Jane Hunter Hafsa Qureshi Jane Hunter M Sc

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Jane Hunter Hafsa Qureshi

Jane Hunter Hafsa Qureshi

� Jane Hunter �M. Sc. e. Health candidate (part-time) �Undergrad in Computer Engineering at

� Jane Hunter �M. Sc. e. Health candidate (part-time) �Undergrad in Computer Engineering at Mc. Master �Have also done an MBA at Mc. Master �Working as a software developer at NCR where we are currently creating a Java development infrastructure for next generation banking products �Married for 10 years as of June, no kids

� Hafsa Qureshi �M. Sc. e. Health candidate (full-time, thesis student) �B. Sc. Health

� Hafsa Qureshi �M. Sc. e. Health candidate (full-time, thesis student) �B. Sc. Health Informatics from University of Waterloo �Trying to look for internship employment �Recently married

Introduce SNOMED CT Show some of the uses of SNOMED Discuss some disadvantages of

Introduce SNOMED CT Show some of the uses of SNOMED Discuss some disadvantages of SNOMED

Vocabularies What is SNOMED CT? Examples Database Tables Implementing an Application with SNOMED Questions

Vocabularies What is SNOMED CT? Examples Database Tables Implementing an Application with SNOMED Questions

SNOMED CT • Systematized Nomenclature of Medicine Clinical Terms Me. SH • Medical Subject

SNOMED CT • Systematized Nomenclature of Medicine Clinical Terms Me. SH • Medical Subject Headings UMLS • Unified Medical Language System LOINC ICD-10 -CA - • Logical Observation Identifiers Names and Codes • Enhanced Canadian version of the 10 th revision of the International Statistical Classification of Diseases and Related Health Problems

HTTP: //LIBRARY. AHIMA. ORG/XPEDIO/GROUPS/PUBLIC/DOCUMENTS/AHIMA/BOK 1_033474. HCSP? DDOCNAME=BOK 1_0334 74

HTTP: //LIBRARY. AHIMA. ORG/XPEDIO/GROUPS/PUBLIC/DOCUMENTS/AHIMA/BOK 1_033474. HCSP? DDOCNAME=BOK 1_0334 74

� Systematized Nomenclature of Medicine Clinical Terms � controlled medical vocabulary licensed and supported

� Systematized Nomenclature of Medicine Clinical Terms � controlled medical vocabulary licensed and supported by the International Health Terminology SDO � provides a common language that enables a consistent way of indexing, storing, retrieving and aggregating clinical data across specialties and sites of care � comprehensive, multi-lingual clinical terminology that provides clinical content and expressivity for clinical documentation and reporting

� Medical Subject Headings � Comprehensive controlled vocabulary for the purpose of indexing journal

� Medical Subject Headings � Comprehensive controlled vocabulary for the purpose of indexing journal articles and books in the life sciences � Created and updated by the United States National Library of Medicine (NLM) � serves as a thesaurus that facilitates searching � used by the MEDLINE/Pub. Med article database and by NLM's catalog of book holdings

� Unified Medical Language System � compendium of many controlled vocabularies in the biomedical

� Unified Medical Language System � compendium of many controlled vocabularies in the biomedical sciences � provides a mapping structure among these vocabularies and allows one to translate among the various terminology systems � Comprehensive thesaurus and ontology of biomedical concepts � provides facilities for natural language processing � intended to be used mainly by developers of systems in medical informatics

� Logical Observation Identifiers Names and Codes � universal standard for identifying medical laboratory

� Logical Observation Identifiers Names and Codes � universal standard for identifying medical laboratory observations � developed and is maintained by the Regenstrief Institute, a US non-profit medical research organization � publicly available at no cost. � include medical and laboratory code names, nursing diagnosis, nursing interventions, outcomes classification, and patient care data set.

� International Statistical Classification of Diseases and Related Health Problems � provides codes to

� International Statistical Classification of Diseases and Related Health Problems � provides codes to classify diseases and a wide variety of signs, symptoms, abnormal findings, complaints, social circumstances, and external causes of injury or disease � every health condition can be assigned to a unique category and given a code, up to six characters long

� Why are there so many vocabularies?

� Why are there so many vocabularies?

