Werner CEUSTERS Center of Excellence in Bioinformatics and Life Sciences

1. MHI501 – Introduction to Health InformaticsThe UMLS, SNOMED andthe NCI Thesaurus(just to list a few, and in the first place … outstanding problems!)SUNY at Buffalo - November 7, 2007 Werner CEUSTERS Center of Excellence in Bioinformatics and Life Sciences University at Buffalo, NY, USA http://www.org.buffalo.edu/RTU

2. The problem to be solved

3. Better care Better information A general belief:

4. Being better informed Better care Better information ‘Information’ versus ‘informing’

5. A general belief: Being better informed • Concerns primarily the delivery ofinformation: Being better informed Better Better care information

6. A general belief: Being better informed • Concerns primarily the delivery of information: • Timely, • Where required (e.g. bed-side computing), • What is permitted, • What is needed. • Involves: • Connecting systems, • Making systems interoperable: • Syntactically, • Semantically.

7. HIMSS Integration and Interoperability Steering Committee • the ability of health IS to work together within and across organizational boundaries in order to advance the effective delivery of healthcare for individuals and communities, covering the following dimensions: • Uniform movement of healthcare data, • Uniform presentation of data, • Uniform user controls, • Uniform safeguarding data security and integrity, • Uniform protection of patient confidentiality, • Uniform assurance of a common degree of system service quality. Interoperability Definition and Background. Approved by HIMSS Board of Directors., 06/09/05.

8. HIMSS Integration and Interoperability Steering Committee • the ability of health IS to work together within and across organizational boundaries in order to advance the effective delivery of healthcare for individuals and communities, covering the following dimensions: • Uniform movement of healthcare data, • Uniform presentation of data, • Uniform user controls, • Uniform safeguarding data security and integrity, • Uniform protection of patient confidentiality, • Uniform assurance of a common degree of system service quality. No mention of information quality Interoperability Definition and Background. Approved by HIMSS Board of Directors., 06/09/05.

9. Ontolog-Discussion: Healthcare Informatics Landscape “The Business Value for Health IT Ontology Tools in Health Data and Information Systems: • Facilitates development of open-standards, interoperable networks of health information systems and EHRs, • Supports patient safety and goals to reduce medical errors in health care delivery, • Promotes data quality in the electronic exchange of health information.” Is about quality preservation Marc Wine, August 25, 2005

10. Patient-specific information Medical “knowledge” “Better Information” must cover … • EHR • PHR • Various modality related databases • Lab, imaging, … • Classification systems • Terminologies • Ontologies • Textbooks

11. Utility Coverage Authority Accuracy Objectivity Timeliness Understandability How to assess whether information is “better” ? Understandability Seems to have received most attention thus far

12. Some figures about the estimated size of “clinical language” (Evans & Patel ‘91) • number of unique medical expressions: 107 • In one domain (AIDS) : 150.000 candidate term phrases of 1 to 5 words found • 100-200 subdomains in medicine • estimated 2-word expressions: 4*106 • assumes 20.000 meaningful single words • assumes 10% combination rate

13. Some figures about the estimated size of “clinical language” (Tuttle & Nelson ‘94) • 0.5 x 106 entries in Oxford Dictionary of English • 0.3 x 106 word occurrences in Snomed 3.1 • 0.15 x 106 meanings in Meta-1.3 • 0.10 x 106 entries in Dorland’s Medical Dictionary • 0.05 x 106 entries in Webster’s Collegiate Dict. • 0.01 x 106 words in average human recognition voc. • 0.005 x 106 words in “basic English”

14. Coding systems and nomenclatures in healthcare • Main purposes: to stabilize the terminology • Mechanism: assign a code to every single term • Uses: • EDI • data storage and archiving • NLP • Disadvantages: • no internal structure • difficulties in finding specific terms • does not account for synonyms

15. Terminologies Ontologies Coding & classification systems More advanced ‘semantic’ technologies Utility Coverage Authority Accuracy Objectivity Understandability Timeliness Understandability

16. On ‘meaning’ and ‘understanding’

17. What is understanding ? • To understand something is to know what its significance is. • What 'knowing significance' amounts to may be very different in different contexts: thus understanding a piece of music requires different things of us than understanding a sentence in a language we are learning, for instance. It would be useful, then, for theorists to look at the different kinds of understanding that there are, and examine them in detail and without prejudice, rather than looking for the essence of understanding. (Tim Crane, philosopher of mind) • The significance of a single sentence, too, can vary from context to context.

18. The etymology of “understanding” • “understanding”  Latin “substare” • literally: “to stand under” • Websters Dictionary (1961) understanding =the power to render experience intelligible by bringing perceived particulars under appropriate concepts. • “particulars” = what is NOT SAID of a subject (Aristotle) • substances: this patient, that tumor, ... • qualities: the red of that patient’s skin, his body temperature, blood pressure, ... • processes: that incision made by that surgeon, the rise of that patient’s temperature,... • “concepts”: may be taken in the above definition as Aristotle’s “universals” = what is SAID OF a subject • Substantial concepts: patient, tumor, ... • Quality concepts: white, temperature • ...

