SNOMED CT
Encyclopedia
SNOMED CT is a systematically organised computer processable collection of medical terminology
covering most areas of clinical information such as diseases, findings, procedures, microorganisms, substances, etc. It allows a consistent way to index, store, retrieve, and aggregate clinical data across specialties and sites of care. It also helps organising the content of medical records, reducing the variability in the way data is captured, encoded and used for clinical care of patients and research.
The primary purpose of SNOMED CT is to support the effective clinical recording of data with the aim of improving patient care. It is a structured collection of medical terms that are used internationally for recording clinical information and are coded in order to be computer processable. It covers areas such as diseases, symptoms, operations, treatments, devices and drugs. Its purpose is to consistently index, store, retrieve, and aggregate clinical data across specialties and sites of care. It helps organizing the content of electronic health records systems
, reducing the variability in the way data is captured, encoded and used for clinical care of patients and research. Specific language editions are available which augment the international Edition and can contain language translations as well as additional national terms.
SNOMED CT is considered by some to be the most comprehensive, multilingual clinical healthcare terminology in the world. It provides for consistent information interchange and is fundamental to an interoperable electronic health record. It can be used to record the clinical details of individuals in electronic patient records and support application functionality such as informed decision making, linkage to clinical care pathways and knowledge resources, shared care plans and as such 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.
In January 2002, SNOMED CT was created by the merger, expansion, and restructuring of the College of American Pathologists
(CAP) SNOMED RT (Reference Terminology) and the UK National Health Service
(NHS) Clinical Terms (also known as the Read codes
). The historical strength of the Systematized Nomenclature of Medicine
(SNOMED) was its coverage of medical specialties, while the strength of Clinical Terms Version 3 was its terminologies for general practice. SNOMED CT cross maps to such other terminologies as ICD-9-CM, ICD-O3, ICD-10
, Laboratory LOINC
and OPCS-4
. It supports ANSI
, DICOM, HL7, and ISO standards. SNOMED CT is currently used in a joint project with the WHO as the ontological basis of the upcoming ICD 11.
The National Library of Medicine (NLM), on behalf of the U.S. Department of Health and Human Services, entered into an agreement with College of American Pathologists for a perpetual license for the core SNOMED CT (in Spanish and English) and ongoing updates. The contract provides to NLM a perpetual license to distribute SNOMED within the NLM’s Unified Medical Language System UMLS Metathesaurus for no cost use within the U.S. by both U.S. government (federal, state, local, and territorial) and private organizations. The contract also covers updates to SNOMED CT issued by the College of American Pathologists between June 30, 2003 and June 29, 2008.
In April 2007, SNOMED CT was acquired by IHTSDO
, The International Health Terminology Standards Development Organisation.
SNOMED CT is currently available in American English, British English and Spanish, with other translations under way or nearly completed in French, Dutch, Danish, and Swedish, .
In 2011, SNOMED CT includes 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.
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.
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" (i.e. a patient where cold is recorded in their record as head cold, and in another as Acute coryza can both 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).
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 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.
formalism, restricting itself to the following operators:
413350009 | finding with explicit context | :
{ 246090004 | associated finding | = ( 284196006 | burn of skin | :
246112005 | severity | = 24484000 | severe |
, 363698007 | finding site | = 321472003 | structure of dermatoglyphic patterns of palm |)
, 408729009 | finding context | = 410515003 | known present |
, 408731000 | temporal context | = 410512000 | current or specified |
, 408732007 | subject relationship context | = 410604004 | subject of record |
}
Such expressions are said to have been 'post-coordinated'. When used, post coordinated conditions avoids the need to create large numbers of defined Concepts within SNOMED CT. However, most systems only allow for pre-coordinated conditions. Reliable analysis and comparison of any such post-coordinated expression - with respect to both those concepts already within the SNOMED CT release dataset and any other ad hoc concepts created or yet to be created by its community of end users - properly requires an appropriate machinery to efficiently process description logics expressions.
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.
Although browsers like CliniClue support the compositional syntax, there is almost no application in clinical practice, as it seems too complex for users and is not sufficiently supported by coding tools. DL-specific syntaxes, e.g. the Manchester Syntax, as developed by the Semantic Web community would be more intuitive, but it would still require to semantically clarifying SNOMED-CT specific syntax elements such as the Role Group.
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 principles 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 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.
, 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 the GNP). 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 web site .
Medical terminology
Medical terminology is a vocabulary for accurately describing the human body and associated components, conditions, processes and process in a science-based manner. Some examples are: R.I.C.E., trapezius, and latissimus dorsi. It is to be used in the medical and nursing fields...
covering most areas of clinical information such as diseases, findings, procedures, microorganisms, substances, etc. It allows a consistent way to index, store, retrieve, and aggregate clinical data across specialties and sites of care. It also helps organising the content of medical records, reducing the variability in the way data is captured, encoded and used for clinical care of patients and research.
