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An extended SQL for temporal data management in clinical decision-support systems.

A K Das1, S W Tu, G P Purcell

  • 1Section on Medical Informatics, Stanford University School of Medicine, California 94305-5479.

Proceedings. Symposium on Computer Applications in Medical Care
|January 1, 1992
PubMed
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This study introduces a temporal database for HIV patient care systems, enhancing clinical decision support. The new system manages time-based data effectively, improving protocol adherence and patient outcomes.

Area of Science:

  • Computer Science
  • Medical Informatics
  • Database Systems

Background:

  • Clinical trial protocols generate complex temporal data.
  • Existing database models struggle with managing time-dependent clinical information.
  • The T-HELPER physician workstation requires robust temporal data management for HIV patient care.

Purpose of the Study:

  • To develop a database implementation supporting temporal data management for the T-HELPER physician workstation.
  • To address the specific temporal querying requirements identified in clinical trial protocols.
  • To enhance protocol-directed decision support for HIV disease management.

Main Methods:

  • Analyzed temporal predicates in clinical trial protocols.
  • Extended the standard relational data model by incorporating timestamps for instant- and interval-based data.

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  • Developed operations for manipulating timestamped data (timepoints and intervals).
  • Modified the SQL query language to support temporal operations within relational tables.
  • Main Results:

    • A temporal database implementation was successfully developed.
    • The extended relational model effectively stores and manages temporal data.
    • Modified SQL supports necessary temporal data manipulation and querying.
    • The system meets the temporal data management needs for protocol-directed decision support.

    Conclusions:

    • The developed temporal database extension enhances the T-HELPER system's capability.
    • The approach effectively manages temporal data crucial for HIV patient care protocols.
    • This work advances the integration of temporal data management in clinical decision support systems.