Methods: assembled 1929 source concept records from a variety of clinical information records were

Methods: assembled 1929 source concept records from a variety of clinical information records were coded in each scheme by an investigator and checked by the coding scheme owner. codings were then scored by an independent panel of clinicians for acceptability

� Conclusion: � No major terminology source can lay claim to being the ideal

� Conclusion: � No major terminology source can lay claim to being the ideal resource for a computer-based patient record. � SNOMED is considerably more complete, has a compositional nature and a richer taxonomy. It suffers from less clarity, resulting from a lack of syntax and evolutionary changes in its coding scheme. � READ has greater clarity and better mapping to administrative schemes, is rapidly changing and is less complete. � UMLS is a rich lexical resource, with mappings to many source vocabularies. It provides definitions for many of its terms. However, due to the varying granularities and purposes of its source schemes, it has limitations for representation of clinical concepts within a computerbased patient record.

HTTP: //WWW. IHTSDO. ORG/SNOMED-CT/ � SNOMED CT is �a clinical healthcare terminology �a resource

HTTP: //WWW. IHTSDO. ORG/SNOMED-CT/ � SNOMED CT is �a clinical healthcare terminology �a resource with comprehensive, scientificallyvalidated content �essential for electronic health records �a terminology that can cross-map to other international standards �already used in more than fifty countries

HTTP: //WWW. IHTSDO. ORG/SNOMED-CT/ � Each year, avoidable deaths and injuries occur because of

HTTP: //WWW. IHTSDO. ORG/SNOMED-CT/ � Each year, avoidable deaths and injuries occur because of poor communication between healthcare practitioners. � The delivery of a standard clinical language for use across the world's health information systems can therefore be a significant step towards improving the quality and safety of healthcare. � SNOMED CT aims to improve patient care through the development of systems to accurately record health care encounters. � Ultimately, patients will benefit from the use of SNOMED CT, for building and facilitating communication and interoperability in electronic health data exchange.

Consists of • For example over a million 22298006 means myocardial medical infarction (MI).

Consists of • For example over a million 22298006 means myocardial medical infarction (MI). Concepts The Concepts are arranged in a type or IS -A hierarchy • For example, Viral pneumonia IS-A Infectious pneumonia IS-A Pneumonia IS-A Lung disease.

HTTP: //WWW. IHTSDO. ORG/SNOMED-CT/ � concepts are organized in hierarchies, from the general to

HTTP: //WWW. IHTSDO. ORG/SNOMED-CT/ � concepts are organized in hierarchies, from the general to the specific � allows very detailed (“granular”) clinical data to be recorded and later accessed or aggregated at a more general level

� Concepts may have multiple parents, for example Infectious pneumonia is also an Infectious

� Concepts may have multiple parents, for example Infectious pneumonia is also an Infectious disease. � The Concept graph must be acyclic — a parent cannot be its own child.

HTTP: //WWW. IHTSDO. ORG/SNOMED-CT/ � From abscess to zygote, SNOMED CT includes more than

HTTP: //WWW. IHTSDO. ORG/SNOMED-CT/ � From abscess to zygote, SNOMED CT includes more than 311, 000 unique concepts. � There almost 800, 000 descriptions in SNOMED CT, including synonyms that can be used to refer to a concept.

�a “concept” is a clinical meaning identified by a unique numeric identifier (Concept. ID)

�a “concept” is a clinical meaning identified by a unique numeric identifier (Concept. ID) that never changes. � formally defined in terms of their relationships with other concepts. � give explicit meaning which a computer can process and query on. � Every concept also has a set of terms that name the concept in a human-readable way. � Concept. IDs do not contain hierarchical or implicit meaning. � The numeric identifier does not reveal any information about the nature of the concept.

� Concept descriptions are the terms or names assigned to a SNOMED CT concept

� Concept descriptions are the terms or names assigned to a SNOMED CT concept � “Term” in this context means a phrase used to name a concept � A unique Description. ID identifies a description � Multiple descriptions might be associated with a concept identified by its Concept. ID

� Some of the descriptions associated with Concept. ID 22298006: �Fully Specified Name: Myocardial

� Some of the descriptions associated with Concept. ID 22298006: �Fully Specified Name: Myocardial infarction (disorder) Description. ID 751689013 �Preferred term: Myocardial infarction Description. ID 37436014 �Synonym: Cardiac infarction Description. ID 37442013 �Synonym: Heart attack Description. ID 37443015 �Synonym: Infarction of heart Description. ID 37441018 � Each of the above descriptions has a unique Description. ID