The primary purpose of SNOMED CT is to support the effective clinical recording of data with the aim of improving patient care. It is a structured collection of medical terms that are used internationally for recording clinical information and are coded in order to be computer processable. It covers areas such as diseases, symptoms, operations, treatments, devices and drugs. Its purpose is to consistently index, store, retrieve, and aggregate clinical data across specialties and sites of care. It helps organizing the content of electronic health records systems
Electronic medical record
An electronic medical record is a computerized medical record created in an organization that delivers care, such as a hospital or physician's office...
, reducing the variability in the way data is captured, encoded and used for clinical care of patients and research. Specific language editions are available which augment the international Edition and can contain language translations as well as additional national terms.
SNOMED CT is considered by some to be the most comprehensive, multilingual clinical healthcare terminology in the world. It provides for consistent information interchange and is fundamental to an interoperable electronic health record. It can be used to record the clinical details of individuals in electronic patient records and support application functionality such as informed decision making, linkage to clinical care pathways and knowledge resources, shared care plans and as such 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.
History
Over four decades, SNOMED has developed from a pathology-specific nomenclature (SNOP) into a logic-based health care terminology.In January 2002, SNOMED CT was created by the merger, expansion, and restructuring of the College of American Pathologists
College of American Pathologists
The College of American Pathologists , is a medical society serving more than 17,000 physician members and the laboratory community throughout the world....
(CAP) SNOMED RT (Reference Terminology) and the UK National Health Service
National Health Service
The National Health Service is the shared name of three of the four publicly funded healthcare systems in the United Kingdom. They provide a comprehensive range of health services, the vast majority of which are free at the point of use to residents of the United Kingdom...
(NHS) Clinical Terms (also known as the Read codes
Read codes
Read codes are the standard clinical terminology system used in General Practice in the United Kingdom. It supports detailed clinical encoding of multiple patient phenomena including: occupation; social circumstances; ethnicity and religion; clinical signs, symptoms and observations; laboratory...
). The historical strength of the Systematized Nomenclature of Medicine
Systematized Nomenclature of Medicine
The Systematized Nomenclature of Medicine is a multiaxial, hierarchical classification system . As in any such system, a disease may be located in a body organ which results in a code in a topography axis and may lead to morphological alterations represented by a morphology code.-Purpose:SNOMED...
(SNOMED) was its coverage of medical specialties, while the strength of Clinical Terms Version 3 was its terminologies for general practice. SNOMED CT cross maps to such other terminologies as ICD-9-CM, ICD-O3, ICD-10
ICD-10
The International Statistical Classification of Diseases and Related Health Problems, 10th Revision is a medical classification list for the coding of diseases, signs and symptoms, abnormal findings, complaints, social circumstances, and external causes of injury or diseases, as maintained by the...
, Laboratory LOINC
LOINC
Logical Observation Identifiers Names and Codes is a database and universal standard for identifying medical laboratory observations. It was developed and is maintained by the Regenstrief Institute, a US non-profit medical research organization, in 1994...
and OPCS-4
Office of Population Censuses and Surveys
The Office of Population Censuses and Surveys , was created in May 1970 through the merger of the General Register Office and the Government Social Survey Department....
. It supports ANSI
Ansi
Ansi is a village in Kaarma Parish, Saare County, on the island of Saaremaa, Estonia....
, DICOM, HL7, and ISO standards. SNOMED CT is currently used in a joint project with the WHO as the ontological basis of the upcoming ICD 11.
The National Library of Medicine (NLM), on behalf of the U.S. Department of Health and Human Services, entered into an agreement with College of American Pathologists for a perpetual license for the core SNOMED CT (in Spanish and English) and ongoing updates. The contract provides to NLM a perpetual license to distribute SNOMED within the NLM’s Unified Medical Language System UMLS Metathesaurus for no cost use within the U.S. by both U.S. government (federal, state, local, and territorial) and private organizations. The contract also covers updates to SNOMED CT issued by the College of American Pathologists between June 30, 2003 and June 29, 2008.
In April 2007, SNOMED CT was acquired by IHTSDO
IHTSDO
-Introduction:The International Health Terminology Standards Development Organisation is an international non-profit standards development organization...
, The International Health Terminology Standards Development Organisation.
SNOMED CT is currently available in American English, British English and Spanish, with other translations under way or nearly completed in French, Dutch, Danish, and Swedish, .
Structure
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 includes 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.
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" (i.e. a patient where cold is recorded in their record as head cold, and in another as Acute coryza can both 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).
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 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++EL++
EL++ is a lightweight description logic that was designed to*capture the expressive power that is used by large-scale ontologies from practical applications*have polytime reasoning problems, in particular classification and instance checking...
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)
- The logic will be extended in the near future to include General Concept Inclusion Axioms.
