1. OpenGALEN Slide No.: 1 Introduction to Clinical Terminology and Classification Clinical Decision Support L4 AL Rector OpenGALEN TopThing UK The Medical Informatics Group, U of Manchester www.cs.man.ac.uk/mig/galen www.opengalen.org www.topthing.com rector@cs.man.ac.uk

2. OpenGALEN Slide No.: 2 The Vision Best Practice Clinical Terminology Data Entry Clinical Record Decision Support Best Practice Data Entry Electroni c Health Records Decision Support & Aggregated Data GALEN Clinical Terminology HealthCard Mr Ivor Bigun Dun Roamin Anytown Any country 4431 3654 90273

3. OpenGALEN Slide No.: 3 Open GALEN: Philosophy Terminology is software  Terminology is the interface between people and machines Re-use is the key  Patient-centred information Terminology must have a purpose  Always ask: “What’s it for?” — Not art for art’s sake  Terminology supports clinical applications - not vice versa – Applications for someone to do something for somebody – Keep the ‘Horse before the Cart’  Always ask: “How will we know if it works?” “How will we know if it fails?”

4. OpenGALEN Slide No.: 4 Open GALEN: Key ideas Separation of kinds of knowledge  Terminology, medical record and information system schemas  Concepts, language, Coding, Indexing, Pragmatics  Machine level, User level Knowledge is fractal!  There will always be more detail to be added — Therefore terminologies must be extensible Formal logical Support  Too big and complicated to maintain by hand — Extensibility requires rules — Software needs logical rigour

5. OpenGALEN Slide No.: 5 Axes for kinds of Knowledge Machine level Human Level Concepts Language Coding Indexing Pragmatics & User Interface Terminology Medical Records/ Information systems

6. OpenGALEN Slide No.: 6 Uses of Terminology Clinical  Epidemiology and quality assurance  Reproducibility / Comparability  Indexing Software  Re-use !  Integration and Messaging between systems  Authoring and configuring systems  Data capture and presentation (user interface)  Indexing information and knowledge (meta-data, The Web)

7. OpenGALEN Slide No.: 7 History: Origins of existing terminologies Epidemiology  ICD - Farr in 1860s to ICD9 in 1979 — International reporting of morbidity/mortality  ICPC - 1980s — Clinically validated epidemiology in primary care  Now expanded for use in Dutch GP software Librarianship  MeSH - NLM from around 1900 - Index Medicus & Medline  EMTree - from Elsevier in 1950s - EMBase Remumeration  ICD9-CM (Clinical Modification) 1980 — 10 x larger than ICD; aimed at US insurance reimbursement

8. OpenGALEN Slide No.: 8 Traditional Systems Built by people for interpretation by people (Coding clerks)  Most knowledge implicit in rubrics — Must understand medicine to use intelligently  Not built for software On paper for use on paper  Enumerated - top down all possibilities listed — Serial - Single use - Single View Hierarchical Thesauri  Traditional terminological techniques from librarianship — ‘Broader than’ / ‘Narrower than’ (ISO 1087)  no logical foundation Focused on ‘terms’  Language and concepts mixed — Synonyms, preferred terms, etc caused confusion

9. OpenGALEN Slide No.: 9 History (2) Pathology indexing  SNOMED 1970s to 1990 (SNOMED International) — First faceted or combinatorial system  Topology, morphology, aetiology, function  Plus diseases cross referenced to ICD9 Specialty Systems  Mostly similar hierarchical systems — ACRNEMA/SDM - Radiology — NANDA, ICNP… - Nursing —…—…—…—…

10. OpenGALEN Slide No.: 10 History (3) Early computer systems  Read I (4 digit Read) — Aimed at saving space on early computers  1-5 Mbyte / 10,000 patients — Hierarchical modelled on ICD9  Detailed signs and symptoms for primary care  Purchased by UK government in 1990 — Single use  Morbidity indexing  Medical Entities Dictionary (MED) — Jim Cimino

11. OpenGALEN Slide No.: 11 History (4) Aspirations for electronic patient records (EPRs)  Weed’s Problem Oriented Medical Record — Direct entry by health care professionals Aspirations for decision support  Ted Shortliffe (MYCIN), Clem McDonald (Computer based reminders), Perry Miller (Critiquing),.. Aspirations for re-use  Patient centred information Needed common multi-use multi-purpose terminology  None worked

