SNOMED CT

SNOMED-CT
Developer(s) International Health Terminology Standards Development Organisation

SNOMED CT [lower-alpha 1] or SNOMED Clinical Terms is a systematically organized computer processable collection of medical terms providing codes, terms, synonyms and definitions used in clinical documentation and reporting. SNOMED CT is considered to be the most comprehensive, multilingual clinical healthcare terminology in the world.[2] The primary purpose of SNOMED CT is to encode the meanings that are used in health information and to support the effective clinical recording of data with the aim of improving patient care. SNOMED CT provides the core general terminology for electronic health records. SNOMED CT comprehensive coverage includes: clinical findings, symptoms, diagnoses, procedures, body structures, organisms and other etiologies, substances, pharmaceuticals, devices and specimens.

SNOMED CT is maintained and distributed by the International Health Terminology Standards Development Organisation (IHTSDO), an international non-profit standards development organization, located in Copenhagen, Denmark.

SNOMED CT provides for consistent information interchange and is fundamental to an interoperable electronic health record. It provides a consistent means to index, store, retrieve, and aggregate clinical data across specialties and sites of care. It also helps in organizing the content of electronic health records systems by reducing the variability in the way data are captured, encoded and used for clinical care of patients and research.[3] SNOMED CT can be used to directly record clinical details of individuals in electronic patient records. It also provides the user with a number of linkages to clinical care pathways, shared care plans and other knowledge resources, in order to facilitate informed decision-making, and to support long-term patient care. The availability of free automatic coding tools and services, which can return a ranked list of SNOMED CT descriptors to encode any clinical report, could help healthcare professionals to navigate the terminology.

SNOMED CT is a terminology that can cross-map to other international standards and classifications.[4] Specific language editions are available which augment the international edition and can contain language translations, as well as additional national terms. For example, SNOMED CT-AU, released in December 2009 in Australia, is based on the international version of SNOMED CT, but encompasses words and ideas that are clinically and technically unique to Australia.[5]

History

SNOMED was started in 1965 as a Systematized Nomenclature of Pathology (SNOP) and was further developed into a logic-based health care terminology.[1][6]

SNOMED CT was created in 1999 by the merger, expansion and restructuring of two large-scale terminologies: SNOMED Reference Terminology (SNOMED RT), developed by the College of American Pathologists (CAP); and the Clinical Terms Version 3 (CTV3) (formerly known as the Read codes), developed by the National Health Service of the United Kingdom (NHS).[7][8] The final product was released in January 2002.

The historical strength of SNOMED was its coverage of medical specialties. SNOMED RT, with over 120,000 concepts, was designed to serve as a common reference terminology for the aggregation and retrieval of pathology health care data recorded by multiple organizations and individuals. The strength of CTV3 was its terminologies for general practice. CTV3, with 200,000 interrelated concepts, was used for storing structured information about primary care encounters in individual, patient-based records.[9] Currently, SNOMED CT contains more than 311,000 active concepts and provides the core general terminology for the electronic health record (EHR).[10]

In July 2003, the National Library of Medicine (NLM), on behalf of the United States Department of Health and Human Services, entered into an agreement with the College of American Pathologists to make SNOMED CT available to U.S. users at no cost through the National Library of Medicine's Unified Medical Language System UMLS Metathesaurus. The contract provided NLM with a perpetual license for the core SNOMED CT (in Spanish and English) and its ongoing updates.[7][11][12]

In April 2007, SNOMED CT intellectual property rights were transferred from the CAP to the International Health Terminology Standards Development Organisation (IHTSDO) in order to promote international adoption and use of SNOMED CT. IHTSDO is responsible for "ongoing maintenance, development, quality assurance, and distribution of SNOMED CT" internationally [1][5][8] and consists of a number of the world's leading e-health countries, including: Australia, Canada, Czech Republic, Denmark, Estonia, Hong Kong, Iceland, Israel, Lithuania, Malaysia, Malta, Netherlands, New Zealand, Poland, Singapore, Slovak Republic, Slovenia, Spain, Sweden, United Kingdom, United States and Uruguay.[13]

SNOMED CT is a multinational and multilingual terminology, which can manage different languages and dialects. SNOMED CT is currently available in American English, British English, Spanish, Danish and Swedish, with other translations under way or nearly completed in French and Dutch. SNOMED CT cross maps to other terminologies, such as: ICD-9-CM, ICD-10, ICD-O-3, ICD-10-AM, Laboratory LOINC and OPCS-4. It supports ANSI, DICOM, HL7, and ISO standards. SNOMED CT is currently used in a joint project with the World Health Organization (WHO) as the ontological basis of the upcoming ICD-11.

