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Related Experiment Videos

Multipurpose practice guideline modules for clinical decision analysis and quality improvement

E A Balas1, D Gardner, O Hamdy

  • 1School of Medicine, University of Missouri-Columbia, Columbia 65201, USA.

Medinfo. MEDINFO
|January 1, 1995
PubMed
Summary

Researchers found significant information loss when communicating clinical trial data. A new tool for sharing clinical practice guidelines was developed and tested for knowledge base development.

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Area of Science:

  • Clinical Informatics
  • Health Services Research
  • Medical Information Systems

Background:

  • Effective communication of clinical research findings is crucial for evidence-based practice.
  • Information loss between clinical researchers and IT developers can hinder knowledge translation.
  • Current methods for sharing clinical practice guidelines may be suboptimal.

Purpose of the Study:

  • To quantify information loss in communication between clinical researchers and information system developers.
  • To design a tool facilitating the sharing of clinical practice guidelines.
  • To evaluate the feasibility of this tool in knowledge base development.

Main Methods:

  • Analysis of 101 randomized controlled clinical trials to assess information reporting.

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  • Development of a multipurpose knowledge module for clinical practice recommendations.
  • Application of guideline modules in building a quality feedback expert system (QFES) knowledge base.

    • Main Results:

    • Exact numeric results were reported in only 64% of analyzed clinical trials.
    • Structured abstracts improved overall quality scores (p<0.001) but not numeric reporting (p=0.31).
    • A multipurpose knowledge module was conceptualized and applied successfully in QFES development.

    Conclusions:

    • Significant information loss occurs in clinical research communication, particularly regarding numeric data.
    • A novel knowledge module approach can enhance the sharing of clinical practice guidelines.
    • The developed tool shows feasibility for improving knowledge base construction in expert systems.