A method for structuring complex clinical knowledge and its representational formalisms to support composite...

Area of Science:

• Medical Informatics
• Knowledge Engineering
• Systems Engineering

Background:

• Clinical knowledge representation formalisms are often suboptimal, hindering accurate capture, sharing, and implementation.
• Existing formalisms lack the fidelity to represent complex medical expertise thoroughly and concisely.
• This leads to difficulties in improving patient care through clinical information systems.

Purpose of the Study:

• To develop a systematic method for addressing complexities in knowledge composition and interoperability.
• To create a standards-based representational formalism for medical knowledge.
• To improve the quality and usability of medical expertise in clinical settings.

Main Methods:

• Synthesized cross-industry frameworks from Healthcare, Linguistics, System Engineering, Standards Development, and Knowledge Engineering.
• Utilized IEEE 42010, MetaObject Facility, Semantic Triangle, and Ontology Framework.
• Applied system engineering principles: separation of concerns, cohesion, and loose coupling.

Main Results:

• Defined a "Multilayer Metamodel for Representation and Knowledge" (M*R/K) reference framework.
• Established a standard vocabulary for organizing medical knowledge perspectives, concepts, and relationships.
• Covered the lifecycle from language creation to knowledge implementation in Electronic Health Records (EHRs).

Conclusions:

• M*R/K offers a systematic approach to knowledge composition and interoperability challenges in medical knowledge representation.
• The framework guides the development, assessment, and coordinated use of knowledge representation formalisms.
• M*R/K can promote alignment and aggregated use of domain-specific languages in artifacts like clinical practice guidelines (CPGs).