� Concepts are represented by a unique humanreadable Fully Specified Name (FSN). � Each

� Concepts are represented by a unique humanreadable Fully Specified Name (FSN). � Each concept has one unique FSN intended to provide an unambiguous way to name a concept. � not necessarily the most commonly used for that concept � Each FSN ends with a “semantic tag” in parentheses at the end of the concept to indicate the semantic category to which the concept belongs � For example, � Hematoma (morphologic abnormality) is a FSN that represents the description of what the pathologist sees at the tissue level � Hematoma (disorder) is a FSN which indicates the concept that would be used to code the clinical diagnosis of a hematoma by a general practitioner.

� � Each concept has one Preferred Term meant to capture the common word

� � Each concept has one Preferred Term meant to capture the common word or phrase used by clinicians to name that concept. For example, � the concept 54987000 Repair of common bile duct (procedure) has the Preferred term “Choledochoplasty” to represent a common name clinicians use to describe the procedure. � � � Unlike FSNs, Preferred Terms are not necessarily unique Occasionally, the Preferred Term for one concept may also be a Synonym or the Preferred Term for a different concept. For example � Cold sensation quality (qualifier value) has a preferred term of “Cold. ” � Common cold (disorder) also has a synonym of “Cold. ” � In both cases, “cold” represents a common clinical phrase used to capture the meaning of the FSN.

� Synonyms represent any additional terms that represent the same concept as the FSN.

� Synonyms represent any additional terms that represent the same concept as the FSN. � are not required to be unique across concepts. � Example: � Some of the Synonyms associated with Concept. ID 22298006 which has the Fully Specified Name: Myocardial infarction (disorder) are: �Synonym: Cardiac infarction Description. ID: 37442013 �Synonym: Heart attack Description. ID: 37443015 �Synonym: Infarction of heart Description. ID: 37441018

HTTP: //WWW. IHTSDO. ORG/SNOMED-CT/ there about 1, 360, 000 links or al m for

HTTP: //WWW. IHTSDO. ORG/SNOMED-CT/ there about 1, 360, 000 links or al m for r e id the cept v ro d o con p ps s an the i h n s on nitio cs of i t i a i rel def erist ct a r a ch s be eman tw ee tic r n t ela co he S tion nc NO shi ep ME ps ts DC T

� four types of relationships � Defining characteristics are IS_A relationships and defining attributes.

� four types of relationships � Defining characteristics are IS_A relationships and defining attributes. � Qualifying characteristics are non-defining, qualifying attributes. constrains the possible values an implementer can select in assigning a qualifying characteristic to a concept � Historical concepts. relationships relate inactive concepts to active For example, a concept may be inactivated because it is a duplicate. A “same-as” relationship would be created between the 2 concepts. � Additional relationships are other non-defining characteristics For example, PART OF which is retained for backward compatibility with SNOMED RT.

Each concept in SNOMED CT is logically defined through its relationships to other concepts.

Each concept in SNOMED CT is logically defined through its relationships to other concepts. Every active SNOMED CT concept (except the “SNOMED CT Concept” Root concept) has at least one IS_A relationship to a supertype concept. establish IS_A relationships with one or more defining concepts (called supertypes) and modeling the difference with those supertypes through defining attributes.

� “Supertype-Subtype relationships” or “Parent- Child relationships. ” � IS_A relationships are the basis

� “Supertype-Subtype relationships” or “Parent- Child relationships. ” � IS_A relationships are the basis of the SNOMED CT’s hierarchies.

� Attributes relate two concepts and establish the type of relationship between them. �

� Attributes relate two concepts and establish the type of relationship between them. � Example: � Lumbar discitis (disorder) (a concept in the Clinical finding hierarchy) is related to concepts in the Body structure hierarchy through two attributes: FINDING SITE and ASSOCIATED MORPHOLOGY. Lumbar discitis (disorder) FINDING SITE Structure of lumbar intervertebral disc (body structure) ASSOCIATED MORPHOLOGY Inflammation (morphologic abnormality) � The two attributes FINDING SITE and ASSOCIATED MORPHOLOGY and their assigned values provide definition for the concept Lumbar discitis (disorder).

� Example: � the concept Pneumonia (disorder) is characterized with the attribute FINDING SITE.