12. OpenGALEN Slide No.: 12 Summary of Changes at end of 1st Generation From terminologies for people to terminologies for machines From paper to software From single use to multiple re-use for patient centred systems From entry by coding clerks to direct entry by health care professionals From pre-defined reporting for statistics to reliable indexing for decision support

13. OpenGALEN Slide No.: 13 Problems with ‘First Generation’ Enumerated Systems in coping with these changes

14. OpenGALEN Slide No.: 14 Problems (1) Scaling !!!  More detail and more specialities required scaling up, but... The combinatorial explosion  Example: Burns: — 100 sites x 3 depths  404 codes  5 subsites/site x chemical or thermal  7272 –x 3 extents x 3 durations  –x 3 extents x 3 durations  116,352  ‘The Persian chessboard’ — 2 64 — 2 64  10 19   10 19 grains of rice  100 billion tonnes of rice   10 19 nanoseconds  10,000 years  Read II grew from 20,000 to 250,000 terms in ~100 staff-years — still too small to be useful  but too big to use

15. OpenGALEN Slide No.: 15 Problems (2) Information implicit in the rubrics  “Hypertension excluding pregancy” — Computers can’t read!  Invisible to software  No explicit information except the hierarchy — Minimal support for software — No opportunity to use softwre to help Language and concepts confused  Synonyms  Preferred terms  Homonyms  Only simple look up and spelling correction

16. OpenGALEN Slide No.: 16 Problems (3) Mixed Organisation  ‘Heart diseases’ in 13 of 19 chapters of ICD — Tumours, infections, congenital abnormalities, toxic, …  ‘Steroids’ in five chapters of standard drug classifications — Anti-inflammatories, anthi-asthmatics, …  Unreliable for indexing or Abstractions — How to say something about ‘all heart diseases’? Fixed organisation  Single hierarchy - Single use — Where to put ‘gout’ - arthritis or metabolic disease?  Back and forth in each edition of ICD — No re-use

17. OpenGALEN Slide No.: 17 Problems 3b Thesauri rather than Classifications A Mixed Hierarchy A correct kind-of (subsumption) hierarchy

18. OpenGALEN Slide No.: 18 Problems (4) ‘Semantic identifiers’  Codes really paths - moving a concept meant changing its code 3 Cardiovascular disorders … 3.4 Disorders of Artery...... 3.4.2 Disorders of coronary artery... … 3.4.2.3 Coronary thrombosis … Easy to process but...  Reorganisation requires changing codes  Codes cannot be permanent

19. OpenGALEN Slide No.: 19 Problems (5) Maintenance  20 Years from ICD9 to ICD10  ~100 person-years from Read 1 to Read 3  Mega francs/guilders/crowns/marks on European coding schemes  Thousands of unpaid hours of committee time — Impossible / meaningless decisions take longest  You can search forever for something that is not there — Multiple uses compete -  Must choose one use –Most successful were clear about their purpose - ICD, ICPC, MeSH Codes change meaning with version changes  Old data misleading!

20. OpenGALEN Slide No.: 20 Problems (6) Version specific artefacts  “Not otherwise specified” (NOS) — Used to move a general concept ‘down’  Not elsewhere classified (NEC) — Catch all - Nowhere else in coding system e.g. ‘Tumour not elsewhere classified’  dependent on version,  “Other” — Catch all - Not listed below, e.g. “Other diseases of the cardiovascular system”  dependent on version Not used consistsently

21. OpenGALEN Slide No.: 21 Problem (7): Language is slippery: Two hands or Four?

22. OpenGALEN Slide No.: 22 Language/Concepts are slippery Human cognition makes it look easy  Logic fails to capture it — Classification is easy until you try to do it  Trying since Aristotle in the West and Ancient Chinese in the East Words/Concepts mean what a community decides they mean  Does a chimpanzee have four hands?  Is a prion alive?  Is surgery on the ovary a kind of ‘Endocrine surgery’? Easier to agree on the concrete than the abstract  Easy to agree on useful abstractions and generalisations — Harder to agree on how to name them

23. OpenGALEN Slide No.: 23 Problems (8) There is no re-use - there is no standard  The ‘grand challenge’: A common controlled vocabulary for medicine — But re-use requires multiple different views  People’s needs differ / People do and find different things — By profession  Doctors and specialties, nurses, physiotherapiests, dentists… — By situation  Inpatient, outpatient, primary care, community… — By task  Diagnosis, management, prescribing,  patient care, public health, quality assurance, management, planning — By country and community  US, UK, France, Germany, Japan, Korea,...