Structure

SNOMED CT consists of four primary core components:

  1. Concept Codes - numerical codes that identify clinical terms, primitive or defined, organized in hierarchies
  2. Descriptions - textual descriptions of Concept Codes
  3. Relationships - relationships between Concept Codes that have a related meaning
  4. Reference Sets - used to group Concepts or Descriptions into sets, including reference sets and cross-maps to other classifications and standards.[14]

SNOMED CT "Concepts" are representational units that categorize all the things that characterize health care processes and need to be recorded therein. In 2011, SNOMED CT included more than 311,000 concepts, which are uniquely identified by a concept ID, i.e. the concept 22298006 refers to Myocardial infarction. All SNOMED CT concepts are organized into acyclic taxonomic (is-a) hierarchies; 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 a child of Infectious disease. The taxonomic structure allows data to be recorded and later accessed at different levels of aggregation. SNOMED CT concepts are linked by approximately 1,360,000 links, called relationships.[15]

Concepts are further described by various clinical terms or phrases, called Descriptions, which are divided into Fully Specified Names (FSNs), Preferred Terms (PTs), and Synonyms. Each Concept has exactly one FSN, which is unique across all of SNOMED CT. It has, in addition, exactly one PT, which has been decided by a group of clinicians to be the most common way of expressing the meaning of the concept. It may have zero to many Synonyms. Synonyms are additional terms and phrases used to refer to this concept. They do not have to be unique or unambiguous.

The formal model underlying SNOMED CT

SNOMED CT can be characterized as a multilingual thesaurus with an ontological foundation. Thesaurus-like features are concept–term relations such as the synonymous descriptions "Acute coryza", "Acute nasal catarrh", "Acute rhinitis", "Common cold" (as well as Spanish "resfrío común" and "rinitis infecciosa") for the concept 82272006.

Under ontological scrutiny, SNOMED-CT is a class hierarchy (with extensive overlap of classes in contrast to typical statistical classifications like ICD). This means that the SNOMED CT concept 82272006 defines the class of all the individual disease instances that match the criteria for "common cold" (e.g., one patient may have "head cold" noted in their record, and another may have "Acute coryza"; both can be found as instances of "common cold"). The superclass (Is-A) Relation relates classes in terms of inclusion of their members. That is, all individual "cold-processes" are also included in all superclasses of the class Common Cold, such as Viral upper respiratory tract infection (Figure).

Common cold as a primitive concept in SNOMED CT

SNOMED CT's relational statements are basically triplets of the form Concept1 - Relationx - Concept2, with Relationx being from a small number of relation types (called linkage concepts), e.g. finding site, due to, etc. The interpretation of these triplets is (implicitly) based on the semantics of a simple Description logic (DL). E.g., the triplet Common Cold - causative agent – Virus, corresponds to the first-order expression

forall x: instance-of (x, Common cold) -> exists y: instance-of (y, Virus) and causative-agent (y, x)

or the more intuitive DL expression

Common cold subClassOf causative-agent some Virus

In the Common cold example the concept description is "primitive", which means that necessary criteria are given that must be met for each instance, without being sufficient for classifying a disorder as an instance of Common Cold . In contrast, the example Viral upper respiratory tract infection depicts a fully described concept, which is represented in description logic as follows:

Viral upper respiratory tract infection as a defined concept in SNOMED CT
 Viral upper respiratory tract infection equivalentTo
 	Upper respiratory infection and Viral respiratory infection and
 		Causative-agent some Virus and
 		Finding-site some Upper respiratory tract structure and
 		Pathological-process some Infectious process

This means that each and every individual disorder for which all definitional criteria are met can be classified as an instance of Viral upper respiratory tract infection.

Description logics

As of 2011, SNOMED CT content limits itself to a subset of the EL++ formalism, restricting itself to the following operators:

For understanding the modelling, it is also import to look at the stated view of a concept versus the inferred view of the concept. In further considering the state view, SNOMED CT used in the past an modelling approach referred to as 'proximal parent' approach. After 2015, an superior approach called 'proximal primitive parent' has been adopted.

Precoordination and postcoordination

SNOMED CT provides a compositional syntax[16] that can be used to create expressions that represent clinical ideas which are not explicitly represented by SNOMED CT concepts.

