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Managing SNOMED

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Title: Managing SNOMED


1
Managing SNOMED
  • NAHLN
  • January 2004
  • Las Vegas

2
Nomenclature Tasks
  • Do I know how you should do this?
  • NO!!!!!!

3
Nomenclature Tasks
  • Install nomenclature
  • Interface to terminology
  • Subsetting to enhance efficiency
  • Mapping from existing controlled vocabulary
  • Displaying preferred descriptions
  • System wide
  • User specific??????
  • Message processing
  • Requests from users for concept addition
  • Updates (ongoing)
  • Queries

4
Interface options (Ferrari)
  • Data entry concept requests
  • Queries of LIMS data
  • Natural language interface?
  • Description logic approach

High Powered Terminology Server
Lims Server CIS Server Etc.
  • Advantages
  • Offload nomenclature from production system CPU /
    data storage
  • Single update with new release of nomenclature
  • Access to all at all times
  • Minimal SNOMED pre-processing
  • Disadvantages
  • Expense
  • Server
  • Terminology software
  • SNOMED functionality inadequate at this time.
  • Probably requires full time nomenclaturologist ?

5
Interface options (Chevy)
  • Store subsets (pick lists) in LIMS System
  • Query server
  • a complete copy of SNOMED
  • Your SNOMED workshop

Lims Server
Low End Terminology Server (Full copy of SNOMED)
  • Advantages
  • Terminology operations
  • Disadvantages
  • Several many subsets
  • Subset updates as second step with new release
    (problematic if manual)
  • Somebody must build subsets

6
SNOMED Subset
  • a set of Concepts, Descriptions, or
    Relationships that are appropriate to a
    particular language, dialect, country, specialty,
    organization, user or context.
  • simplest form, the Subset Mechanism is a list
    of SNOMED identifiers (SCTIDs).
  • Mechanism may be used to derive tables that
    contain only part of SNOMED CT.

7
Functional Sub-setting
  • We only need PORTIONS of SNOMED
  • DIFFERENT portions of SNOMED for various parts of
    LIMS.
  • Retain the ability to use ALL of SNOMED to
    search, retrieve, analyze data produced using
    sub-sets.
  • Be prepared to transfer (copy) from SNOMED to
    subset as needs change.

8
Existing Subset(s)
  • Non-human subset
  • This subset assists applications that desire to
    exclude concepts which are not human medical
    concepts (i.e., paw and fin).
  • Note that this is NOT a veterinary subset as that
    subset would include terms shared with humans
    such as brain and eye.
  • Pathology subsets (3)
  • CAP Cancer checklists
  • Allergen subsets

9
NAHLN Subsets?
  • SNOMED (-) hierarchies that are NOT of interest.
  • Someone has to decide whats not of interest
  • Someone familiar with SNOMED should build the
    subsets
  • Desired functionality -gt Subset the
    relationships?
  • It would be nice to have a Non-human-only subset
  • Organisms
  • Species
  • Breeds
  • Bacteria, viruses, parasites, etc.
  • Diseases of interest
  • Some portion of laboratory tests (classification
    scheme for LOINC?)
  • Reportable diseases (depending on jurisdiction)

10
Subsets
Veterinary Subset (large) SNOMED (human only) 100 k - 200k concepts
Bacteria Living organism automated subset 6500 concepts
Abnormal Morphologies Body structure automated subset 4000 concepts
Respiratory Findings Findings/disorders automated subset 850
Severities Automated from qualifiers 5
11
Veterinary SubsetsShared resource
  • We need to develop a root veterinary subset
  • Manual process (cant be automated at this time).
  • Prune SNOMED to remove human ONLY content.
  • Prune SNOMED aggressively to remove excessive
    granularity.
  • Automated subsetting works on ALL SNOMED or the
    Veterinary subset.

12
Subsets
All of SNOMED
Cardiovascular disease subset Algorithm
Vet Subset
Cardiovascular Diseases
Intersection Veterinary Cardiovascular Diseases
13
Subset development (Ideal)
  • Build a complete Veterinary Subset of SNOMED
  • Veterinary subset a resource shared by the
    profession.
  • Managed by central authority
  • Distributed by SNOMED?
  • Use algorithm approaches to create microsubsets

14
NAHLN Extension(s)?
  • Conditions of husbandry
  • Probably should be core
  • Descriptions (more synonyms)
  • Local
  • Network-wide

15
Recursion for gathering all descendants of a
concept.
  • Build subsets
  • breeds, species
  • all disorders
  • all cardiovascular disorders
  • etc.
  • Query for concept and all its specializations
  • everything that ISA respiratory disease.

