snomed ct snomed ct snomed ct 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. 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 ctscreenshot of a snomed browserdeveloper(s)snomed internationaltypemedical termswebsitewww.snomed.orgas of2007 snomed ct is maintained and distributed by snomed international, an international non-profit standards development organization, located in london, uk. snomed international is the trading name of the international health terminology standards development organisation (ihtsdo), established in 2007. 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. 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. 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. history snomed started in 1965 as a systematized nomenclature of pathology (snop) and was further developed into a logic-based health care terminology. 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). the final product was released in january 2002. the international health terminology standards development organisation now considers snomed ct to be a brand name rather than an acronym. previously snomed was an acronym of 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. 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. the january 2020 release of the snomed ct international edition included more than 350,000 concepts. 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 nlm negotiation team was led by betsy humphreys, and the contract provided nlm with a perpetual license for the core snomed ct (in spanish and english) and its ongoing updates. 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. now trading as snomed international, the organization is responsible for "ongoing maintenance, development, quality assurance, and distribution of snomed ct" internationally and its membership consists of a number of the world's leading e-health countries and territories, including: argentina, australia, belgium, brunei, canada, czech republic, chile, denmark, estonia, hong kong, iceland, india, ireland, israel, lithuania, malaysia, malta, netherlands, new zealand, norway, poland, portugal, singapore, slovak republic, republic of slovenia, spain, sweden, switzerland, united kingdom, united states and uruguay. 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 underway 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. structure snomed ct consists of four primary core components: concept codes – numerical codes that identify clinical terms, primitive or defined, organized in hierarchies descriptions – textual descriptions of concept codes relationships – relationships between concept codes that have a related meaning reference sets – used to group concepts or descriptions into sets, including reference sets and cross-maps to other classifications and standards. snomed ct "concepts" are representational units that categorize all the things that characterize healthcare 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, e.g. 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. 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. semantic tag snomed ct assigns each concept a semantic tag. it is present in parenthesis in fully specified name of each concept. there can be multiple semantic tags used within each snomed ct top level hierarchy. for example, top level hierarchy of pharmaceutical/biologic product uses semantic tags of: product, medicinal product, medicinal product form and clinical drug. only one semantic tag can be used for each concept. the formal model underlying snomed ct snomed ct statistics (as of november 2016). sd stands for sufficiently defined. 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 2021, snomed ct content limits itself to a subset of the el++ formalism, restricting itself to the following operators: top, bottom primitive roles and concepts with asserted parent(s) for each concept definition and conjunction but not disjunction or negation role hierarchy but not role composition domain and range constraints existential but not universal restriction a restricted form of role inclusion axiom (xry ^ ysz => xrz) general concept inclusion axioms (a ⊆ b). for understanding the modelling, it is also important 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 a modelling approach referred to as 'proximal parent' approach. after 2015, a superior approach called "proximal primitive parent" has been adopted. precoordination and postcoordination snomed ct provides a compositional syntax that can be used to create expressions that represent clinical ideas which are not explicitly represented by snomed ct concepts. this mechanism exists because it is challenging to create and maintain all possible concepts upfront (as precoordinated 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. major electronic health record systems (ehrs) have repeatedly complained to ihtsdo and other standards organizations about the "complexity" of post-coordinated expressions. 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 | } postcoordination is an important desirable feature of a terminology. prior