� Example: � the concept Pneumonia (disorder) is characterized with the attribute FINDING SITE. Since pneumonia is a disorder of the lung, FINDING SITE has the value Lung structure (body structure). Pneumonia (disorder) FINDING SITE Lung structure (body structure)

HTTP: //WWW. IHTSDO. ORG/SNOMED-CT/ Clinical finding/disorder Procedure/intervention Observable entity Body structurez Organism Substance Pharmaceutical/biologic

HTTP: //WWW. IHTSDO. ORG/SNOMED-CT/ Clinical finding/disorder Procedure/intervention Observable entity Body structurez Organism Substance Pharmaceutical/biologic product Specimen Special Concept Physical Object Physical force Event Environment or geographical location Social context Staging and Scales

HTTP: //WWW. IHTSDO. ORG/SNOMED-CT/ � Concepts in this hierarchy represent the result of a

HTTP: //WWW. IHTSDO. ORG/SNOMED-CT/ � Concepts in this hierarchy represent the result of a clinical observation, assessment or judgment, and include both normal and abnormal clinical states � contains the sub-hierarchy of Disease. � Examples of Clinical finding concepts: � Clear sputum (finding) � Normal breath sounds (finding) � Poor posture (finding) � Examples of Disease concepts: � Tuberculosis (disorder) � Non-Hodgkin's lymphoma (disorder)

HTTP: //WWW. IHTSDO. ORG/SNOMED-CT/ � The Event hierarchy includes concepts that represent occurrences (excluding

HTTP: //WWW. IHTSDO. ORG/SNOMED-CT/ � The Event hierarchy includes concepts that represent occurrences (excluding procedures and interventions) � Examples �Flood of Event concepts: (event) �Bioterrorisk attach (event) �Earthquake (event)

HTTP: //WWW. IHTSDO. ORG/SNOMED-CT/ �This hierarchy contains such subhierarchies as Assessment scales and Tumor

HTTP: //WWW. IHTSDO. ORG/SNOMED-CT/ �This hierarchy contains such subhierarchies as Assessment scales and Tumor staging �Examples of Assessment scales concepts: �Glasgow coma scale (assessment scale) �Stanford Binet intelligence scale (assessment scale) �Examples of Tumor staging concepts: �International Federation of Gynecology and Obstetrics (FIGO) staging �Dukes staging system (tumor staging)

HTTP: //WWW. IHTSDO. ORG/SNOMED-CT/ �provides explicit links (cross maps) to health-related classifications and coding

HTTP: //WWW. IHTSDO. ORG/SNOMED-CT/ �provides explicit links (cross maps) to health-related classifications and coding schemes in use around the world �e. g. diagnosis classifications such as ICD-9 -CM, ICD-O 3, and ICD-10, as well as the OPCS-4 classification of interventions. �Additional cross-maps are also under development or consideration �Cross-maps facilitate reuse of SNOMED CT -encoded data for other purposes, such as reimbursement or statistical reporting

HTTP: //WWW. IHTSDO. ORG/SNOMED-CT/ � SNOMED CT is a multinational, multilingual terminology � has

HTTP: //WWW. IHTSDO. ORG/SNOMED-CT/ � SNOMED CT is a multinational, multilingual terminology � has a built-in framework to manage different languages and dialects � The International Release includes a set of language-independent concepts and relationships � available in US English, UK English, Spanish and Danish � Currently translations into French, Swedish, Lithuanian, and several other languages � planning to translate the standard into other languages

HTTP: //LIBRARY. AHIMA. ORG/XPEDIO/GROUPS/PUBLIC/DOCUMENTS/AHIMA/BOK 1_033474. HCSP? DDOCNAME=BOK 1_0334 74 � This 85 year (258707000