24. OpenGALEN Slide No.: 24 Summary of Problems 1st Generation Enumerated Systems Enumerated Single Hierarchies  List all possibilities in advance — Cannot cope with fractal knowledge  Most knowledge implicit — Invisible to software  Can’t agree on common concepts and classification — Unreliable for indexing Difficult to use for healthcare professionals  No support for user interface Can’t build and maintain big classifications  Language and concepts don’t translate easily to logic and software

25. OpenGALEN Slide No.: 25 Cimino’s Desiderata (1) Concept orientation  Separate language (terms) and concepts (codes) Concept permanence  Never re-use a code (‘retire’ it) Nonsemantic concept identifiers  Separate the code from the path Polyhierarchy  Allow one concept to be classified in multiple ways — Gout can be both a metabolic disease and an arthritis

26. OpenGALEN Slide No.: 26 Cimino’s Desiderata (2) Formal Definitions  i.e ‘Be compositional’ Reject ‘Not elsewhere classified’  concept permanence and NEC Multiple granularities  Organ, tissue, cellular, molecular  Grades, types, classes of diseases  Special clinical criteria Multiple consistsent views  Allow different organisations — e.g. functional, anatomical, pathological

27. OpenGALEN Slide No.: 27 Cimino’s Desiderata (3) Represent context  Family history, risk, source of information Evolve gracefully  Allow controlled changes Recognise redundancy (equivalence)  ‘Carcinoma’ + ‘Lung’ ?=? ‘Carcinoma of the lung’ — How would we know?  How could a machine know?

28. OpenGALEN Solution Generation 1 Megaterm + Crossmapping = UMLS Clinical Applications Medical Records Data entry Decision support UMLS Medical Records Data entry Decision support MEGA- TERM Coding & Classification ICD-9 ICD-10 MeSH ACRNEMA ICPC SNOMED Axes READ OPCS

29. OpenGALEN Slide No.: 29 Unified Medical Language System (UMLS) from US National Library of Medicine  Defacto common registry for vocabularies — Concept Unique Identifiers (CUIs) and Lexical Unique Identifiers (LUIs) are defacto the common nomenclature Solution 1 Cross-mapping & UMLS

30. OpenGALEN Slide No.: 30 Solution 1 Cross-mapping & UMLS An invaluable resource, but...  No better than the vocabularies which are mapped — Limited detail for patient care — Unreliable for indexing or abstraction of knowledge — Best for relating everything to MeSH for indexing literature  Still limited by combinatorial explosion — Still can’t cope with fractal knowledge  Not extensible - no help in building or extending terminologiese  No help in reorganising existing terminologies to re-use for new purposes  Top down  Information still implicit — Minimal help with software  No help with data capture, user interfaces

31. OpenGALEN Slide No.: 31 Solutions Generations 2-3 Compositional Systems Beat the combinatorial explosion  Build concepts out of pieces - leggo — Dictionary and grammar rather than phrasebook  But hard

32. OpenGALEN Slide No.: 32 Solution Generation 1.5: Faceted Faceted systems: SNOMED International — Inflammation + Lung + Infection + Pneumococcus  Pneumoccal pneumonia Limit combinatorial explosion, but…  Rigid - a limited number of axes / facets / chapters  Each facet has the problems of a first generation enumerated system — Much knowledge still implicit  No way to know how identifiers relate — No explicit relations, only ‘+’ — No way to recognise redundancy / equivalence — No help with data capture or user interface / No way to recognise nonsense  Carcinoma + Hair + Donkey + Emotional  ????  Still can’t cope with fractal knowledge — Limited extensibility: limited help with building, extending or reorganising  Still Top Down

33. OpenGALEN Slide No.: 33 Generation 2: Enumerated Compositional Read III with qualifiers — Inflammation: site: lung, cause: pneumococcus  Pnemococcal Pneumonia More semantics but…  Limited qualifiers - limited views - limited re-use  Limited help with data capture - User interface difficult  Much information still implicit - limited software support — No way to recognise redundancy / equivalence / errors — Organisation still mixed - indexing better but still unreliable  Limited separation of language and concepts  Still can’t cope with fractal knowledge — Limited extensibility; limited help with building and reorganising terminologies  Top down

