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Building an explanation function for a hypertension decision-support system.

R D Shankar1, S B Martins, S W Tu

  • 1Stanford Medical Informatics, Stanford University School of Medicine, Stanford, California 94305-5479, USA. shankar@smi.stanford.edu

Studies in Health Technology and Informatics
|October 18, 2001
PubMed
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The ATHENA Decision-Support System (DSS) enhances hypertension management in primary care by providing evidence-based explanations for its recommendations. This improves user trust and acceptance through clear, visualized reasoning.

Area of Science:

  • Medical Informatics
  • Clinical Decision Support Systems

Background:

  • User acceptance of clinical decision support systems (CDSS) is crucial for effective implementation.
  • Effective explanation of reasoning and justification of conclusions are key factors influencing user acceptance.

Purpose of the Study:

  • To develop and integrate an explanation function for the ATHENA Decision-Support System (DSS).
  • To enhance user trust and acceptance of the ATHENA DSS in primary care hypertension management.

Main Methods:

  • Adapted the WOZ declarative explanation framework to build the explanation function.
  • Integrated the explanation function with the EON component-based architecture of ATHENA DSS.
  • Utilized argument models and visual clients to generate and display explanations.

Related Experiment Videos

Main Results:

  • The explanation function successfully tapped into EON components, guidelines, and medical literature.
  • Generated rich, evidence-based explanations by incorporating varied information sources.
  • Employed visual clients to display explanations, mirroring natural medical arguments.

Conclusions:

  • The developed explanation function enhances the ATHENA DSS by providing transparent, evidence-based reasoning.
  • This approach is expected to improve user acceptance and the effective management of hypertension in primary care.