EP01.03 - Rule Based Approach for Integrating SNOMED CT, LOINC, and RxNorm
e-Health ePoster Library. Shayegani S. Jun 7, 2016; 131588; EP01.03
Shapoor Shayegani
Shapoor Shayegani
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Purpose/Objectives: SNOMED CT, LOINC, and RxNorm are three comprehensive and widely adopted terminologies used by several organizations across the world. SNOMED CT is the most comprehensive and precise clinical health terminology product in the world. LOINC provides a common language for clinical and laboratory observations, and RxNorm provides normalized names for clinical drugs. Two major challenges associated with the use of these terminologies, are a) considerable overlap exists between SNOMED CT and LOINC, as well as between SNOMED CT and RxNorm, and the decision on which code to use when there is overlap has been mainly subjective leading to confusions; and b) the three terminologies have disparate attributes and structure, making it hard to integrate their use. This presentation aims to describe a rule based approach for bringing parts of SNOMED CT, LOINC, and RxNorm into one integrated view, in order to facilitate utilizing concepts from any of the abovementioned three terminologies without worrying about their disparate attributes or their different structure. Methodology/Approach: The methodology consisted of re-engineering the relational structure of RxNorm to allow integration of its content into SNOMED CT, applying a rule based approach to place RxNorm concepts within the hierarchical body of SNOMED CT based on the semantics and the type of RxNorm concepts, as well as defining rules based on LOINC parts, to model LOINC concepts using SNOMED CT concept model attributes, and running a description logic-based classifier to place RxNorm and LOINC concepts underneath appropriate SNOMED CT concepts. The LOINC-SNOMED CT Cooperative Project Technology Preview was also reviewed and utilized in the design of the rules. Finding/Results: More than 31,000 LOINC concepts as well as over 8,500 RxNorm concepts were modeled based on SNOMED CT concept model and were placed in SNOMED CT's hierarchy by a Description Logic classifier. The resulting artifact combines parts of the three terminologies under the overall structure of SNOMED CT, thus creating a single representation of all concepts regardless of the provenance of those concepts. This integration will allow the user to more efficiently perform analysis and utilize the concepts from these foundational sources for encoded clinical data, decision support, analytics, etc. It will also allow applying description logic (based on SNOMED CT's concept model) to the concepts of LOINC and RxNorm, where none currently exists. This project also helped identify some terminology content enhancement suggestions which will result in working with the respective SDOs to improve the content. Conclusion/Implication/Recommendations: Integration of terminology products is essential in providing a smoother path to interoperability. We believe this project makes significant contribution to achieving the overall objective of interoperability and can inform future advances in this regard. 140 Character Summary: This presentation aims to describe a rule based approach for integrating SNOMED CT, LOINC, and RxNorm under the overall structure of SNOMED CT.
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