Figure 1.
Attributes used to define Situation with Explicit Context concepts in the Systematized Nomenclature of Medicine, Clinical Terms (SNOMED-CT).
SNOMED-CT system provides concept models constructed in different clinical domains. An example of a concept model for Situation with Explicit Context is presented. This model includes six attributes: Associated Procedure, procedure Context, Temporal Context, Subject relationship Context, Associated finding, and Finding Context. Grey oval: concept domain; white oval: attributes; blue line: hasAttribute.
Figure 2.
Reference Information Model (RIM) core domain.
RIM of Health Level 7 (HL7), an existing terminology and information model standards, uses an object-oriented modeling approach derived from four main classes: Act, Entity, Role, and Participation (https://wiki.nci.nih.gov/display/SAIF/HL7+Reference+Information+Model).
Figure 3.
Representing “mother smoked when she was pregnant” using SNOMED-CT and HL7 RIM.
SNOMED-CT concept models provides a high level of sophistication for representing a unit of clinical concept, but it lacks a way of representing a phenotype data element, which usually does not require the level of sophistication but spans to multiple concept domains. Here we showed that the SNOMED-CT concept models do not include an explicit subject of information attribute thus subject of the finding is described using the relationship context attribute. HL7 RIM, an integrate model of healthcare domain, does not provide a complete set of attributes for the concept. HL7 RIM stores the key concepts “smoking during pregnancy” in an unspecific attribute “value” without specifying semantic roles of each concept.
Figure 4.
Structure of the HeightMeasure CEM.
(http://intermountainhealthcareorg/CEM/Pages/Detail.aspx?NCID=520862031&k=height.) CEM represents height measurement with sufficient details through various attributes and qualifiers/modifiers.
Figure 5.
Template models that serve as the basis for creating a CEM are available in six domains: Disease and Disorders, Procedures, Signs and Symptoms, Medications, Anatomical Sites, and Laboratory Tests. Detailed attributes and qualifiers/modifiers in these models are shown.
Figure 6.
Nested modeling of "Corticosteroid dose at follow up."
We modeled a phenotype variable description “Corticosteroid at follow up visit” using integrated multiple relevant CEM template models, including Signs and Symptoms CEM template model and Medication template model.
Figure 7.
In-house developed information model for Age related finding variables.
The core attributes of in-house developed information model include Topic, Subject of Information, Associated Event, and Linkage Concept. A phenotype variable example “age of mother first diagnosed with breast cancer” is represented with the model. As shown, “age” is identified as Topic, “mother” is identified as Subject of Information, “diagnosis of breast cancer” is identified as Associated Event, and first is identified as Linkage Concept.