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SNOMED CT

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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 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.

Contents

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 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.

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.

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, tope 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 Coldcausative agentVirus, 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

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 an 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 exist 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

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.

Postcoordination is an important desirable feature of a terminology. Prior 2020, International Classification of Diseases (ICD) did not allow post-coordination and SNOMED CT was the only terminology that supported postcoordination. Since 2020, a new version of ICD-11 now also supports postcoordination.

Veterinary content

The International Edition of SNOMED CT only includes human terms. In 2014, clearly veterinary concepts were moved into a SNOMED CT veterinary extension. This extension is managed by the Veterinary Terminology Services Lab at the Va-Md College of Veterinary Medicine at Virginia Tech.

Known deficiencies and mitigation strategies

This section may be too technical for most readers to understand. Please help improve it to make it understandable to non-experts, without removing the technical details.(June 2019) ()

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 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. 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. 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. 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, disorders, findings, substances, organisms etc. Translation guidelines 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, 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 for research 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 descendant 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 the quality of SNOMED CT. To that end, in 2009, a prototype Machine Readable Concept Model (MRCM) was created by the SNOMED CT team. In a follow up work, this model is being revised to utilize SNOMED CT expression constraints.

SNOMED CT and other terminologies

SNOMED CT and ICD

SNOMED CT is a clinical terminology designed to capture and represent patient data for clinical purposes. 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. Both systems use standardized definitions and form a common medical language used within electronic health record (EHR) systems. 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. In 2010s, the advantage of SNOMED CT over ICD was the multiple parent hierarchy of SNOMED CT. Since 2020 release of ICD 11, this advantage is less important because ICD-11 foundational level allows an ICD 11 concept to have multiple parents.

SNOMED CT ICD (Mortality and Morbidity Statistics view)
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

SNOMED CT and LOINC

LOINC is a terminology that contains laboratory tests. Since 2017, SNOMED International started creating terms for LOINC components and created a set of SNOMED CT expressions that capture the meaning of many LOINC terms.

SNOMED CT and MedDRA

There is overlap between MedDRA and SNOMED CT that is not beneficial for pharmaceutical industry. In 2021, two maps map between SNOMED CT and MedDRA were jointly published by both organizations (from SNOMED CT to MedDRA and from MedDRA to SNOMED CT).

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

  • It captures clinical information at the level of detail needed for the provision of healthcare
  • Through sharing data it can reduce the need to repeat health history at each new encounter with a healthcare professional
  • Information can be recorded by different people in different locations and combined into simple information views within the patient record
  • Use of a common terminology decreases the potential for differing interpretation of information
  • Electronic recording in a common way reduces errors and can help to ensure completeness in recording all relevant data
  • Standardised information makes analysis easier, supporting quality, cost effective practice, research and future clinical guideline development
  • A clinical terminology allows a health care provider to identify patients based on specified coded information, and more effectively manage screening, treatment and follow up

Use cases

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

  • Electronic Health Record Systems
  • Computerized Provider Order Entry CPOE such as E-Prescribing or Laboratory Order Entry
  • Catalogues of clinical services; e.g., for Diagnostic Imaging procedures
  • Knowledge databases used in clinical decision support systems (CDSS)
  • Remote Intensive Care Unit Monitoring
  • Laboratory Reporting
  • Emergency Room Charting
  • Cancer Reporting
  • Genetic Databases

Access

SNOMED CT is maintained and distributed by SNOMED International, an international non-profit standards development organization, located in London, UK..

The use of SNOMED CT in production systems requires a license. There are two types of license:

  1. Country/territory membership in SNOMED International (charged according to gross national product).
  2. Affiliate 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).

Global Patient Set (GPS) subset

GPS was released in Sep 2019 and contains 21 782 concepts.

SNOMED CT concepts typically belong to 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.

Procedure

Procedure example

Concept in this hierarchy represent procedures performed on a patient. There is a well established defined concept model for procedures. Procedure site (direct or indirect) specifies on what part of body the procedure is performed. A separate set of rules exist for evaluation procedures. Evaluation procedures are procedures where evidence is evaluated to support the determination of a value, inference or conclusion. Evaluation procedures have additional attributes, such as 'Has specimen','Property' or 'Measurement method'.

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)

Observable entities

SNOMED International is working on creating a concept model for observable entities.

Body Structure

Body parts represent one of the largest hierarchies within SNOMED CT. The modeling is based on Foundational Model of Anatomy but it differs from the model in some aspects (e.g., region is taken as 3D region and not a 2D region). Important attributes include: 'Laterality', several types of 'Part of' relationships, and 'Is a'.

