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Automatic encoding of clinical narrative

N Sager, I D Bross, G Story

    Computers in Biology and Medicine
    |January 1, 1982
    PubMed
    Summary
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    This study presents an automated system for encoding English medical data. The program successfully translates free-text patient information into a structured format for analysis.

    Area of Science:

    • Medical Informatics
    • Natural Language Processing
    • Computational Linguistics

    Background:

    • Automatic encoding of medical data is crucial for efficient information retrieval and analysis.
    • Existing methods may lack the flexibility to handle diverse free-text medical inputs.
    • Standardized data representation facilitates large-scale epidemiological studies and clinical research.

    Purpose of the Study:

    • To describe an experimental program for the automatic encoding of English-language medical data.
    • To evaluate the program's performance in a real-world application using a specific medical code.
    • To demonstrate the feasibility of using natural language processing for medical data abstraction.

    Main Methods:

    • The encoding program utilizes a two-stage process involving natural language processing (NLP).

    Related Experiment Videos

  • Stage 1: A general-purpose NLP processor parses free-text input and structures information into a tabular format.
  • Stage 2: A code-dependent subprogram assigns numerical values based on word positions within the established information format.

    • Main Results:

    • A blind test was conducted using the encoding program.
    • The test employed the code used at Roswell Park Memorial Institute for the earliest symptoms of head-neck cancer.
    • Results indicate the program's capability to automatically encode specific medical data.

    Conclusions:

    • The described two-stage program offers a viable method for automatic encoding of English medical data.
    • This approach has potential applications in streamlining medical record processing and data analysis.
    • Further development could enhance the program's adaptability to various medical coding systems and data types.