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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
Published on: September 20, 2018
Computerization framework for clinical practice guidelines by extending the XML guidelines element model (GEM).
Zafar Hashmi1, Tatjana Zrimec, Andrew Hopkins
1Center of Health Informatics, University New South Wales, Sydney, NSW 2052, Australia. zafarh@cse.unsw.edu.au
This study presents a framework to computerize clinical practice guidelines (CPG), enhancing decision-making for healthcare professionals. By adding context and semantics, it creates a structured knowledge base for point-of-care assistance.
Area of Science:
- Medical Informatics
- Knowledge Management
- Clinical Decision Support
Background:
- Evidence-based knowledge is crucial for clinical decision-making.
- Clinical practice guidelines (CPG) offer up-to-date best practices.
- Computerizing CPG can improve their effectiveness.
Purpose of the Study:
- To present a framework for computerizing clinical practice guidelines.
- To enhance CPG knowledge with context, semantics, and meta-information.
- To develop a structured CPG knowledge base for point-of-care assistance.
Main Methods:
- Implemented a knowledge management approach for CPG computerization.
- Utilized an extended-knowledge component ontology and UMLS.
- Transformed CPG knowledge into structured 'extended-knowledge components'.
Main Results:
- Developed a CPG knowledge computerization framework.
- Created a 'CPG knowledge base' from structured components.
- The framework enriches CPGs with context and semantics.
Conclusions:
- The developed framework effectively computerizes CPG knowledge.
- This facilitates better decision support for healthcare practitioners.
- The structured knowledge base aids in point-of-care assistance.