Summary

Solor Knowledge Architecture was created to integrate disparate knowledge sources and preserve the meaning of information for the interoperability of electronic health record data (i.e., semantic interoperability) critical to delivering safe Veteran care and leveraging standards-based clinical decision support. Solor is an open-source project of capabilities and services that overcomes interoperability complexities by assimilating disparate health knowledge sources into a consistent representation based on best practices of computer science.

Solor’s Knowledge Architecture employs the design principle called separation of concerns, whereby a system is divided into distinct sections, such that each section can address separate concerns. In this case, each architectural layer may build upon artifacts from lower layers, as described below:

Foundational Architecture of the Knowledge Architecture provides the common elements of interoperability, such as object identity, versioning, modularity, and knowledge representation.
Terminology Knowledge layer is responsible for structured sets of medical terms and codes that define concepts of interest, including descriptions, dialects, language, and semantic hierarchy.
Statement Model layer is responsible for defining how data elements are combined to create a statement. This layer reuses the artifacts defined in the Terminology Knowledge layer.
Assertional Knowledge layer uses the Terminology Knowledge layer concepts to specify non-defining facts that may be used by procedural knowledge algorithms.
Procedural Knowledge layer is responsible for information about standard ways to carry out specific procedures and other procedural guidelines, e.g., treatment protocols for diseases and order sets focused on certain patient situations.

Impact on Strategies

Increased reliance on computerized health records, including Electronic Health Records Systems, requires standardized medical terminology to encode health information consistently across systems and enterprises. Clinicians require not only objective quantitative measurements (e.g. 90 beats per minute for a patient's pulse) but also contextual or procedural context (e.g. pulse oximetry, manual) about past observations or requests for future interventions. While two quantitative measurements may be the same, the procedural information could indicate meaningful semantic differences and lead to different clinical interpretation and treatment. As information is exchanged across systems, the solution requires a common understanding of data and a method to support knowledge-representation and clinical decision rules based on common terminology and statements. Each component must address an aspect and, together they need to address the requirements of clinicians. Current HL7 standard implementations rely on profiles and templates to disambiguate statement and terminology, and provide sufficient precision for transactions, documents, and standards-based APIs. Therefore the architectural approach described here would be applicable to standards organizations developing interoperability-enterprise, and project-specific implementations in equal measure.

Functional decomposition—often referred to as a Separation of Concerns (SoC)—across components or sections with a specific purpose is a foundational design principle for complex system architecture. Enabling a SoC allows a complete system to be subdivided into distinct sections or components with well-defined functionality and dependencies. If successful, this approach allows individual sections to be able to be reused, as well as designed, implemented, and updated independently to address emerging requirements. This is especially useful and important in a medical context given how many different health information and clinical terminology projects are ongoing at any given time. Efforts are often uncoordinated and led by disparate and unrelated standards development organizations. In these cases, SoC allows teams to work independently, in coordination with each other, and reuse the resulting artifacts.

References

Veterans Affairs (VA) Terminology Strategy of the Health Informatics Business Line, VA/DoD Health Executive Committee. White Paper. 2021-03-12. 200728 -JCISI FINAL-v2 CDO comments 210312.1