data management is crucial for improving obstetric care and research.
    • Existing methods may be costly, inflexible, or time-consuming.

    Purpose of the Study:

    • To describe a new, practical, and economical approach for processing perinatal data.
    • To detail a system utilizing microcomputers for data entry and mainframe computers for data reduction.
    • To demonstrate the utility of the Screen Oriented Data Access (SODA) and Statistical Analysis System (SAS) programs in perinatal data management.

    Main Methods:

    • Data entry was performed on an Apple II Plus microcomputer using the Screen Oriented Data Access (SODA) program.

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  • Data were stored on diskettes and transmitted via modem and telephone line.
  • Data reduction and statistical analyses were conducted on an IBM 370/168 mainframe computer using the Statistical Analysis System (SAS) program.

    • Main Results:

    • The described approach proved to be practical for handling large obstetric populations.
    • The system demonstrated flexibility in data entry and processing.
    • The method was found to be economical compared to alternative data processing techniques.

    Conclusions:

    • This integrated microcomputer-mainframe system offers an efficient solution for perinatal data processing.
    • The use of SODA and SAS facilitates effective data management and analysis in obstetrics.
    • The approach is highly suitable for large-scale obstetric data collection and research.