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Related Experiment Video

Updated: Sep 7, 2025

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System for Context-Specific Visualization of Clinical Practice Guidelines (GuLiNav): Concept and Software

Jonas Fortmann1,2, Marlene Lutz1, Cord Spreckelsen2,3

  • 1Institute of Medical Informatics, Medical Faculty, Rheinisch-Westfälische Technische Hochschule Aachen University, Aachen, Germany.

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|June 22, 2022
PubMed
Summary

This study introduces dynamic guideline visualization for clinical decision support systems, improving insight into guideline models and patient treatment context. The approach enhances guideline adherence and clinician acceptance.

Keywords:
clinicalclinical decision support systemclinical practice guidelinecomputer-assisted decision makingdecision makingdecision support techniqueseHealthelectronic healthguideline representationsoftwaresupport systemsworkflowworkflow control patterns

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Area of Science:

  • Computer Science
  • Medical Informatics
  • Health Systems Engineering

Background:

  • Clinical decision support systems (CDSS) leverage clinical practice guidelines (CPGs) for improved availability and adherence.
  • Current CDSS often use internal state-based models lacking user transparency.
  • Lack of user insight into guideline models hinders effective clinical decision-making.

Purpose of the Study:

  • To present a novel dynamic guideline visualization approach for CDSS.
  • To incorporate individual patient treatment context into guideline recommendations.
  • To enhance transparency and usability of CPGs within CDSS.

Main Methods:

  • Derived requirements for enhanced guideline visualization.
  • Utilized Business Process Model and Notation (BPMN) for computer-interpretable guidelines.
  • Employed graph-based representation, logical inferences, and a business rules engine for context-specific visualization.

Main Results:

  • Implemented and piloted an algorithmic approach for guideline interpretation and visualization.
  • Developed a context-specific guideline visualization derived from algorithmic interpretation.
  • Demonstrated high clinician acceptance through a formative usability evaluation of a prototype tool.

Conclusions:

  • The novel guideline processing and visualization concept is technically feasible.
  • The approach addresses limitations in existing guideline-based CDSS.
  • Further research is needed to assess applicability in specific medical use cases.