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Database and knowledge base integration--a data mapping method for Arden Syntax knowledge modules

B Johansson1, N Shahsavar, H Ahlfeldt

  • 1Department of Medical Informatics, Linköping University, Sweden. BoJoh@imt.liu.se

Methods of Information in Medicine
|December 1, 1996
PubMed
Summary
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This study introduces a novel method for linking clinical databases to medical knowledge bases using Arden Syntax modules. It simplifies database querying for medical experts, enhancing data-driven decision support systems.

Area of Science:

  • Medical Informatics
  • Database Management
  • Clinical Decision Support

Background:

  • Data-driven decision support systems are crucial in medicine, relying on integrated databases and inference engines.
  • Efficient implementation of database queries within medical knowledge modules is essential for system functionality.
  • Existing methods may require medical experts to have in-depth knowledge of database structures.

Purpose of the Study:

  • To describe a method for seamlessly linking clinical databases with knowledge bases utilizing Arden Syntax modules.
  • To simplify the process of database query implementation for medical experts authoring knowledge modules.
  • To facilitate standardized and platform-independent integration of diverse clinical databases.

Main Methods:

  • A query meta-database containing SQL query templates, managed by a database administrator, forms the core of the method.

Related Experiment Videos

  • Medical experts reference simple codes in the meta-database, abstracting away complex database models and attribute naming.
  • Standard tools like C++ and Open Database Connectivity (ODBC) are employed for broad platform compatibility.

    • Main Results:

    • The described method enables medical experts to link to clinical databases without needing specific database administration knowledge.
    • It standardizes the way knowledge modules interact with various clinical databases.
    • The use of C++ and ODBC ensures wide platform applicability and interoperability.

    Conclusions:

    • This approach significantly streamlines the integration of clinical data into medical knowledge bases.
    • It enhances the development and utility of data-driven clinical decision support systems.
    • The method promotes standardized database linking, improving efficiency and accessibility in medical informatics.