19. Understanding natural language • Is constructing meaning from language by which the degree of understanding involves a multifaceted meaning-making process that depends on knowledge about language and knowledge about the world. ( cf. “reading comprehension” by humans. ) • But then: what is “meaning”

20. Dyadic models of “meaning” • Saussure (language philosopher): • signe / signifiant (sign/concept) • Ron Stamper (information scientist): • thing-A STANDS-FOR thing-B • Major drawback: • excludes the “referent” from the model, i.e. that what the sign/symbol/word/... denotes

21. Standard Semiotic/Semantic Triangle

22. Triadic models of meaning: The Semiotic/Semantic triangle Reference: Concept / Sense / Model / View / Partition Sign: Language/ Term/ Symbol Referent: Reality/ Object

23. Aristotle’s triadic meaning model Words spoken are signs or symbols (symbola) of affections or impressions (pathemata) of the soul (psyche); written words (graphomena) are the signs of words spoken (phoné). As writing (grammatta), so also is speech not the same for all races of men. But the mental affections themselves, of which these words are primarily signs (semeia), are the same for the whole of mankind, as are also the objects (pragmata) of which those affections are representations or likenesses, images, copies (homoiomata). Aristotle, 'On Interpretation', 1.16.a.4-9, Translated by Cooke & Tredennick, Loeb Classical Library, William Heinemann, London, UK, 1938. pathema semeia  gramma/ phoné pragma

24. my your understanding understanding Richards’ semantic triangle • Reference (“concept”): “indicates the realm of memory where recollections of past experiences and contexts occur”. • Hence: as with Aristotle, the reference is “mind-related”: thought. • But: not “the same for all”, rather individual mind-related reference symbol referent

25. R1 R2 R3 mole “skin lesion” mole “unit” mole “animal” Don’t confuse with homonymy ! “mole”

26. One concept understanding of x understanding of y referent symbol Different thoughts Homonymy R2 R3 R1 mole “skinlesion” mole “unit” “mole” mole “animal”

27. And by the way, synonymy... the Aristotelian view Richards’ view “sweat” “sweat” “perspiration” “perspiration”

28. Frege’s view • “sense” is an objective feature of how words are used and not a thought or concept in somebody’s head • 2 names with the same reference can have different senses • 2 names with the same sense have the same reference (synonyms) • a name with a sense does not need to have a reference (“Beethoven’s 10th symphony”) sense name reference (=referent)

29. Most terminologies are ‘concept’-based • But what the word ‘concept’ denotes, is never clarified and users of it often refer to different entities in a haphazard way: • meaning shared in common by synonymous terms • idea shared in common in the minds of those who use these terms • unit of describing meanings knowledge • universal that what is shared by all and only all entities in reality of a similar sort Smith B, Kusnierczyk W, Schober D, Ceusters W. Towards a Reference Terminology for Ontology Research and Development in the Biomedical Domain. Proceedings of KR-MED 2006, Biomedical Ontology in Action, November 8, 2006, Baltimore MD, USA

30. Most terminologies are ‘concept’-based • But what the word ‘concept’ denotes, is never clarified and users of it often refer to different entities in a haphazard way: • meaning shared in common by synonymous terms • idea shared in common in the minds of those who use these terms • unit of describing meanings knowledge • universal that what is shared by all and only all entities in reality of a similar sort These views require the involvement of a cognitive entity:

31. Most terminologies are ‘concept’-based • But what the word ‘concept’ denotes, is never clarified and users of it often refer to different entities in a haphazard way: • meaning shared in common by synonymous terms • idea shared in common in the minds of those who use these terms • unit of describing meanings knowledge • universal that what is shared by all and only all entities in reality of a similar sort These views require the involvement of a cognitive entity: This view does not presuppose cognition at all

32. Concept as mental particulars:Seth Russell’s ‘mentography’ http://robustai.net/mentography/Mentography.html (Just for reference, I didn’t study this in detail, so I make no statement about the value of this approach)

33. ‘Concept’*-orientation has sad consequences • Too much effort goes into the specification business • OWL, DL-reasoners, translators and convertors, syntax checkers, ... • Too little effort into the faithfulness of the conceptualizations towards what they represent. • Pseudo-separation of language and entities • “absent nipple”, “planned act”, “prevented abortion” • Many concept-based systems exhibit mistakes of various sorts. * When ‘concept’ is not clearly defined

34. Some examples • Gene Ontology • menopause part_of death * • SNOMED • both uterii is_a uterus * • UMLS • blood pressure is_a lab result • GALEN • vomitus contains carrot *corrected in most recent version

35. Another known problem: Intentionality in the semiotic triangle • “The physician wanted to give the patient an injection” • The physician gave the injection (= referent), and because of that, the patient died from a side-effect. • Hence: “giving the injection” = “killing the patient” (= two references) • Hence??? • “the physician wanted to kill the patient” ???

