SNOMED Print

SNOMED CT (Systematized Nomenclature of Medicine - Clinical Terms), is a systematically organized computer processable collection of medical terminology covering most areas of clinical information such as diseases, findings, procedures, microorganisms, pharmaceuticals etc. It allows a consistent way to index, store, retrieve, and aggregate clinical data across specialties and sites of care. It also helps organizing the content of medical records, reducing the variability in the way data is captured, encoded and used for clinical care of patients and research.

Purpose
Clinicians and organizations use different clinical terms that mean the same thing. For example, the terms heart attack, myocardial infarction, and MI may mean the same thing to a cardiologist, but, to a computer, they are all different. There is a need to exchange clinical information consistently between different health care providers, care settings, researchers and others (semantic interoperability),and because medical information is recorded differently from place to place (on paper or electronically), a comprehensive, unified medical terminology system is needed as part of the information infrastructure.

Structure
SNOMED CT consists of over a million medical Concepts. For example 22298006 means myocardial infarction (MI). The concepts are arranged in a type or IS-A hierarchy. For example, Viral pneumonia IS-A Infectious pneumonia IS-A Pneumonia IS-A Lung disease. Concepts may have multiple parents, for example Infectious pneumonia is also an Infectious disease. The Concept graph must be acyclic - a parent cannot be its own child. Concepts can have roles, eg. Viral pneumonia has a role Causitive Agent which must be a Virus.
Some Concepts can be primitive, such as Virus. But SNOMED also allows concepts to be defined by a predicate. For example Viral pneumonia might be defined as Pneumonia that is caused by a Virus. Defined concepts are based on description logic.
Descriptions are terms or names (synonyms) assigned to a concept. Concepts often have several descriptions, and a description may sometimes refer to more than one concept. For example, Immunosuppression might be a therapy or a finding.
Upper level concepts include procedures, drugs, findings & disorders, events, anatomy, organisms.
SNOMED concepts are often refered to by an information model such as HL7.
If concepts are refered to directly by an information model then they are considered to be 'pre-coordinated'.
But SNOMED CT also enables more complex descriptions to be used. For example, there might not be an explicit concept for a burn between the toes. But it could be described as

Such expressions are said to have been 'post-coordinated'. When used, post coordinated conditions avoids the need to create large numbers of Defined Concepts within SNOMED. However, many systems only use pre-coordinated conditions.
Reliable analysis and comparison of any such post-coordinated expressions - with respect to both those concepts already within the SNOMED CT release dataset and any other ad hoc concepts created or yet to be created by its community of end users - properly requires the application of an appropriate description logic classification algorithm. As of 2007, SNOMED CT content limits itself to a subset of the EL++ formalism, restricting itself to the following operators:

The logic may be extended in the near future to include General Concept Inclusion Axioms.

In theory, description logic reasoning can be applied to any new candidate post-coordinated expressions in order to assess whether it is a parent or ancestor of, a child or other descendent of, or semantically equivalent to any existing concept from the 370,000 pre-coordinated concepts which are already distributed worldwide. However, partly as the continuing fall-out from the merger with CTV3, SNOMED content in 2007 still contains undiscovered semantically duplicate primitive and defined concepts. Additionally, many concepts remain primitive whilst their semantics can also be legitimately defined in terms of other primitives and roles concurrently in the system. Because of these omissions and actual or possible redundancies of semantic content, real-world performance of algorithms to infer subsumption or semantic equivalence will be unpredictably imperfect.

Use
SNOMED CT is one of a suite of designated data standards for use in U.S. Federal Government systems for the electronic exchange of clinical health information.

Sample Computer Applications Using SNOMED CT

  • Electronic Medical Records
  • Computerized Provider Order Entry Such As E-Prescribing Or Laboratory Order Entry
  • Remote Intensive Care Unit Monitoring
  • Laboratory Reporting
  • Emergency Room Charting
  • Cancer Reporting
  • Genetic Databases