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. 2022 Jun 22;6(6):e28013.
doi: 10.2196/28013.

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

Jonas Fortmann  1   2 , Marlene Lutz  1 , Cord Spreckelsen  2   3
Affiliations

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

Jonas Fortmann et al. JMIR Form Res. .

Abstract

Background: Clinical decision support systems often adopt and operationalize existing clinical practice guidelines leading to higher guideline availability, increased guideline adherence, and data integration. Most of these systems use an internal state-based model of a clinical practice guideline to derive recommendations but do not provide the user with comprehensive insight into the model.

Objective: Here we present a novel approach based on dynamic guideline visualization that incorporates the individual patient's current treatment context.

Methods: We derived multiple requirements to be fulfilled by such an enhanced guideline visualization. Using business process and model notation as the representation format for computer-interpretable guidelines, a combination of graph-based representation and logical inferences is adopted for guideline processing. A context-specific guideline visualization is inferred using a business rules engine.

Results: We implemented and piloted an algorithmic approach for guideline interpretation and processing. As a result of this interpretation, a context-specific guideline is derived and visualized. Our implementation can be used as a software library but also provides a representational state transfer interface. Spring, Camunda, and Drools served as the main frameworks for implementation. A formative usability evaluation of a demonstrator tool that uses the visualization yielded high acceptance among clinicians.

Conclusions: The novel guideline processing and visualization concept proved to be technically feasible. The approach addresses known problems of guideline-based clinical decision support systems. Further research is necessary to evaluate the applicability of the approach in specific medical use cases.

Keywords: clinical; clinical decision support system; clinical practice guideline; computer-assisted decision making; decision making; decision support techniques; eHealth; electronic health; guideline representation; software; support systems; workflow; workflow control patterns.

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Conflict of interest statement

Conflicts of Interest: None declared.

Figures

Figure 1
Figure 1
An example computer-interpretable guideline modeled in GuideLine Interchange Format (GLIF) using the GLIF Editor from the Medical Objects Knowledgebase.
Figure 2
Figure 2
Short checklist of the requirements for contextualized representation.
Figure 3
Figure 3
Context-based guideline visualization—Overview: Given a guideline definition and a treatment context (left), a context-sensitive guideline representation is generated (right).
Figure 4
Figure 4
Context-based guideline visualization—Processing steps: Intermediate results after each processing step during the generation of a context-sensitive guideline.
Figure 5
Figure 5
Schematic visualization illustrating stateless guideline processing by the system.
Figure 6
Figure 6
Two distinct interfaces provided by the system: internal software library (Java API) or HTTP (representational state transfer API). CDSS: clinical decision support system; GuLiNav: GuideLine Navigator; API: application programming interface; REST: representational state transfer.
Figure 7
Figure 7
Exemplary Drools rules that are part of the rule system.
Figure 8
Figure 8
Overarching diagram describing the relation between concepts and technologies used by the GuideLine Navigator. GuLiNav: GuideLine Navigator; REST: representational state transfer.
Figure 9
Figure 9
Screenshot of the system’s demonstrator front end.
Figure 10
Figure 10
The business process model and notation model used for the test case of the synchronization pattern.
See this image and copyright information in PMC

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