For example, there is no explicit concept for a "third degree burn of left index finger caused by hot water". However, using the compositional syntax it can be represented as

284196006 | burn of skin | :
   116676008 | associated morphology | = 80247002 | third degree burn injury |
 , 272741003 | laterality | = 7771000 | left |
 , 246075003 | causative agent | = 47448006 | hot water |
 , 363698007 | finding site | = 83738005 | index finger structure

Such expressions are said to have been 'postcoordinated'. Post-coordination avoids the need to create large numbers of defined Concepts within SNOMED CT. However, many systems only allow for precoordinated representations. Reliable analysis and comparison of post-coordinated expressions is possible using appropriate algorithms machinery to efficiently process the expression taking account of the underlying description logic.

For example, the postcoordinated expression above can be transformed using a set of standard rules to the following "normal form expression" which enables comparison with similar concepts.

64572001 | disease | :
   246075003 | causative agent | = 47448006 | hot water |
 , 363698007 | finding site | = ( 83738005 | index finger structure | :
          272741003 | laterality | = 7771000 | left | )
 , { 116676008 | associated morphology | = 80247002 | third degree burn injury |
 , 363698007 | finding site | = 39937001 | skin structure | }

Human vs. Veterinary Content

International edition of SNOMED CT is only focusing on human term. In 2015, SNOMED CT clearly veterinary concepts (that were not human) were moved into a SNOMED CT veterinary extension. This extension is managed by a team at Virginia Tech University.

Known deficiencies and mitigation strategies

Earlier SNOMED versions had faceted structure ordered by semantic axes, requiring that more complex situations required to be coded by a coordination of different codes. This had two major shortcomings. On the one hand, the necessity of post-coordination was perceived as a user-unfriendly obstacle, which has certainly contributed to the rather low adoption of early SNOMED versions. On the other hand, uniform coding was difficult to obtain. E.g.,Acute appendicitis could be post-coordinated in three different ways[17] with no means to compute semantic equivalences. SNOMED RT had addressed this problem by introducing description logic formula. With the addition of CTV3 a large number of concepts were redefined using formal expressions. However, the fusion with CTV3, as a historically grown terminology with many close-to user descriptions, introduced some problems which still affect SNOMED CT. In addition to a confusing taxonomic web of many hierarchical levels with massive multiple inheritance (e.g. there are 36 taxonomic ancestors for Acute appendicitis), many ambiguous, context-dependent concepts have found their way into SNOMED CT. Pre-coordination was sometimes pushed to extremes, so there are, for example, 350 different concepts for burns found on the head.

A further phenomenon which characterizes parts of SNOMED CT is the so-called epistemic intrusion.[18] In principle, the task of terminology (and even an ontology) should be limited to providing context-free term or class meanings. The contextualization of these representational units should be ideally the task of an information model.[19] Human language is misleading here, as we use syntactically similar expression to represent categorically distinct entities, e.g. Ectopic pregnancy vs. Suspected pregnancy. The first one refers to a real pregnancy, the second one to a piece of (uncertain) information. In SNOMED CT most (but not all) of these context-dependent concepts are concentrated in the subhierachy Situation with explicit context. A major reason for why such concepts cannot be dispensed with is that SNOMED CT takes on, in many cases, the functionality of information models, as the latter do not exist in a given implementation.

With the establishment of IHTSDO; SNOMED CT became more accessible to a wider audience. Criticism of the state of the terminology was sparked by numerous substantive weaknesses as well as on the lack of quality assurance measures.[20] From the beginning IHTSDO was open regarding such (also academic) criticism. In the last few years considerable progress has been made regarding quality assurance and tooling.

The need for a more principled ontological foundation was gradually accepted, as well as a better understanding of description logic semantics. Redesign priorities were formulated regarding observables,[21] disorders, findings,[22] substances, organisms etc. Translation guidelines[23] were elaborated as well as guidelines for content submission requests and a strategy for the inclusion of pre-coordinated content. There are still known deficiencies regarding the "ontological commitment" of SNOMED CT,[24] e.g., the clarification of which kind of entity is an instance of a given SNOMED CT concept. The same term can be interpreted as a disorder or a patient with a disorder, for example Tumour might denote a process or a piece of tissue; Allergy may denote an allergic reaction or just an allergic disposition. A more recent strategy is the use of rigorously typed upper-level ontologies to disambiguate SNOMED CT content.

