Health Language Blog

SNOMED CT: Why it matters to you

Posted on 08/03/16


In Part One of our Terminology Standards blog series, we introduced the goal of using industry standards to achieve semantic interoperability and promote better information sharing. The second blog tackled coding and billing standards. This third installment describes the importance of SNOMED CT as the foundation for standardizing clinical content in EHRs.

By now, most healthcare organizations recognize the challenges associated with aggregating and sharing clinical information. It’s no secret that disparate health IT systems and clinical vocabularies create barriers to exchanging and using patient data in a meaningful way.

SNOMED CT®, or the Systematized Nomenclature of Medicine Clinical Terms, can help. A widely used clinical terminology set, SNOMED CT is the most comprehensive, multilingual clinical terminology in the world, encompassing more than 300,000 concepts, along with terms, synonyms, and definitions for human and non-human concepts. In fact, it was specifically designed to be a U.S. standard for electronic health information exchange.

Use of SNOMED CT increased when Stage 2 Meaningful Use required it for problem lists. Going forward, it will be a critical component to any strategy to support clinical data recording to improve patient care.

History of SNOMED CT

Developed by the College of American Pathologists in 1974 as the Systemized Nomenclature of Pathology (SNOP), the current format—SNOMED CT— was released in 2002 as a combination of SNOMED RT (Reference Terminology) and CTV3 (Clinical Terms Version 3). The clinical vocabulary is now owned and maintained by the International Health Terminology Standards Development Organization (IHTSDO) and used in more than fifty countries. SNOMED CT is being used in conjunction with the World Health Organization as the foundation for ICD-11.


SNOMED CT clinical concepts are organized hierarchically and represented by multiple levels of granularity. Hierarchies include:

  • Body Structure
  • Clinical Finding
  • Event
  • Procedure
  • Social Context
  • Substance

SNOMED CT comprises four files:

1) Concept file: codes that identify unique objects

2) Description file: terms that explain the concept

3) Relationship file: lateral associations between related concepts

4) Hierarchy file: vertical (hierarchical) structure

For example, the number representing the common cold may be linked to such descriptions as “common cold,” “acute coryza,” “acute infective rhinitis,” “cold,” or “head cold.”

Represented by a computer-readable numeric code, the January 2016 release of SNOMED CT includes more than 310,000 concepts, 794,000 descriptions, 19 hierarchies, and 920,000 relationships. These numbers continue to grow with each release.


Today, SNOMED CT is essential for recording and sharing clinical data such as patient problem lists and family, medical, and social histories in EHRs. It can be mapped to other international standards, such as ICD-9 and ICD-10, to better facilitate semantic interoperability. For instance, when clinical terms are seamlessly mapped between ICD-9, ICD-10, and SNOMED CT, revenue cycle efficiency and accuracy are boosted by eliminating productivity losses that would be associated with trying to identify the correct code from ICD-10’s 155,000 options.

By standardizing the way health IT systems read disparate terminologies, SNOMED CT enables consistent representations and reproductions of clinical content in EHRs. Other applications can use SNOMED CT for clinical decision support systems, laboratory reporting, emergency room charting, and cancer reporting.

Join us next week for Part 4 of our Terminology Standards series to explore the structure and function of LOINC, the HIPAA-required standard terminology for transmitting laboratory orders.


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Topics: SNOMED, data normalization, interoperability, SNOMED CT, standards

About the Author

Dale Davidson has almost 20 years’ experience in health care, specializing in provider coding and billing. She is certified by the AAPC as a CPC, CPC-I, CEMC and through AHIMA as an Approved ICD-10 trainer. In addition, she has 10 years’ experience in coder training, mentoring and education. Dale joined Health Language in 2013 and is responsible for helping clients map their data to standardized terminologies, create and maintain solid data governance practices, remediate for ICD-10, and provide consulting services for our 280+ content sets. She participates in implementations and is a subject matter expert in many of our applications.