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The Significance of SNODENT MIE 2005, Geneva

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Title: The Significance of SNODENT MIE 2005, Geneva


1
The Significance of SNODENTMIE 2005, Geneva
Louis J. Goldberg, Werner Ceusters, John Eisner,
Barry Smith
  • Dr. Werner Ceusters
  • European Centre for Ontological Research
  • Saarland University
  • Saarbrücken - Germany

2
SNODENT
  • Structured NOmenclature of DENTistry
  • designed as a diagnostic companion to the Current
    Dental Terminology (CDT) treatment codes of the
    American Dental Association (ADA)
  • A collection of 6491 terms, partly (4900) taken
    from SNOMED, partly (1600) contributed by ADA
  • Integrated in SNOMED-CT starting with the January
    2004 version

3
Quality of SNODENT
  • Has the potential to become a de facto standard.
  • But is it of good enough quality ?
  • To answer that question
  • We compared it with SNOMED
  • We applied quality checking methods that have
    been used with succes in other checking other
    systems
  • SNOMED-CT (MEDINFO 2004)
  • NCI-Thesaurus (Meth Inform Med 2005)

4
Materials
  • SNODENT as a flat list of
  • 6491 unique enomens, each of them associated
    with one out of
  • 3863 unique termcodes
  • The termcodes are suspiciously similar to SNOMED
    concept codes
  • D5-10000 Dental disease, NOS
  • D5-10000 Disease of teeth, NOS
  • D5-10000 Tooth disorder, NOS
  • F-51540 Expectoration of bloody sputum
  • F-51540 Expectoration of hemorrhagic sputum
  • Thus we were interested to find out how that
    version of SNODENT compared to relevant content
    of SNOMED-CT (July 2003 version)

5
Methods
  • Simple analysis and comparisons
  • face validity of SNODENT-terms with respect to
    the associated codes (synsets)
  • There was no documentation on what the enomen
    termcode relationship in SNODENT represents !
  • Overlap of terms/enomens and conceptcodes/termcode
    s in both systems
  • Status of the SNODENT-terms if it were
    SNOMED-terms
  • SNODENT-graph extraction from SNOMED
  • Re-classification of that graph using our
    MEDINFO-2004 algorithm

6
SNODENT-graph extraction from SNOMED
  • For each enomen of SNODENT extract all
    SNOMED-concepts to which that term is associated,
    and for each such SNOMED-concept extract all
    concepts on any path to the top, going over both
    isa and associative relationships

ISA
associative
7
The re-classification algorithm
  • Automated post-coordination using version space
    theory
  • Guided creation of
  • Most specific generalisations
  • If there is a concept with properties P1 and P2,
    then create a concept that is defined by these
    properties
  • Most generic specialisations
  • Reclassify all existing concepts having the
    properties P1 and P2
  • Process guided by existing subsumption hierarchy
  • Inspect suspicious configurations

8
Suspicious configurations
The presence of only one generated concept in a
list of the concepts subsumed by a given concept
The presence of only one existing subsumed
concept next to a list of generated concepts for
the same subsumer
The presence of a pre-existing concept that is
subsumed by a generated concept without any other
additional relationships from the pre-existing
concept to another one.
(xxx)
(xxx)


XXX
XXX
XXX


XXX


XXX

9
Problems in the Calibration of SNODENT and SNOMED
(1)
  • 618 (9.52) of SNODENT terms,
  • involving 208 (5.38) termcodes,
  • point to concepts in SNOMED-CT that have a
    watch out status, distributed as follows
  • retired 86,
  • duplicate 15,
  • ambiguous 517.
  • 1203 (18.53) SNODENT terms point to SNOMED-CT
    concepts that are labelled as active, but that do
    not have (in SNOMED) the term used by SNODENT.
  • Hence
  • if SNOMED-CT would be taken as the gold standard,
    18.53 of the SNODENT terms must be considered to
    be inappropriate.
  • If SNODENT would be taken as gold standard,
    SNOMED-CT would lack 18.53 of the accepted terms
    in SNODENT.

10
Problems in the Calibration of SNODENT and SNOMED
(2)
  • 368 (5.67) SNODENT terms are not found in
    SNOMED, although the corresponding concept does
    exist in both systems (and with the same code).
  • Differences are due to
  • use of adjectival form,
  • use of a determiner,
  • use of NOS,
  • eponyms,
  • spelling variants.
  • SNODENT enforces just a single meaning for terms
    that are in and of themselves polysemous, but
    SNOMED allows terms to be used in a variety of
    meanings.
  • 437 (6.73) SNODENT terms are used in SNOMED with
    different meanings, the majority reflecting a
    (systematic) oddity of SNOMED rather than of
    SNODENT.