The increased take-up of SNOMED CT into applications in daily use across the world to support patient care is leading to a larger engaged community. This has led to an increase in the resource allocated to authoring SNOMED CT terms as well as to an increase in collaboration to take SNOMED CT into a robust industry used standard. This is leading to an increase in the number of software tools and development of materials that contribute to knowledge base to support implementation. A number of on-line communities that focus on particular aspects of SNOMED CT and its implementation are also developing.

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 existing pre-coordinated concepts. However, partly as the continuing fall-out from the merger with CTV3, SNOMED 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.

SNOMED CT validation

Using consistent rules is important for quality of SNOMED CT. To that end, in 2009, a prototype of Machine Readable Concept Model (MRCM) was created by SNOMED CT team. In a follow up work, this model is being revised to utilize SNOMED CT expression contraints.

SNOMED CT and ICD

SNOMED CT is a clinical terminology designed to capture and represent patient data for clinical purposes.[25] The International Statistical Classification of Diseases and Related Health Problems (ICD) is an internationally used medical classification system; which is used to assign diagnostic and, in some national modifications, procedural codes in order to produce coded data for statistical analysis, epidemiology, reimbursement and resource allocation.[26] Both systems use standardized definitions and form a common medical language used within electronic health record (EHR) systems.[27] SNOMED CT enables information input into an EHR system during the course of patient care, while ICD facilitates information retrieval, or output, for secondary data purposes.[27][28]

SNOMED CT ICD
Type Terminology System Classification System
Purpose Information Input Information Output
Function Describes and defines clinical information for primary data purposes Aggregates and categorizes clinical information for secondary data purposes

Use

SNOMED CT is used in a number of different ways, some of which are:

Use cases

More specifically, the following sample computer applications use SNOMED CT:

Access

SNOMED CT is maintained and distributed by IHTSDO, an international non-profit standards development organization, located in Copenhagen, Denmark.

The use of SNOMED CT in production systems requires a license. There are two models. On the one hand SNOMED CT can be achieved by national membership in the IHTSDO (charged according to gross national product). On the other hand, it can be used via a corporate business license (dependent on the number of end users). LDCs (least developed countries) can use SNOMED CT without charges.

For scientific research in medical informatics, for demonstrations or evaluation purposes SNOMED CT sources can be freely downloaded and used. The original SNOMED CT sources in tabular form are accessible by registered users of the Unified Medical Language System (UMLS) who have signed an agreement. Numerous online and offline browsers are available.

Those wishing to obtain a license for its use and to download SNOMED CT should contact their National Release Centre, links to which are provided on the IHTSDO website.

License free subsets

To facilitate adoption of SNOMED CT and use of SNOMED CT in other standards, there are license free subsets. For example, a set of 7,314 codes and descriptions is free for use by users of DICOM-compliant software (without restriction to IHTSDO member countries).[29]

Top level concepts

SNOMED CT concepts typically belong a single hierarchy. (with the exception of drug-device combined concepts). Some hierarchies, have a concept model defined (e.g., clinical findings). For other domains (e.g., Organism, Substance, Qualifier value), there is no concept model yet defined.

Event

As of 2016, the Event hierarchy does not have a concept model defined. In 2006, some concepts from the 'Clinical Finding' hierarchy were moved to the Event hierarchy. Those concepts retained some of their attributes. (e.g., causative agent)

See also

Notes

  1. ↑ The International Health Terminology Standards Development Organisation considers SNOMED CT to be a brand name rather than an acronym. Previously SNOMED was an acronym for Systematized Nomenclature Of Medicine, but it lost that meaning when SNOMED was combined with CTV3 (Clinical Terms Version 3) into the merged product called SNOMED Clinical Terms, which was shortened to SNOMED CT.[1]

