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Developing guideline-based decision support systems using protégé and jess.
Chiehfeng Cliff Chen1, Kung Chen, Chien-Yeh Hsu
1Graduate Institute of Medical Sciences, College of Medicine, Taipei Medical University, Taiwan.
Computer Methods and Programs in Biomedicine
|July 3, 2010
Summary
Computerized physician order entry and electronic prescriptions are vital for medication safety. New tools streamline the creation of clinical decision support systems, accelerating their adoption in healthcare.
Area of Science:
- Health Informatics
- Clinical Decision Support
- Medical Error Reduction
Background:
- The Institute of Medicine highlights computerized physician order entry (CPOE) and electronic prescribing (e-prescribing) as crucial for enhancing patient safety and reducing medication errors.
- Computerized clinical decision support systems (CDSS) show potential in improving healthcare practitioner performance.
- Current CDSS development cycles are lengthy, hindering widespread implementation.
Purpose of the Study:
- To present a novel suite of tools for modeling and executing clinical practice guidelines.
- To enable the automated synthesis of clinical decision support systems (CDSS) from these guidelines.
- To facilitate the easier and wider application of CDSS in clinical practice.
Main Methods:
- Development of a guideline modeling and execution tool suite.
- Leveraging Protégé, Jess, and Java technologies for system construction.
- Focus on tools designed for ease of use and automated CDSS synthesis.
Main Results:
- The presented tools simplify the process of guideline modeling and execution.
- Automated synthesis of CDSS from clinical practice guidelines of moderate complexity is achievable.
- The system is designed for user-friendliness, reducing the barrier to CDSS development.
Conclusions:
- The developed tool suite offers a practical solution for accelerating the creation and deployment of CDSS.
- This approach can significantly reduce the cycle time for developing and implementing CDSS.
- Facilitates the wider adoption of evidence-based practices through accessible clinical decision support.
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