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caBIO at BOSC 2002 NCICB

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International dictionary of medical terms including some 65,000 diagnoses, signs ... Used as online dictionary and thesaurus, for mapping and document indexing ... – PowerPoint PPT presentation

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Title: caBIO at BOSC 2002 NCICB


1

Use of Mapping for caBIG Standard Vocabularies
Issues to Consider
Margaret Haber Office of Communications National
Cancer Institute
2
Overview
  • Mapping Why
  • Mapping How
  • NCI Metathesaurus example methods
  • caBIG Mapping Issues and Questions

3
One Answer is MappingRelating Terminologies for
Effective Data Exchange
  • A holistic view of information exchange requires
    broader interoperability, butwhere do we place
    the fences?
  • Clinical data, regulatory submissions, discovery
    research?
  • Industry agreements, nationally accredited,
    global standardization?

4
The Pillars of InteroperabilityNecessary but not
sufficient
  • Common information models across all domains of
    interest
  • A foundation of rigorously defined data types
    (metadata)
  • A methodology for interfacing with controlled
    vocabularies

5
Interoperability Keys for Terminology
  • Use of Industry Standards, where feasible
  • Must allow for extensions to core standards
  • Specialty terminology remains common
  • Mapping is therefore essential
  • Conformance with Data Models
  • For process (logical models)
  • For data flow (messages)
  • For data at rest (database design)

6
Mapping has been named as an essential part of
enabling effective interchange between core,
standard terminologies. Complete mapping includes
  • An initial high level map performed using
    algorithmic insertion formulas, such as lexical
    matching, followed by human review for accuracy
  • Rule-based mapping of non-overlap areas using
    consistent, explicit coding principles
  • Actual testing and implementation in systems that
    demonstrate accuracy and effectiveness for data
    capture, transfer, collection and interpretation

7
High Level Map
  • Identifies content/concept overlap and gaps
  • Reveals issues of semantic equivalence or
    synonymy, differences in definition of terms
  • Allows comparative analysis of classification
    systems and structural models
  • Provides comparison of content coverage in
    required domains
  • Allows system query to quantify comparisons for
    further analysis

8
COSTART vs MedDRA vs SNOMED
9
Rule Based Map
  • Often application and system dependent
  • Requires domain knowledge and consensus to judge
    appropriate methodology for concept-walking
    between terminologies
  • Must grapple with issues of pre- vs.
    post-coordination (full specification vs.
    composition) of terms and concepts
  • Terminology assessment and gap analysis
    identifies new concept needs, driving both
    structural requirements for the terminologies and
    the mapping rules between them

10
As an example of some issues that can be involved
. . . .
11
SNOMED CT
  • Merger of the College of American Pathologists
    Systematized Nomenclature of Medicine (SNOMED)
    Reference Terminology (RT) and UK Clinical Terms
    Version 3 (CTV3 or Read Codes)
  • Broad based clinical terms (CT) with 350,000
    concepts, gt1.37 Million semantic relationships
  • Terms of License Five year free distribution in
    US through NLMs UMLS for English and Spanish
    versions including concepts, descriptions,
    relationships, and history. If terminated, the
    last version of SNOMED remains distributable with
    no further updates provided

12
MedDRA (v7.1)
  • Description
  • International dictionary of medical terms
    including some 65,000 diagnoses, signs
    symptoms, adverse drug reactions, therapeutic
    indications, names/results of laboratory,
    radiological, and other investigations,
    surgical/medical procedures, social circumstances
  • Developer
  • Under the auspices of the International
    Conference on Harmonization of Technical
    Requirements for Registration of Pharmaceuticals
    for Human Use (ICH) as agreed-upon terminology
    for regulatory reporting
  • Terms of Licensing
  • Maintenance and Support Services Organization
    (MSSO) supplies MedDRA in various formats,
    multiple levels of subscription

13
MedDRA vs SNOMED Content
  • MedDRA content coverage, granularity (level of
    detail) and fully specified (pre-coordinated)
    terms suited to the capture of data relevant to
    adverse event reporting for drugs
  • SNOMED has broader/more granular content
    coverage for the representation of information in
    many domains of patient records, potential for
    enabling post-coordination (composition) of
    concepts

