ECO R European Centre for Ontological Research The

ECO R European Centre for Ontological Research The Significance of SNODENT MIE 2005, Geneva Louis J. Goldberg, Werner Ceusters, John Eisner, Barry Smith Dr. Werner Ceusters European Centre for Ontological Research Saarland University Saarbrücken - Germany

ECO R European Centre for Ontological Research 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

ECO R European Centre for Ontological Research 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)

ECO R Materials European Centre for Ontological Research • 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 – – – D 5 -10000 F-51540 Dental disease, NOS Disease of teeth, NOS Tooth disorder, NOS Expectoration of bloody sputum 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)

ECO R European Centre for Ontological Research 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/termcodes 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

ECOSNODENT-graph extraction R from SNOMED European Centre for Ontological Research • For each enomen of SNODENT extract all SNOMED-concepts to which that term is associated, and for each such SNOMEDconcept extract all concepts on any path to the top, going over both isa and associative relationships Snomed-CT concept ISA associative

ECOThe re-classification algorithm R European Centre for Ontological Research • Automated post-coordination using version space theory: – Guided creation of: • Most specific generalisations: – If there is a concept with properties P 1 and P 2, then create a concept that is defined by these properties • Most generic specialisations: – Reclassify all existing concepts having the properties P 1 and P 2 – Process guided by existing subsumption hierarchy • Inspect suspicious configurations

ECO R Suspicious configurations European Centre for Ontological Research The presence of only one generated concept in a list of the concepts subsumed by a given concept; (xxx) The presence of only one existing subsumed concept next to a list of generated concepts for the same subsumer; (xxx) The presence of a preexisting concept that is subsumed by a generated concept without any other additional relationships from the pre-existing concept to another one. XXX XXX XXX

ECO Problems in the Calibration of R SNODENT and SNOMED (1) European Centre for Ontological Research • 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.

ECO Problems in the Calibration of R SNODENT and SNOMED (2) European Centre for Ontological Research • 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.

ECO Examples of single terms in SNODENT R used with plural meanings in SNOMED European Centre for Ontological Research SNODENT term SNODENT enomen SNOMED concept name Bruise M-14200 Bruise (finding) Bruise M-14200 Contusion – lesion (morphologic abnormality) Alveolar arch of mandible T-11182 Structure of alveolar arch of mandible (body structure) Entire alveolar arch of mandible (body structure) Bloody discharge M-36860 Bloody discharge (morphologic abnormality) Bloody discharge M-36860 Bloody discharge (substance) Chemotherapy P 2 -67010 Chemotherapy (procedure) Chemotherapy P 2 -67010 Drug therapy (procedure) Chemotherapy P 2 -67010 Antineoplastic chemotherapy regimen (regime/therapy) Administration of antineoplastic agent (procedure)

ECO What does the SNODENT R enomen – termcode relation captures ? European Centre for Ontological Research Reference to the same universal ? D 5 -10000 Dental disease, NOS Disease of teeth, NOS Tooth disorder, NOS F-51540 Expectoration of bloody sputum Expectoration of hemorrhagic sputum

ECO What does the SNODENT R enomen – termcode relation captures ? European Centre for Ontological Research Reference to ‘roughly’ the same universal ? (differences not being relevant for dentists) F-A 3692 F-A 3692 Adverse taste perception Chorda tympani disorder Dysgeusia Neurologic unpleasant taste Parageusia Perversion of sense of taste Primary taste disorder T-53120 Dorsal surface of anterior two-thirds of tongue Dorsal surface of tongue Dorsum of anterior tongue

ECO Failure to apply sound R ontological principles European Centre for Ontological Research D 5 -22070 Cheilodynia D 5 -22070 Painful lips D 5 -10578 Sensitive dentin D 5 -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 !

ECO Results of graph extraction R and reclassification European Centre for Ontological Research • ~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

ECO R Example of suspicious configuration European Centre for Ontological Research – XXX-10015676 XXX • DEVELOPMENTAL ABNORMALITY OF TOOTH SIZE AND FORM • CONGENITAL ANOMALY OF TEETH (DISORDER) : 79723009 – MOON'S MOLAR TEETH (DISORDER) : 109436001 – XXX-10007459 XXX • 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-10007569 XXX – MOLAR TOOTH STRUCTURE (BODY STRUCTURE) : 76928009 • XXX-10009937 XXX – 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

ECO R European Centre for Ontological Research 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.

ECO R Work to be done by CAP/ADA European Centre for Ontological Research • 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.

ECO R European Centre for Ontological Research Conclusion • SNODENT as a flat structure isn’t 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