36. Take home message • Terminology: to find your way in language • Ontology: to find your way in what there is • Terminology + ontology: • to accurately describe what there is • to get an accurate picture of what there is on the basis of descriptions. • This works only if ontologies and terminologies exhibit a sound, consistent and coherent structure. • Most of them don’t !

37. The word ‘Ontology’ has two meanings • Ontology: the science of what entities exist and how they relate to each other. • An ontology:a representation of some domain which • (1) is intelligible to a domain expert, and • (2) is formalized in a way that allows it to support automatic information processing.

38. Within the context of ‘anontology’,the word ‘domain’ has two meanings • For most computer scientists: • A representation of an agreed upon conceptualization about which man and machine can communicate using an agreed upon vocabulary • For philosophical ontologists: • A representation of a portion of reality • Still allowing for a variety of entities to be recognised by one school and refuted by another one

39. Structure of remaining part of this talk • Discuss several well-known coding systems, classifications, terminologies, etc, … • Students should try to find the gazillion ways in which the principles of a coherent language-reality model are violated. • Since there are a gazillion violations, it should not be too difficult to find many. • Therefore, I make it more challenging by not listing the principles first.

40. An easy starter:Border’s classification of ‘medicine’

41. Refer to the size of the books that do not fit on a normal Border’s Bookshop shelf Border’s classification of medicine: what’s wrong ? • Medicine • Mental health • Internal medicine • Endocrinology • Oversized endocrinology • Gastro-enterology • ... • Pediatrics • ... • Oversized medicine

42. MeSH:Medical Subject Headings

43. MeSH

44. Wolfram syndrome Use of MeSH in PUBMED

45. MeSH: Medical Subject Headings • Designed for bibliographic indexing, eg Index Medicus • Basis for MedLINE  Pubmed • focuses on biomedicine and other basic healthcare sciences • clinically very impoverished • Consistency amongst indexers: • 60% for headings • 30% for sub-headings

46. MeSH Tree Structures - 2004 •  Anatomy [A] •  Organisms [B] •  Diseases [C] •  Chemicals and Drugs [D] •  Analytical, Diagnostic and Therapeutic Techniques and Equipment [E] •  Psychiatry and Psychology [F] •  Biological Sciences [G] •  Physical Sciences [H] •  Anthropology, Education, Sociology and Social Phenomena [I] •  Technology and Food and Beverages [J] •  Humanities [K] •  Information Science [L] •  Persons [M] •  Health Care [N] • Geographic Locations [Z]

47. MeSH Tree Structures – 2004 • Cardiovascular Diseases [C14] • Heart Diseases [C14.280] • Arrhythmia [C14.280.067] + • Carcinoid Heart Disease [C14.280.129] • Cardiomegaly [C14.280.195] + • Endocarditis [C14.280.282] + • Heart Aneurysm [C14.280.358] • Heart Arrest [C14.280.383] + • Heart Defects, Congenital [C14.280.400] • Aortic Coarctation [C14.280.400.090] • Arrhythmogenic Right Ventricular Dysplasia [C14.280.400.145] • Cor Triatriatum [C14.280.400.200] • Coronary Vessel Anomalies [C14.280.400.210] • Crisscross Heart [C14.280.400.220] • Dextrocardia [C14.280.400.280] +

48. ? ? What is the problem ? (MeSH 2007) Different set of more specific terms when different path from the top is taken.

49. All MeSH Categories Diseases Category Nervous System Diseases Female Urogenital Diseases and Pregnancy Complications Male Urogenital Diseases Eye Diseases Cranial Nerve Diseases Female Urogenital Diseases Neurodegenerative Diseases Optic Nerve Diseases Optic Nerve Diseases Urologic Diseases Heredodegenerative Disorders, Nervous System Eye Diseases, Hereditary Optic Atrophy Kidney Diseases Optic Atrophies, Hereditary Diabetes Insipidus Wolfram Syndrome MeSH: some paths from top to Wolfram Syndrome

50. All MeSH Categories ??? Diseases Category Nervous System Diseases Female Urogenital Diseases and Pregnancy Complications Male Urogenital Diseases Eye Diseases Cranial Nerve Diseases Female Urogenital Diseases … Neurodegenerative Diseases Optic Nerve Diseases Optic Nerve Diseases Urologic Diseases Heredodegenerative Disorders, Nervous System Eye Diseases, Hereditary has Optic Atrophy Kidney Diseases Optic Atrophies, Hereditary Diabetes Insipidus Wolfram Syndrome What would it mean if used in the context of a patient ? has