14
MedDRA vs SNOMED Structure
  • MedDRA hierarchy not is_a but rather groups of
    related terms in a structure designed to maximize
    capture and retrieval of relevant related terms
    these terms may fall into more than one higher
    level grouping
  • SNOMED is concept based, with terms and true
    synonyms classified in an is_a
    poly-hierarchical structure it is more reliant
    on composition to fully express granular concepts

15
Example of MedDRA Terminology Links for Toxic
Epidermal Necrolysis
Skin and Subcutaneous Tissue Disorders
Infections and Infestations
Injury, Poisoning and Procedural Complications
Immune System Disorders
SOC
Epidermal and Dermal Conditions
Ancillary Infectious Topics
Chemical Injury, Overdose, and Poisoning
Allergic Conditions
HLGT
Bullous Conditions
Inflammatory Disorders Following Infection
Poisoning and Toxicity
Allergies to Foods, Food Additives, Drugs and
Other Chemicals
HLT
Toxic Epidermal Necrolysis PT
PT
Drug Eruption Lyell Syndrome Type
Necrolysis Epidermal Toxic (Lyell Type)
Necrolysis Epidermal Toxic (Lyell Type)
Necrolysis Epidermal Toxic (Lyell Type)
Necrolysis Epidermal Toxic (Lyell Type)
Necrolysis Epidermal Toxic (Lyell Type)
Necrolysis Epidermal Toxic (Lyell Type)
LLT
Drug Eruption Lyell Syndrome Type
Necrolysis Epidermal Toxic (Lyell Type)
Necrolysis Epidermal Toxic (Lyell Type)
Necrolysis Epidermal Toxic (Lyell Type)
Necrolysis Epidermal Toxic (Lyell Type)
Necrolysis Epidermal Toxic (Lyell Type)
Necrolysis Epidermal Toxic (Lyell Type)
16
Example of SNOMED Terminology Links for Toxic
Epidermal Necrolysis
Chemical compound
Barbitone chemical
Chemical product
Chemical categorized structurally
Chemical suspension
Antipyrine
Has causative
Pyrazole derivative
  • Toxic epidermal necrolysis Synonyms Lells
    toxic epidermal necrolysis, supdpidermal type
    TEN Toxic epidermal necrolysis Lyells
    syndrome

Dermis
Has finding site
Is a
Is a
Chemical-induced dermatotogical disorder
Non-infectious, vesicular and/or bullous disease
Disease of skin and/or subcutaneous tissue
17
Issues to consider when looking at potential
standard terminologies before undertaking maps
  • Terminologies in use for health communications
    reporting must have clear policies and procedures
    for both national and international use
    (scope/extent of license, fees, maintenance)
  • Reliable mechanisms for user feedback must be in
    place to ensure requirements for updates can be
    incorporated into the terminology and published
    on a regular basis
  • The above requirement (2) becomes more
    challenging with terminologies that have very
    broad coverage or a wide user base

18
Issues to Consider . . .
  • Concept capture is only one part of the story
    structure such as hierarchy is critical for
    aggregation and retrieval, and very important
    particularly for reporting applications
  • Hierarchies are also important in mapping, to
    indicate the intended meaning of a concept if
    ambiguous, and to provide appropriate terms for
    mapping (up-coding) from more granular
    terms/terminologies. Cross-maps thus require
    comparative structural analysis
  • Size of the terminology and depth of hierarchies
    can be a significant issue for applications

19
NCI EVS Goal Integration by Meaning
  • Clinical, translational, and basic research
    terminology have overlapping but specialized
    needs, therefore EVS assists to
  • Integrate different conceptual frameworks
  • Create terminological and taxonomic conventions
    across systems
  • Provide terminology for
  • Tagging store/transfer/archive data for future
    analysis
  • Reasoning limited inferencing about data

20
NCI Metathesaurus
  • Filtered UMLS Metathesaurus extended with
    additional required vocabularies
  • 930,000 concepts, 2,200,000 terms and phrases
    with definitions
  • Mappings among over 50 vocabularies
  • Extensive synonymy Over 40,000 terms for
    neoplasms mapped to 7,000 concepts
  • Used as online dictionary and thesaurus, for
    mapping and document indexing

21
NCI Metathesaurus (2)
  • Minor releases monthly, Major releases twice a
    year
  • Provides a mapped overlap and partial
    inter-relation of current versions of NCI
    required vocabularies, ex. The ICDs, MedDRA,
    SNOMED, MeSH (NLM Medical Subject Headings),
    HCPCS (procedures), LOINC (lab values), drug
    terminologies (VA NDF, AOD, RxNORM, Multum, NCI
    Thesaurus drugs, etc.)

