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Related Experiment Videos

[Programming of freely written anamnesses for the computer].

M Crivelli, C Zeller, M Scherrer

    Schweizerische Medizinische Wochenschrift
    |July 8, 1978
    PubMed
    Summary

    Free text analysis of patient histories using STAIRS-IBM significantly speeds up data retrieval for respiratory diseases. Computer dialogue selection of chronic bronchitis in lung cancer patients was 3 months faster than manual review, improving clinical correlation discovery.

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    Area of Science:

    • Medical Informatics
    • Clinical Data Analysis
    • Information Retrieval

    Context:

    • Over 5000 outpatient respiratory disease case histories were stored as free text between 1974 and 1977.
    • Efficient retrieval of specific patient data from large, unstructured text databases is a significant challenge.

    Purpose:

    • To evaluate the retrieval efficiency of the STAIRS-IBM program for free text case histories.
    • To demonstrate the utility of automated text analysis for identifying clinical correlations, specifically chronic bronchitis in lung cancer patients.

    Summary:

    • The STAIRS-IBM program was used with various syntax operators to test retrieval efficiency on free text case histories.
    • Chronic bronchitis in lung cancer patients was analyzed, with word constellations used as retrieval arguments.
    • Computer dialogue selection for chronic bronchitis cases (pre-existing >5 years) yielded 87% accuracy, compared to 74% for no history, significantly reducing analysis time from 3 months to 4 hours.

    Impact:

    • Free text analysis of case histories is feasible with STAIRS-IBM, enabling rapid identification of clinically relevant correlations.
    • Automated data retrieval drastically reduces time compared to manual review, allowing clinicians to discover new insights faster.
    • The system's efficiency can be further improved, with potential for minimal misclassification, highlighting its value in medical research.

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