References

  1. 1 2 3 "History Of SNOMED CT". International Health Terminology Standards Development Organisation. Retrieved 26 April 2015.
  2. ↑ Benson, Tim (2012). Principles of Health Interoperability HL7 and SNOMED. London: Springer. ISBN 978-1-4471-2800-7.
  3. ↑ Ruch, Patrick; Gobeill, Julien; Lovis, Christian; Geissbühler, Antoine (2008). "Automatic medical encoding with SNOMED categories". BMC Medical Informatics and Decision Making. 8: S6. doi:10.1186/1472-6947-8-S1-S6. PMC 2582793Freely accessible. PMID 19007443.
  4. ↑ "SNOMED CT & Other Terminologies, Classifications & Code Systems". International Health Terminology Standards Development Organisation. Retrieved 26 April 2015.
  5. 1 2 "Our Work: Clinical Terminology: SNOMED-CT-AU". Retrieved 26 April 2015.
  6. ↑ Cornet, Ronald; de Keizer, Nicolette (2008). "Forty years of SNOMED: a literature review". BMC Medical Informatics and Decision Making. 8: S2. doi:10.1186/1472-6947-8-S1-S2. PMC 2582789Freely accessible. PMID 19007439.
  7. 1 2 "SNOMED Clinical Terms To Be Added To UMLS Metathesaurus". United States National Library of Medicine. 24 May 2006. Retrieved 26 April 2015.
  8. 1 2 "FAQs: SNOMED CT in the UMLS". United States National Library of Medicine. 22 May 2012. Retrieved 26 April 2015.
  9. ↑ Stearns, Michael Q.; Price, Colin; Spackman, Kent A.; Wang, Amy Y. (2001). "SNOMED Clinical Terms: Overview of the Development Process and Project Status" (PDF). Proceedings of the AMIA Symposium. American Medical Informatics Association: 662–666. PMC 2243297Freely accessible. PMID 11825268.
  10. ↑
  11. ↑ "SNOMED license agreement". United States National Library of Medicine. 24 May 2006. Retrieved 26 April 2015.
  12. ↑ Unified Medical Language System
  13. ↑ "Members". International Health Terminology Standards Development Organisation. Retrieved 23 May 2016.
  14. ↑
  15. ↑ SNOMED CT Documentation is publicly available at http://www.snomed.org/doc
  16. ↑ SNOMED CT Compositional Grammar http://doc.ihtsdo.org/download/doc_CompositionalGrammarSpecificationAndGuide_Current-en-US_INT_20150522.pdf
  17. ↑ Spackman KA, Campbell KE. "Compositional concept representation using SNOMED: towards further convergence of clinical terminologies". Proc AMIA Symp. 1998: 740–744.
  18. ↑ Ingenerf, J; Linder, R (2009). "Assessing applicability of ontological principles to different types of biomedical vocabularies". Methods of Information in Medicine. 48 (5): 459–467. doi:10.3414/me0628.
  19. ↑ Rector A. (2008) Barriers, approaches and research priorities for integrating biomedical ontologies. Semantic Health Deliverable 6.1 http://www.semantichealth.org/DELIVERABLES/SemanticHEALTH_D6_1.pdf
  20. ↑ Stefan Schulz; Boontawee Suntisrivaraporn; Franz Baader; Martin Boeker (April 2009). "SNOMED reaching its adolescence: Ontologists' and logicians' health check". International Journal of Medical Informatics. 78 (Supplement 1): S86–S94. doi:10.1016/j.ijmedinf.2008.06.004. PMID 18789754.
  21. ↑ SNOMED CT® Style Guide: Observable Entities and Evaluation Procedures (Laboratory) Draft IHTSDO Standard v1.0, 2010-06-30, http://ihtsdo.org/fileadmin/user_upload/Docs_01/Publications/Drafts_for_review/SNOMED_CT_Style_Guide_Observables_v1.0.pdf
  22. ↑ Schulz, S; Spackman, K; James, A; Cocos, C; Boeker, M (May 2011). "Scalable representations of diseases in biomedical ontologies". Journal of Biomedical Semantics. 17 (2(Suppl 2)): S6.
  23. ↑ http://ihtsdo.org/fileadmin/user_upload/Docs_01/About_IHTSDO/Publications/IHTSDO_Translation_Guidelines_v2.00_20100407.pdf
  24. ↑ Schulz, S; Cornet, R; Spackman, K Consolidating SNOMED CT’s . Applied ontology. 2011; 6: 1-11.
  25. ↑ Kostick, K. (2012) SNOMED CT Integral Part of Quality HER Documentation. Journal of AHIMA 83.10 (October 2012): 72-75.
  26. ↑ http://www.who.int/classifications/icd/en/
  27. 1 2 Bowman, S. (2005) Coordinating SNOMED-CT and ICD-10: Getting the Most out of Electronic Health Record Systems. Journal of AHIMA 76(7):60-61. www.ahima.org/perspectives
  28. ↑ Truran, D., Saad, P. Zhang, M., Innes, K. (2010) SNOMED CT and its place in health information management practice. Health Information Management Journal Vol 39 (2):37-39 ISSN 1833-3583 (Print) 1833-3575 (Online)
  29. ↑ https://confluence.ihtsdotools.org/pages/viewrecentblogposts.action?key=ILS
This article is issued from Wikipedia - version of the 12/2/2016. The text is available under the Creative Commons Attribution/Share Alike but additional terms may apply for the media files.