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Related Experiment Videos

Algorithm-derived, computer-generated interpretive comments in the reporting of laboratory tests.

T H McConnell, C T Ashworth, R D Ashworth

    American Journal of Clinical Pathology
    |July 1, 1979
    PubMed
    Summary
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    Computer-generated comments help manage large volumes of lab data for physicians. This study shows their effective use in a clinical laboratory setting for chemical profiles and thyroid tests.

    Area of Science:

    • Clinical Chemistry
    • Medical Informatics
    • Laboratory Medicine

    Background:

    • Physicians face overwhelming daily laboratory data volumes, increasing potential for errors.
    • Computer-generated reminders are a proposed solution to mitigate data processing challenges.
    • Clinical laboratories generate extensive data from tests like chemical profiles and thyroid function.

    Purpose of the Study:

    • To evaluate the practical application of a custom computer program generating algorithm-derived comments.
    • To assess the impact of these computer-generated comments in a busy clinical laboratory.
    • To determine the utility of this system for reporting chemical profiles and thyroid function tests.

    Main Methods:

    • Implementation of a user-written program generating algorithm-derived comments.

    Related Experiment Videos

  • Daily use of the program for reporting laboratory test results.
  • Focus on chemical profiles and routine thyroid function tests.
  • Study conducted in a medium-sized, privately owned independent clinical laboratory.

    • Main Results:

    • The program provided daily computer-generated comments for test reporting.
    • Experience gained from using the system in a real-world clinical setting.
    • The system was applied to chemical profiles and thyroid function tests.

    Conclusions:

    • Computer-generated comments can aid in managing complex laboratory data.
    • The user-written program demonstrated practical utility in a clinical laboratory.
    • This approach offers a potential solution for reducing physician oversight errors.