Pharmaceutical / biologic product

Pharmaceutical product example

Pharmaceutical and biologic products are modeled using constructs of active ingredient, presentation strength, and basis of strength. Since 2018, harmonization of SNOMED CT drug content with IDMP standard is an editorial goal. The following types of entities are present:

Medicinal product

A higher level term grouping drugs. For example, 398731002 | Product containing sulfamethoxazole and trimethoprim (medicinal product) |

Clinical Drug

Concept that represents a concrete drug product as used in clinical practice. For example, 317335000 | Product containing precisely esomeprazole 20milligram/1 each conventional release oral tablet (clinical drug)|

Dose Form

Concept representing how the product is delivered. For example, 385219001 | Conventional release solution for injection (dose form) |.

A goal for SNOMED CT is consistency. Several mechanisms are employed to ensure this. Machine readable concept model is used to check for compliance with a set of rules. Rules for creating fully specified name for a concept define allowed and not allowed patterns. When defining a concept, a proximal primitive parent rule is used (in stated definition) to employ best description logic derived classification of concepts.

Separate conventions govern grouping of relationships. Ability to group related relationships is an important strength of SNOMED CT. Rules in Machine Readable Concept Model (MRCM) specify by domain which relationships are never grouped (e.g., 'Is a' or 'Laterality' attributes) and which relationships are always grouped (e.g., 'Finding site'). For correct subsumption inference, some relationships may be in a group but consist of a single relationship.

Another convention for SNOMED CT international edition is to avoid creating intermediate primitive concepts (unless medically necessary and impossible to define with existing concept model). An intermediate primitive (=not defined) concept is a non-defined concept that has children concepts and parent concepts. This convention is related to the use of description logic to facilitate terminology maintenance. Because primitive concepts can not be processed by the description logic classifier, the maintenance of such concepts relies solely on human editors. Adding new intermediate primitive concepts requires changes to all affected concepts and is demanding in terms of terminology maintenance.

