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Exploiting Semantic Web Technologies to Develop OWL-Based Clinical Practice Guideline Execution Engines
IEEE Journal of Biomedical and Health Informatics
|December 23, 2014
Summary
This study introduces three new clinical practice guideline (CPG) execution engines using semantic web technologies. These engines improve the execution of complex, evidence-based guidelines for better clinical decision support.
Area of Science:
- Computer science
- Medical informatics
- Artificial intelligence
Background:
- Computerizing paper-based clinical practice guidelines (CPG) offers evidence-informed decision support at the point of care.
- Semantic web technologies, particularly Web Ontology Language (OWL), are used to represent computerized CPG.
- Existing semantic web reasoning-based CPG execution engines struggle with high expressivity, cognitive load, and updating complexities.
Purpose of the Study:
- To address limitations in existing CPG execution engines.
- To develop and evaluate novel CPG execution engines with enhanced capabilities.
- To improve the shareability and executional power of computerized CPG.
Main Methods:
- Developed three CPG execution engines based on OWL 1 DL, OWL 2 DL, and OWL 2 DL + Semantic Web Rule Language (SWRL).
- Utilized semantic web reasoning for CPG execution, enabling broader compatibility with reasoners and triple stores.
- Evaluated technical performance (CPU time) and medical correctness (relevance, safety, ordering) using diverse CPG and expert review.
Main Results:
- The developed engines demonstrate efficient CPU time and valid recommendation generation compared to existing systems.
- OWL 2 DL and OWL 2 DL + SWRL engines provide enhanced capabilities for executing highly complex CPG.
- Medical evaluations confirmed the validity and appropriateness of CPG-mediated therapy plans for various patient scenarios.
Conclusions:
- The new OWL-based CPG execution engines overcome limitations of previous systems, offering greater expressivity and efficiency.
- These engines enhance the practical application of computerized CPG, supporting physicians with reliable decision support.
- The developed approach increases the shareability and reusability of computerized clinical guidelines.
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