22
NCI Metathesaurus Data Profile
  • Multiple sources per concept or unit of
    semantic meaning
  • Hierarchically organized to reference NCI
    Thesaurus structures when possible alternate
    source hierarchies may also be viewed
  • 109 Term Types within concepts such as
    preferred term (PT), synonyms (SY), abbreviations
    (AB), obsolete (OB), brand name (BR) drugs, etc.

23
NCI Metathesaurus Profile (2)
  • 135 Semantic Types divide groups of concepts
    into general domains of meaning such as
    Neoplasms, Genes, Pharmacologic Substance,
    etc.
  • gt5,600,000 asserted relationships between
    concepts ex.
  • Carcinoma Clinically_associated_with Lytic
    Bone Lesion,
  • TP53 Gene_associated_with_Disease Breast
    Carcinoma

24
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25
 
 
 
 
 
 
  • For Mapping caBIG Standard Vocabularies
  • Is it advisable to offer a caBIG standard
    terminology set based on concept mappings to an
    existing standard terminology?

26
Maybe
  • The answer is a qualified yes but its not
    easy, and risks are present.
  • Maps are difficult to construct.
  • Even carefully constructed maps can convey some
    degree of false synonymy
  • Like terminologies, maps need maintenance.

27
Imprecise or False Synonymy
  • It may not be possible to find an exact match
    between concepts in two terminologies.
  • Often the best one can do is to come close.
  • How is the degree of closeness indicated to a
    user?
  • For certain applications, e.g., clinical,
    close may not be acceptable.

28
Like Terminologies, Maps Require Maintenance
  • A map exists between a pair of terminologies,
    both of which are at specified revision levels or
    versions
  • A change to either terminology requires that the
    map be re-verified and possibly redone

29
This Raises Questions
  • Who will consistently verify an update maps?
  • How committed is the mapping organization to
    this activity?
  • How much time is needed to update the map after
    either vocabulary changes?
  • What is the status of a mapped terminology
    extension in the interim?

30
One Size Doesnt Fit All
  • Theres no single definitive map between a pair
    of terminologies
  • Maps must be based on a well-defined use cases
  • Different use cases may require different maps
  • Example NLM makes multiple maps between CPT
    and ICD to meet varying use cases from providers
    and payers.

31
Vocabularies for Reporting are Especially
Demanding
  • Its extremely challenging to substitute an
    alternative terminology for one designed for
    specific purposes.
  • FDA requires MedDRA for reporting adverse events
  • It would be difficult to code adverse events
    using another terminology and map precisely to
    MedDRA for reporting.
  • There is significant potential to undermine the
    integrity of the reports submitted.

32
The Bottom Line
  • Mapping is expensive, inherently limited, highly
    particularized, and represents an ongoing burden
  • The payoff for a mapping effort must be justified
    by clear operational benefits
  • If a mapped terminology becomes a caBIG standard,
    its ongoing maintenance and integrity becomes a
    significant concern for all users of that
    terminology
  • The analysis that supports the decision to create
    such a map must consider all the costs and risks
    of doing so.

33
EVS Team Acknowledgments
  • NCI Office of Communications
  • Margaret Haber
  • Larry Wright
  • NCI Center for Bioinformatics
  • Frank Hartel
  • Sherri de Coronado
  • Gilberto Fragoso
  • Contractors
  • Apelon, Inc. Northrop Grumman, Inc.
  • Aspen, Inc. Kevric / IMC
  • MSD J. Oberthaler Consulting
  • SAIC Protégé/SMI
  • Collaborations External Reviews
  • NCI caBIG, CTEP, DTP, DCP, DCCPS, MMHCC, etc.
  • NIH NLM, NHLBI
  • Govt FDA, VHA, CDC, DoD, NASA
  • Other CAP/SNOMED, AFIP, HL7, CDISC, MGED, W3C
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