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

2. 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

3. 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)

4. ECO R European Centre for Ontological Research 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 –D5-10000Dental disease, NOS –D5-10000Disease of teeth, NOS –D5-10000Tooth disorder, NOS –F-51540Expectoration of bloody sputum –F-51540Expectoration 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. 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

6. ECO R European Centre for Ontological Research 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 Snomed-CT concept ISAassociative Snomed-CT concept

7. ECO R European Centre for Ontological Research 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. ECO R European Centre for Ontological Research 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

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

11. ECO R European Centre for Ontological Research Examples of single terms in SNODENT used with plural meanings in SNOMED SNODENT termSNODENT enomen SNOMED concept name BruiseM-14200Bruise (finding) BruiseM-14200Contusion – lesion (morphologic abnormality) Alveolar arch of mandibleT-11182Structure of alveolar arch of mandible (body structure) Alveolar arch of mandibleT-11182Entire alveolar arch of mandible (body structure) Bloody dischargeM-36860Bloody discharge (morphologic abnormality) Bloody dischargeM-36860Bloody discharge (substance) ChemotherapyP2-67010Chemotherapy (procedure) ChemotherapyP2-67010Drug therapy (procedure) ChemotherapyP2-67010Antineoplastic chemotherapy regimen (regime/therapy) ChemotherapyP2-67010Administration of antineoplastic agent (procedure)

12. ECO R European Centre for Ontological Research What does the SNODENT enomen – termcode relation captures ? Reference to the same universal ? D5-10000Dental disease, NOS D5-10000Disease of teeth, NOS D5-10000Tooth disorder, NOS F-51540Expectoration of bloody sputum F-51540Expectoration of hemorrhagic sputum

13. ECO R European Centre for Ontological Research F-A3692Adverse taste perception F-A3692Chorda tympani disorder F-A3692Dysgeusia F-A3692Neurologic unpleasant taste F-A3692Parageusia F-A3692Perversion of sense of taste F-A3692Primary taste disorder What does the SNODENT enomen – termcode relation captures ? Reference to ‘roughly’ the same universal ? (differences not being relevant for dentists) T-53120Dorsal surface of anterior two-thirds of tongue T-53120Dorsal surface of tongue T-53120Dorsum of anterior tongue

14. ECO R European Centre for Ontological Research Failure to apply sound ontological principles D5-22070Cheilodynia D5-22070Painful lips D5-10578Sensitive dentin D5-10578Tooth 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. ECO R European Centre for Ontological Research 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. ECO R European Centre for Ontological Research Example of suspicious configuration –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. ECO R European Centre for Ontological Research 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. Example of underspecification

18. ECO R European Centre for Ontological Research 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. 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