16
List a SNOMED definition
ISA relationships always defining 116680003
ISA
Group by RelationshipsGroup CharacteristicType 0
is defining
17
Why map?
  • SNOMED is not optimized for data entry.
  • Your own local vocabulary may be the preferred
    data entry instrument.
  • Capture data via local term (description string)
  • Convert to SNOMED concept
  • Transmit to repository

18
SNOMED Maps
  • SNOMED provides a number of maps to nomenclatures
    of human interest
  • ICD-9
  • ICD-10
  • ICD-0
  • LOINC (special case we MIGHT use)
  • SNOMED is source

19
Mapping
  • Mapping is directional
  • Largely the result of differing granularity
    between target and source
  • 11 Concept is the same
  • Term may be identical or synonym remember to
    distinguish on CONCEPT not on string
  • Narrow to Broad Source concept is more specific
    than target
  • Broad to Narrow Source concept is more general
    than target
  • Two maps may be needed for bi-directional
    functionality (unless entire map is 11)

20
Mapping for NAHLN
  • NAHLN Maps (e.g., CAHFS) will use local
    nomenclature as source, SNOMED as target
  • Map builder qualifications
  • Understand structure of source and target
  • Understand content of source and target
  • IF the map is completely 11, the single map is
    bidirectional.

21
Mapping for NAHLN
  • 11 maps will represent a majority
  • Broad (source) to narrow (SNOMED)
  • Good argument that SNOMED needs more content
  • Narrow (source) to broad (SNOMED)
  • SNOMED may need/want the content
  • Map to a post-coordinated concept may be required

22
Post-coordination(for NAHLN mapping)
  • What is post-coordination?
  • Create a new concept by adding specificity to and
    existing SNOMED concept.
  • Source has
  • Acute pasteurella pneumonia
  • Target (SNOMED) has
  • pasteurella pneumonia
  • Create
  • Pasteurella pneumonia has course acute

23
Post-coordination(for NAHLN mapping)
Pasteurella pneumonia has course acute
  • Where do you put your new creation?
  • Extend the concepts table (1 new)
  • Identifier outside of SNOMED itself (namespace
    mechanism)
  • Extend the relationships table
  • An extension (not part of core)
  • Processed as if it is part of the original table.

24
SNOMED -gt LOINC map?
  • SNOMED can be used to provide a categorization
    hierarchy for LOINC codes through the map.
  • Probably unnecessary unless vocabulary server
    approach is employed.

25
Species and Breeds
  • It is our INTENTION that the living organisms
    hierarchy should accurately reflect the current
    state of the art re animal taxonomy.
  • Each entry has taxonomic rank identified in FSN
  • Relationship type 3 (additional) to support a
    relationship that identifies taxonomic rank.

26
Species and Breeds
  • Gather species and breeds
  • Select the root for the hierarchy
  • Perform recursive search for children
  • Identify taxonomic rank
  • Process string of FSN
  • Fact relationship
  • has taxonomic rank breed (etc.)

27
Concept Addition
  • Users WILL discover concepts that are not present
    in the nomenclature
  • Licensed users can make requests to SNOMED
    directly
  • Channels have been established for timely
    addition.

28
Concept Addition
  • When we (AVMA Secretariat) receive a request for
    concept addition
  • We confirm that the concept is really missing
  • Often there is a synonym present
  • Requested description can be added
  • We prepare a SNOMED-style definition for the
    concept
  • Concepts are added to the nomenclature by a
    veterinarian on SNOMED staff

29
Nomenclature Updates
  • New version of SNOMED scheduled for every 6
    months.
  • Expect change rate to decline with time
  • NLM updating may be less frequent.
  • NLM updating will certainly lag behind SNOMED
    releases.

30
Nomenclature Updates
  • Retired Concepts
  • Concept referral mechanism
  • New Concepts
  • Retired Descriptions
  • New Descriptions
  • New relationships

31
Queries
  • Query full copy of SNOMED
  • Queries based on description have highest yield.
  • Indexes
  • Query portion that has been recorded?

32
SNOMED Extensions
  • Enable authorized organizations to add Concepts,
    Descriptions, Relationships and Subsets to
    complement those that are centrally maintained as
    the core content of SNOMED CT.
  • specialized terminology needs of an organization.
  • Extensions maintain unique identification across
    organizations for data transmission and sharing.

33
SNOMED Extensions
  • Distinguishable from the main body of SNOMED CT
  • in the thesaurus
  • when stored in a patient record, query or
    decision support protocol.
  • Distinguishable from other Extensions, in the
    same way as they are distinguishable from the
    main body of SNOMED CT.
  • Able to be distributed and processed in the same
    way as equivalent components from the main body
    of SNOMED CT without requiring specific
    adaptations of SNOMED-enabled applications.

34
Existing Extension(s)
  • US Drug extension
  • List of drugs marketed in the United States
  • UK Drug extension
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