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[Computer experience and further developments in the respiratory function laboratory (author's transl)].

R Schindl, K Mayer, K Aigner

    Medizinische Klinik
    |November 7, 1975
    PubMed
    Summary
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    A small computer system enhances respiratory function diagnostics by automating data processing and interpretation. This system improves accuracy and efficiency in analyzing patient respiratory and blood gas data.

    Area of Science:

    • Medical Technology
    • Pulmonary Medicine
    • Computer Science

    Context:

    • Respiratory function laboratories traditionally rely on manual data processing.
    • Integrating computing into routine diagnostics presents challenges in data handling and interpretation.
    • The need for efficient and accurate analysis of complex physiological data is growing.

    Purpose:

    • To report satisfactory results from a small-size computer system in a respiratory function laboratory.
    • To establish a diagnostic and teaching program for routine respiratory function methods using this system.
    • To extend the system's capabilities to include blood gas analysis and acid-base status interpretation.

    Summary:

    • A small-size computer system, including a punching and scanning device and a writing machine, was developed for on- and off-line processing in a respiratory function laboratory.

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  • The system facilitates the examination of a large number of cases, reduces errors, provides extensive data, and automates documentation, interpretation, and evaluation.
  • Blood gas analysis was integrated, enabling the interpretation of acid-base status disturbances, with automated checks for clinical correction. Calculations for alveolar-arterial oxygen pressure gradient, venous shunt, and oxygen saturation were also implemented.

    • Impact:

    • Significant improvements in the efficiency and accuracy of respiratory function testing.
    • Enhanced diagnostic capabilities through automated data interpretation and analysis of blood gas parameters.
    • Potential for cost-effective advancements in respiratory diagnostics and education using modular, small-size computer systems.