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SNOMED CT
SNOMED CT Language Watch Edit This article includes inline citations but they are not properly formatted Please improve this article by correcting them September 2019 Learn how and when to remove this template message SNOMED CT note 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 3 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 CTDeveloper s SNOMED International 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 4 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 5 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 6 Contents 1 History 2 Structure 2 1 Semantic tag 2 2 The formal model underlying SNOMED CT 2 3 Description logics 2 4 Precoordination and postcoordination 2 5 Veterinary content 2 6 Known deficiencies and mitigation strategies 2 7 SNOMED CT validation 2 8 SNOMED CT and other terminologies 2 8 1 SNOMED CT and ICD 2 8 2 SNOMED CT and LOINC 2 8 3 SNOMED CT and MedDRA 3 Use 3 1 Use cases 3 2 Access 3 2 1 License free subsets 3 2 2 Global Patient Set GPS subset 4 Top level concepts 4 1 Procedure 4 2 Event 4 3 Observable entities 4 4 Body Structure 4 5 Pharmaceutical biologic product 4 5 1 Medicinal product 4 5 2 Clinical Drug 4 5 3 Dose Form 5 Authoring conventions 6 See also 7 Notes 8 References 9 External linksHistory EditSNOMED started in 1965 as a Systematized Nomenclature of Pathology SNOP and was further developed into a logic based health care terminology 1 7 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 8 The final product was released in January 2002 9 10 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 11 The January 2020 release of the SNOMED CT International Edition included more than 350 000 concepts 12 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 13 and the contract provided NLM with a perpetual license for the core SNOMED CT in Spanish and English and its ongoing updates 9 14 15 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 1 6 10 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 16 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 EditSNOMED 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 17 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 18 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 Edit 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 tope 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 Edit 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 resfrio comun 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 i Common cold i gt exists y instance of y i Virus i and b causative agent b y x or the more intuitive DL expression i Common cold i subClassOf b causative agent b some i Virus i 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 Edit 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 gt 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 an modelling approach referred to as proximal parent approach After 2015 a superior approach called proximal primitive parent has been adopted Precoordination and postcoordination Edit SNOMED CT provides a compositional syntax 19 that can be used to create expressions that represent clinical ideas which are not explicitly represented by SNOMED CT concepts This mechanism exist 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 2020 International Classification of Diseases ICD did not allow post coordination and SNOMED CT was the only terminology that supported postcoordination Since 2020 a new version of ICD 11 now also supports postcoordination Veterinary content Edit The International Edition of SNOMED CT only includes human terms In 2014 clearly veterinary concepts were moved into a SNOMED CT veterinary extension This extension is managed by the Veterinary Terminology Services Lab 20 at the Va Md College of Veterinary Medicine at Virginia Tech Known deficiencies and mitigation strategies Edit This section may be too technical for most readers to understand Please help improve it to make it understandable to non experts without removing the technical details June 2019 Learn how and when to remove this template message 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 21 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 22 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 23 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 24 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 25 disorders findings 26 substances organisms etc Translation guidelines 27 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 28 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 for research 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 descendant 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 Edit Using consistent rules is important for the quality of SNOMED CT To that end in 2009 a prototype Machine Readable Concept Model MRCM was created by the SNOMED CT team In a follow up work this model is being revised to utilize SNOMED CT expression constraints SNOMED CT and other terminologies Edit SNOMED CT and ICD Edit SNOMED CT is a clinical terminology designed to capture and represent patient data for clinical purposes 29 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 30 Both systems use standardized definitions and form a common medical language used within electronic health record EHR systems 31 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 31 32 In 2010s the advantage of SNOMED CT over ICD was the multiple parent hierarchy of SNOMED CT Since 2020 release of ICD 11 this advantage is less important because ICD 11 foundational level allows an ICD 11 concept to have multiple parents SNOMED CT ICD Mortality and Morbidity Statistics view Type Terminology System Classification SystemPurpose Information Input Information OutputFunction Describes and defines clinical information for primary data purposes Aggregates and categorizes clinical information for secondary data purposesSNOMED CT and LOINC Edit LOINC is a terminology that contains laboratory tests Since 2017 SNOMED International started creating terms for LOINC components and created a set of SNOMED CT expressions that capture the meaning of many LOINC terms SNOMED CT and MedDRA Edit There is overlap between MedDRA and SNOMED CT that is not beneficial for pharmaceutical industry In 2021 two maps map between SNOMED CT and MedDRA were jointly published by both organizations from SNOMED CT to MedDRA and from MedDRA to SNOMED CT 33 Use EditSNOMED CT is used in a number of different ways some of which are It captures clinical information at the level of detail needed for the provision of healthcare Through sharing data it can reduce the need to repeat health history at each new encounter with a healthcare professional Information can be recorded by different people in different locations and combined into simple information views within the patient record Use of a common terminology decreases the potential for differing interpretation of information Electronic recording in a common way reduces errors and can help to ensure completeness in recording all relevant data Standardised information makes analysis easier supporting quality cost effective practice research and future clinical guideline development A clinical terminology allows a health care provider to identify patients based on specified coded information and more effectively manage screening treatment and follow upUse cases Edit More specifically the following sample computer applications use SNOMED CT Electronic Health Record Systems Computerized Provider Order Entry CPOE such as E Prescribing or Laboratory Order Entry Catalogues of clinical services e g for Diagnostic Imaging procedures Knowledge databases used in clinical decision support systems CDSS Remote Intensive Care Unit Monitoring Laboratory Reporting Emergency Room Charting Cancer Reporting Genetic DatabasesAccess Edit SNOMED CT is maintained and distributed by SNOMED International an international non profit standards development organization located in London UK The use of SNOMED CT in production systems requires a license There are two types of license Country territory membership in SNOMED International