HTTP: //LIBRARY. AHIMA. ORG/XPEDIO/GROUPS/PUBLIC/DOCUMENTS/AHIMA/BOK 1_033474. HCSP? DDOCNAME=BOK 1_0334 74 � This 85 year (258707000 year) old (70753007 old) (397659008 age) female (248152002 female) was admitted via the emergency room (50849002 emergency room admission) from the nursing home (42665001 nursing home) with shortness of breath (267036007 dyspnea), confusion (225440008 onset of confusion), and congestion (418092006 respiratory tract congestion). There was no history of (14732006 no history of) fever (386661006 fever) or cough (49727002 cough) noted. Patient also has a history of (392521001 history of) senile dementia (15662003 senile dementia) and COPD (13645005 chronic obstructive lung disease). � Prior to (288556008 before) admission (129273005 admission – action), the patient was taking the following medications: � Prednisone (116602009 prednisone), Lasix (81609008 furosemide), Haldol (349874003 oral haloperidol), and Colace (418528006 docusate). Patient has also been taking Lorazepam 0. 5 -mg tablet (349865000 oral form lorazepam) 2 x a day (229799001 twice a day) as needed for anxiety (48694002 anxiety). Patient is also noted to have a vitamin C deficiency (76169001 ascorbic acid deficiency).

HTTP: //EAGL. UNIGE. CH/SNOCAT

HTTP: //EAGL. UNIGE. CH/SNOCAT

HTTP: //EAGL. UNIGE. CH/SNOCAT

HTTP: //EAGL. UNIGE. CH/SNOCAT

HTTP: //EAGL. UNIGE. CH/SNOCAT

HTTP: //EAGL. UNIGE. CH/SNOCAT

� Is SNOMED too complicated?

� Is SNOMED too complicated?

SNOMED CT is distributed as a set of tab-delimited text files that can be

SNOMED CT is distributed as a set of tab-delimited text files that can be imported into a relational database. the Concepts table, the Descriptions table, and the Relationships table, are commonly referred to as the “core” tables. The association of a set of Descriptions and a set of Relationships to each Concept is implemented using the Concept. ID which is the primary or foreign key in the three tables

 The Concepts Table contains all the concepts in SNOMED CT Concept ID •

The Concepts Table contains all the concepts in SNOMED CT Concept ID • Primary Key Fully Specified Name • Foreign key to description table; serves to provide a human readable name for each concept Concept Status • Indicates whether a concept is in active use or retired

 This table relates the various terms used to name a single SNOMED CT

This table relates the various terms used to name a single SNOMED CT concept. Descritption ID • Primary key Description Type • Fully specified name (Indicates type • Preferred Term of description) • Synonym Language Code • Associates each description with a particular language or dialect

 This table contains the relationships between SNOMED CT concepts. Relationship • Primary Key

This table contains the relationships between SNOMED CT concepts. Relationship • Primary Key ID Relationship • Type of relationship Type • First concept in the Concept ID 1 relationship • “target” concept in the Concept ID 2 relationship

� The content of SNOMED CT evolves with each release. � Drivers of these

� The content of SNOMED CT evolves with each release. � Drivers of these changes include changes in understanding of health and disease processes; introduction of new drugs, investigations, therapies and procedures; and new threats to health, as well as proposals and work provided by SNOMED partners and licensees. � Changes designated as minor require only a history record to record the change. � The history mechanism involves the following tables: � Component History Table History References Table

�A Subset refers to a set of Concepts, Descriptions, or Relationships that are appropriate

�A Subset refers to a set of Concepts, Descriptions, or Relationships that are appropriate to a particular language, dialect, country, specialty, organization, user or context. � The Subset Mechanism may be used to derive tables that contain only part of SNOMED CT � Subsets are not necessarily mutually exclusive � Subset mechanism involves the following tables: �Subsets Table �Subset Members Table

�Cross Mappings enable SNOMED CT to effectively reference other terminologies and classifications. � Each

�Cross Mappings enable SNOMED CT to effectively reference other terminologies and classifications. � Each cross map matches SNOMED concepts with another coding scheme that is called the “target scheme. ” �Cross Mapping mechanism involves the following tables: �Cross Map Sets Table Map Targets Table

HTTP: //WWW. IHTSDO. ORG/PUBLICATIONS/IMPLEMENTING-SNOMED-CT/ �The International Health Terminology Standards Development Organization provides technical documentation

HTTP: //WWW. IHTSDO. ORG/PUBLICATIONS/IMPLEMENTING-SNOMED-CT/ �The International Health Terminology Standards Development Organization provides technical documentation for developing SNOMED compliant applications �Technical Reference Guide – 166 pages �Technical Implementation Guide – 211 pages �Includes an appendix for working with HL 7 (version 3)

� All Version 3 products derive their semantic content from the RIM. � Intermediary

� All Version 3 products derive their semantic content from the RIM. � Intermediary models are used to constrain the RIM for use in a particular specification. � Domain Message Information Model (D-MIM), which constrains the portion of the RIM used by a committee in the derivation of all their messages. � Refined Information Model (R-MIM), and a Hierarchical Message Definition (HMD) specify a set of Message Types. � there will be several D-MIMs derived from the RIM; there will be several R-MIMs derived from each D-MIM; and there will be several HMDs derived from each R-MIM. � SNOMED CT will typically apply these constructs to these intermediary models, rather than to RIM itself.