Pre- and postcoordination
SNOMED CT provides a compositional syntax for building new concepts. For example, there might not be an explicit concept for a burn in the palm of the hand. Using the compositional syntax it could be described as413350009 | finding with explicit context | :
{ 246090004 | associated finding | = ( 284196006 | burn of skin | :
246112005 | severity | = 24484000 | severe |
, 363698007 | finding site | = 321472003 | structure of dermatoglyphic patterns of palm |)
, 408729009 | finding context | = 410515003 | known present |
, 408731000 | temporal context | = 410512000 | current or specified |
, 408732007 | subject relationship context | = 410604004 | subject of record |
}
Such expressions are said to have been 'post-coordinated'. When used, post coordinated conditions avoids the need to create large numbers of defined Concepts within SNOMED CT. However, most systems only allow for pre-coordinated conditions. Reliable analysis and comparison of any such post-coordinated expression - with respect to both those concepts already within the SNOMED CT release dataset and any other ad hoc concepts created or yet to be created by its community of end users - properly requires an appropriate machinery to efficiently process description logics expressions.
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 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.
Although browsers like CliniClue support the compositional syntax, there is almost no application in clinical practice, as it seems too complex for users and is not sufficiently supported by coding tools. DL-specific syntaxes, e.g. the Manchester Syntax, as developed by the Semantic Web community would be more intuitive, but it would still require to semantically clarifying SNOMED-CT specific syntax elements such as the Role Group.
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
IHTSDO
-Introduction:The International Health Terminology Standards Development Organisation is an international non-profit standards development organization...
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 principles 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 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.
Use
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 systemClinical decision support systemClinical decision support system is an interactive decision support system Computer Software, which is designed to assist physicians and other health professionals with decision making tasks, as determining diagnosis of patient data. A working definition has been proposed by Dr...
s (CDSS) - Remote Intensive Care Unit Monitoring
- Laboratory Reporting
- Emergency Room Charting
- Cancer Reporting
- Genetic Databases
Access
SNOMED CT is maintained and distributed by the IHTSDOIHTSDO
-Introduction:The International Health Terminology Standards Development Organisation is an international non-profit standards development organization...
, 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 the GNP). 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
Unified Medical Language System
The Unified Medical Language System is a compendium of many controlled vocabularies in the biomedical sciences . It provides a mapping structure among these vocabularies and thus allows one to translate among the various terminology systems; it may also be viewed as a comprehensive thesaurus and...
(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 web site .
See also
- Clinical Care Classification SystemClinical Care Classification SystemClinical Care Classification SystemThe Clinical Care Classification System is a standardized, coded nursing terminology that identifies the discrete elements of nursing practice...
- IHTSDO - International Health Terminology Standards Development OrganizationIHTSDO-Introduction:The International Health Terminology Standards Development Organisation is an international non-profit standards development organization...
- HL7
- EN 13606EN 13606The overall goal of this Health informatics - Electronic Health Record Communication European Standard is to define a rigorous and stable information architecture for communicating part or all of the Electronic Health Record of a single subject of care...
- MEDCINMEDCINMEDCIN, a system of standardized medical terminology, is a proprietary medical vocabulary and was developed by MEDCIN is a point-of-care terminology, intended for use in Electronic Health Record systems....
- CDISCClinical Data Interchange Standards ConsortiumClinical Data Interchange Standards Consortium is a non-profit organization, whose mission is "to develop and support global, platform-independent data standards that enable information system interoperability to improve medical research and related areas of health-care". Their main project, the...
- DOCLEDOCLEDOCLE , is a non-numeric health coding and medical classification system. The Docle system is used in Health Communication Network's electronic medical record and patient management software package, Medical Director...
- SNOMED
- Omaha SystemOmaha SystemThe Omaha System is a standardized health care terminology consisting of an assessment component , an intervention component , and an outcomes component...
External links
- IHTSDO Web Site - Home of the owners of SNOMED
- CAP SNOMED Terminology Solutions - the original creators of SNOMED CT
- Online SNOMED CT Browser English and German
- CliniClue SNOMED CT Browser (Windows) - freeware download
- UMLS-SNOMED FAQs
- NHS Connecting for Health UK
- SNOB - Desktop SNOMED Browser (Windows/WINE) - freeware download
- SNOMED CT Browser with SNOFLAKE view at dataline.co.uk
- VMIL terminology browser
- SNOCat: the SNOMED Categorizer/Browser
- Minnow SNOMED CT Browser (Windows/Mac OS X/Linux) - freeware download
- Problems with SNOMED (Papers by Barry Smith)
- Snow Owl - Freeware multiplatform SNOMED CT browser and authoring tool integrating Protégé.
- “What Is SNOMED Clinical Terms"
- Health Data Management, February 14, 2002: “New Clinical Terminology Available from SNOMED,”