11
Examples of single terms in SNODENT used with
plural meanings in SNOMED
12
What does the SNODENTenomen termcode relation
captures ?
Reference to the same universal ?
D5-10000 Dental disease, NOS D5-10000 Disease of
teeth, NOS D5-10000 Tooth disorder,
NOS F-51540 Expectoration of bloody
sputum F-51540 Expectoration of hemorrhagic
sputum
13
What does the SNODENTenomen termcode relation
captures ?
Reference to roughly the same universal
? (differences not being relevant for dentists)
F-A3692 Adverse taste perception F-A3692 Chorda
tympani disorder F-A3692 Dysgeusia F-A3692 Neuro
logic unpleasant taste F-A3692 Parageusia F-A369
2 Perversion of sense of taste F-A3692 Primary
taste disorder
T-53120 Dorsal surface of anterior two-thirds of
tongue T-53120 Dorsal surface of
tongue T-53120 Dorsum of anterior tongue
14
Failure to apply soundontological principles
D5-22070 Cheilodynia D5-22070 Painful lips
D5-10578 Sensitive dentin D5-10578 Tooth
sensitivity
It is not because patient with cheilodynia
refers to the same entity as patient with
painful lips, that cheilodynia and painful
lips refer to the same entity !
15
Results of graph extraction and reclassification
  • 7500 SNOMED-CT concepts were extracted (2)
  • ( Original SNODENT termcodes 3863 )
  • 1081 new concepts generated through
    reclassification
  • I.e. 14,4 increase
  • Re-classification of SNOMED-CT in total showed
    only a 6 increase (MEDINFO 2004)
  • ? Dentistry poorly worked out in SNOMED

16
Example of suspiciousconfiguration
  • XXX-10015676XXX
  • DEVELOPMENTAL ABNORMALITY OF TOOTH SIZE AND FORM
  • CONGENITAL ANOMALY OF TEETH (DISORDER) 79723009
  • MOON'S MOLAR TEETH (DISORDER) 109436001
  • XXX-10007459XXX
  • SUPERNUMERARY CUSP (DISORDER) 234954009
  • SUPERNUMERARY ROOTS (DISORDER) 12270007
  • STRUCTURE OF CROWN OF TOOTH (BODY STRUCTURE)
    75628001
  • DISEASE OF HARD TISSUES OF TEETH (DISORDER)
    46557008
  • XXX-10007569XXX
  • MOLAR TOOTH STRUCTURE (BODY STRUCTURE) 76928009
  • XXX-10009937XXX
  • TUBERCULUM PARAMOLARE (DISORDER) 78305006
  • TAURODONTISM (DISORDER) 51744007
  • DENS EVAGINATUS (DISORDER) 63691004
  • MICRODONTIA (DISORDER) 32337007
  • PEG-SHAPED TEETH (DISORDER) 29553002
  • GENERALIZED MACRODONTIA (DISORDER) 93463007
  • MACRODONTIA (DISORDER) 71485000

17
Example of underspecification
  • SNOMED currently associates tooth finding only
    with the locations
  • digestive structure and
  • oral cavity structure
  • but not with the locations
  • tooth structure and
  • jaw region structure.

18
Work to be done by CAP/ADA
  • assessing which generated concepts should be
    included in an enhanced version of the SNODENT
    codes and which should be excluded
  • assigning a fully specified name to the included
    concepts
  • subjecting the differentiating criteria which led
    to the excluded concepts to a critical analysis
    and revising them accordingly
  • verifying for the included concepts that they
    subsume all concepts that they should subsume.
  • Estimated effort
  • the 1081 generated concepts themselves subsume
    between 1 and 37 concepts.
  • Many of the generated concepts that subsume only
    one concept have a meaning identical to that of
    the existing SNOMED-CT concept.

19
Conclusion
  • SNODENT as a flat structure isnt very helpful
  • SNODENT in snomed-ised form is better, not
    because the structure is good, but because the
    structure allows you to find mistakes better
  • SNOMED currently covers SNODENT not good enough
  • The part of SNOMED dealing with dentistry is
    structurally worse organised than the entire
    structure
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