� The RIM includes a new set of data types developed for use within

� The RIM includes a new set of data types developed for use within the HL 7 Version 3 family of standards. � Data types that can carry Concept. IDs include: �Coded with Equivalents (CE), which carries a code, the name of the coding scheme the code is drawn from, and a display name corresponding to the code; and allows synonyms to be transmitted – such as an HL 7 code and its equivalent SNOMED code; �Concept Descriptor (CD), which builds on the CE by supporting the post-coordination of codes (or, stated in another way, the combining of codes from a terminology to create a new concept).

� RIM attributes of type CE or CD can also have a specified vocabulary

� RIM attributes of type CE or CD can also have a specified vocabulary domain. � These domains can include HL 7 -defined concepts or can be drawn from HL 7 -recognized coding systems such as LOINC or SNOMED CT. � Vocabulary domains have a coding strength that can be � “Coded, No Extensions” (CNE), in which case the only allowable values for the field are those in the vocabulary domain; � “Coded, With Extensions” (CWE), in which case values other than those in the vocabulary domain (such as local codes) can be used if necessary.

� The vocabulary domain specifications stated in the RIM always refer to a complete

� The vocabulary domain specifications stated in the RIM always refer to a complete vocabulary domain. � at the RIM level there is no specialization based on realm of use or on the context and needs of a specific message. � As RIM attributes are specialized to suit a specific message context, the domain of the attribute can be reduced (constrained) to reflect the specialization. � A vocabulary domain that has been constrained to a particular realm and coding scheme (such as SNOMED CT) is called a “value set. ”

� Retrieve �A an HL 7 V 3 message receiver of one or more

� Retrieve �A an HL 7 V 3 message receiver of one or more HL 7 messages will need to be able to extract the coded information in the message and aggregate it with concepts sent in other messages or with concepts stored in a data repository. �The entire discussion of aggregation in this section assumes that valid and conformant HL 7 messages are received.

�Syntactic �Convert transformation the concepts in the message into a “canonical form” (using a

�Syntactic �Convert transformation the concepts in the message into a “canonical form” (using a derived equivalence between HL 7 RIM attributes and SNOMED CT relationship types). �The use of guidelines and templates can constrain the inherent flexibility of an HL 7 message, and can decrease the number of substeps required to perform a canonical transformation. Tightly coupled systems can take this into account, and establish bilateral agreements that will minimize message variability.

� Aggregation �Aggregate the various representations, all expressed in a common canonical form. �Use

� Aggregation �Aggregate the various representations, all expressed in a common canonical form. �Use techniques that query for the primary code AND the semantic properties of the concepts of interest.

� What are the implications to system designers when they try and hide the

� What are the implications to system designers when they try and hide the use of SNOMED from the end user?

� � � � http: //www 2. infowayinforoute. ca/Documents/R 2_ENGLISH%20 SC%20 Guide%20 and%20 S

� � � � http: //www 2. infowayinforoute. ca/Documents/R 2_ENGLISH%20 SC%20 Guide%20 and%20 S tandards%20 Catalogue. pdf http: //en. wikipedia. org (Medical_Subject_Headings, International_Statistical_Classification_of_Diseases_and_Related_ Health_Problems, Unified_Medical_Language_System, LOINC, SNOMED_CT) http: //www. ihtsdo. org/snomed-ct http: //eagl. unige. ch/SNOCat Campbell JR, Carpenter P, Sneiderman C, Cohn S. Chute CG, Warren J. Phase II Evaluation of Clinical Coding Schemes: Completeness, Taxonomy, Mapping, Definitions, and Clarity. Journal of the American Medical Informatics Association. 1997; 4: 238 -51. http: //www. pubmedcentral. nih. gov/picrender. fcgi? artid=61239& blobtype=pdf SNOMED Clinical Terms User Guide