charged according to gross national product Affiliate 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 Edit 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 34 Global Patient Set GPS subset Edit GPS was released in Sep 2019 and contains 21 782 concepts 35 Top level concepts EditSNOMED CT concepts typically belong to 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 Procedure Edit Procedure example Concept in this hierarchy represent procedures performed on a patient There is a well established defined concept model for procedures Procedure site direct or indirect specifies on what part of body the procedure is performed A separate set of rules exist for evaluation procedures Evaluation procedures are procedures where evidence is evaluated to support the determination of a value inference or conclusion Evaluation procedures have additional attributes such as Has specimen Property or Measurement method Event Edit 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 Observable entities Edit SNOMED International is working on creating a concept model for observable entities 36 Body Structure Edit Body parts represent one of the largest hierarchies within SNOMED CT The modeling is based on Foundational Model of Anatomy but it differs from the model in some aspects e g region is taken as 3D region and not a 2D region Important attributes include Laterality several types of Part of relationships and Is a Pharmaceutical biologic product Edit Pharmaceutical product example Pharmaceutical and biologic products are modeled using constructs of active ingredient presentation strength and basis of strength Since 2018 harmonization of SNOMED CT drug content with IDMP standard is an editorial goal The following types of entities are present Medicinal product Edit A higher level term grouping drugs For example 398731002 Product containing sulfamethoxazole and trimethoprim medicinal product Clinical Drug Edit Concept that represents a concrete drug product as used in clinical practice For example 317335000 Product containing precisely esomeprazole 20milligram 1 each conventional release oral tablet clinical drug Dose Form Edit Concept representing how the product is delivered For example 385219001 Conventional release solution for injection dose form Authoring conventions EditA goal for SNOMED CT is consistency Several mechanisms are employed to ensure this Machine readable concept model is used to check for compliance with a set of rules Rules for creating fully specified name for a concept define allowed and not allowed patterns 37 When defining a concept a proximal primitive parent rule is used in stated definition to employ best description logic derived classification of concepts Separate conventions govern grouping of relationships Ability to group related relationships is an important strength of SNOMED CT Rules in Machine Readable Concept Model MRCM 38 specify by domain which relationships are never grouped e g Is a or Laterality attributes and which relationships are always grouped e g Finding site For correct subsumption inference some relationships may be in a group but consist of a single relationship Another convention for SNOMED CT international edition is to avoid creating intermediate primitive concepts unless medically necessary and impossible to define with existing concept model An intermediate primitive not defined concept is a non defined concept that has children concepts and parent concepts This convention is related to the use of description logic to facilitate terminology maintenance Because primitive concepts can not be processed by the description logic classifier the maintenance of such concepts relies solely on human editors Adding new intermediate primitive concepts requires changes to all affected concepts and is demanding in terms of terminology maintenance See also EditCDISC Clinical Care Classification System DOCLE EN 13606 MEDCIN MedDRA Omaha System ICD11 Foundational Model of AnatomyNotes Edit 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 Wikidata has the property SNOMED CT identifier P5806 see uses References Edit a b c History Of SNOMED CT International Health Terminology Standards Development Organisation Retrieved 26 April 2015 Benson Tim 2012 Principles of Health Interoperability HL7 and SNOMED London England Springer ISBN 978 1 4471 2800 7 Health Information Technology and Health Data Standards at NLM www nlm nih gov Ruch Patrick Gobeill Julien Lovis Christian Geissbuhler 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 2582793 PMID 19007443 Use SNOMED CT www snomed org International Health Terminology Standards Development Organisation Retrieved 5 August 2020 a b Our Work Clinical Terminology SNOMED CT AU Retrieved 26 April 2015 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 2582789 PMID 19007439 Price Colin 2000 Towards a New International Terminology for Health Read Clinical Terms and SNOMED Journal of Informatics in Primary Care 9 1 15 17 a b SNOMED Clinical Terms To Be Added To UMLS Metathesaurus United States National Library of Medicine 24 May 2006 Retrieved 26 April 2015 a b FAQs SNOMED CT in the UMLS United States National Library of Medicine 22 May 2012 Retrieved 26 April 2015 Stearns Michael Q Price Colin Spackman Kent A Wang Amy Y 2001 SNOMED Clinical Terms Overview of the Development Process and Project Status Proceedings of the AMIA Symposium American Medical Informatics Association 662 666 PMC 2243297 PMID 11825268 5 Step briefing www snomed org Retrieved 5 August 2020 Proposed Snomed licensing agreement could be watershed development for healthcare Modern Healthcare 2003 02 21 Retrieved 2019 05 31 SNOMED license agreement United States National Library of Medicine 24 May 2006 Retrieved 26 April 2015 SNOMED Clinical Terms SNOMED CT www nlm nih gov Members www snomed org International Health Terminology Standards Development Organisation Retrieved 5 August 2020 SNOMED CT and HL7 Bringing Standards Together SNOMED CT Documentation is publicly available at http www snomed org doc SNOMED CT Compositional Grammar https confluence ihtsdotools org display DOCSCG Compositional Grammar Specification and Guide Veterinary Terminology Services Lab Spackman KA Campbell KE Compositional concept representation using SNOMED towards further convergence of clinical terminologies Proc AMIA Symp 1998 740 744 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 PMID 19448888 Rector A 2008 Barriers approaches and research priorities for integrating biomedical ontologies Semantic Health Deliverable 6 1 Trading Reviews und Tests Wir testen Broker PDF Archived from the original PDF on 2012 04 13 Retrieved 2012 04 13 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 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 Schulz S Spackman K James A Cocos C Boeker M May 2011 Scalable representations of diseases in biomedical ontologies PDF Journal of Biomedical Semantics 17 2 Suppl 2 S6 doi 10 1186 2041 1480 2 S2 S6 PMC 3102895 PMID 21624161 1 Schulz S Cornet R Spackman K Consolidating SNOMED CT s Applied ontology 2011 6 1 11 Kostick K 2012 SNOMED CT Integral Part of Quality HER Documentation Journal of AHIMA 83 10 October 2012 72 75 WHO International Classification of Diseases 11th Revision ICD 11 WHO Retrieved 5 August 2020 a b 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 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 MedDRA www meddra org Retrieved 2021 07 13 Blog SNOMED International Confluence SNOMED Confluence confluence ihtsdotools org The Global Patient Set snomed org Retrieved 5 August 2020 Observables Inception Elaboration document Observable and Investigation Model Project SNOMED Confluence Naming Patterns SNOMED International Retrieved 18 March 2021 Browser Retrieved 28 April 2021 External links EditSNOMED International website SNOMED International s online browsers for SNOMED CT US National Library of Medicine SNOMED CT resources NHS Digital SNOMED CT resources Veterinary Extension of SNOMED CT Retrieved from https en wikipedia org w index php title SNOMED CT amp oldid 1033478445, wikipedia, wiki, book,

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