34. OpenGALEN Slide No.: 34 CT Vocabulary “Reference Terminology” vs “Interface Terminologies”  Reference terminology = enumerated hierarchy of formally defined terms  Interface terminology = navigation structure for user interface — Explicitly excluded from SNOMED-RT “Terming”, “Coding”, and “Grouping”  Terming - finding the lexical string  Coding - finding the correct unique code (concept)  Grouping - putting codes into groupers for epidmiological or other purposes

35. OpenGALEN Slide No.: 35 Generation 2.5 Pre-coordinated Formal Compositions SNOMED-RT (SNOMED-CT?) — Formal logical model for classifying a fixed list of definitions — Simple fixed ontology (7 links) GALEN derived terminologies  UK Drug Ontology  Procedure classifications

36. OpenGALEN Slide No.: 36 Generation 2.5 Pre-coordinated Formal Compositions More semantics Limited ability to cope with combinatorial explosion  Any one pre-coordinated terminology of fixed size — but arbitrarily many terminologies might be derived Limited ability to cope with fractal knowledge  Limited extensibility — Extensibility requires access to ‘Workbench’ — Bottom up / middle out More explicit information  Logical criteria for correctness / redundancy / equivalence — Based on knowledge representation (ontologies) and description logics Limited support for data capture and user interface

37. OpenGALEN Slide No.: 37 Generation 3: Post-Coordinated Formal Concept Model with Constraints delivered as Software Services OpenGALEN Reference Model - PEN&PAD/Clinergy™ — Inflammation which hasCause (Infection which hasCause Pneumococcus)  PneumococcalPneumonia  “Pneumococcal Pneumonia” A dictionary and grammar rather than a phrase book Software rather than data A sound logical and ontological foundation

38. OpenGALEN Slide No.: 38 Generation 3: Post-Coordinated Formal Concept Models Copes with combinatorial explosion  Indefinitely many compositions possible — Lists not pre-enumerated  Copes with fractal knowledge — Easily extensible to add more detail Most information explicit  More comprehensive ontology (50-250 links) Good support for data capture / user interface  But requires additional pragmatic knowledge layer Separates user view and machine view  Intermediate representation vs GRAIL

39. OpenGALEN Slide No.: 39 Case Study 1: The exploding bicycle ICD-9 (E826) 8 READ-2 (T30..) 81 READ-3 87 ICD-10 (V10-19) 587 V31.22 Occupant of three-wheeled motor vehicle injured in collision with pedal cycle, person on outside of vehicle, nontraffic accident, while working for income W65.40 Drowning and submersion while in bath-tub, street and highway, while engaged in sports activity X35.44 Victim of volcanic eruption, street and highway, while resting, sleeping, eating or engaging in other vital activities

40. OpenGALEN Slide No.: 40 Encrustation + involves: MitralValve Thing + feature: pathological Structure + feature: pathological + involves: Heart Description Logics: A crash course Thing Structure HeartMitralValveVegetation MitralValve * ALWAYS partOf: Heart Encrustation * ALWAYS feature: pathological Feature pathological red + feature: pathological + (feature: pathological)

41. OpenGALEN Slide No.: 41 Defusing the exploding bicycle: 500 codes in pieces 10 things to hit…  Pedestrian / cycle / motorbike / car / HGV / train / unpowered vehicle / a tree / other 5 roles for the injured…  Driving / passenger / cyclist / getting in / other 5 activities when injured…  resting / at work / sporting / at leisure / other 2 contexts…  In traffic / not in traffic V12.24 Pedal cyclist injured in collision with two- or three-wheeled motor vehicle, unspecified pedal cyclist, nontraffic accident, while resting, sleeping, eating or engaging in other vital activities

42. OpenGALEN Slide No.: 42 Goodbye to picking lists… Structured Data Entry File Edit Help What you hit Your Role Activity Location Cycling Accident

43. OpenGALEN Slide No.: 43 Other important links and initiatives HL7 Vocabulary group  See HL7 web site — Or join list server SNOMED-DICOM-Microglossary (Radiology) Nursing initiatives - see Nick Hardiker papers ISO TC215 WG2 / CEN TC251 WG3  See web sites

44. OpenGALEN Slide No.: 44 Criteria for success Re-use  A recognised growing library of common decsision support modules — Stop starting from scratch! Integration  2+ independently developed DSSs integrated with 2+ independently developed EPRS without exponentially increasing effort.

45. OpenGALEN Slide No.: 45 Criteria for success Authoring  No individual invests in their own terminology — enterprise-wide terminology servers Indexing  Simplification of systems — a sharp drop in special cases and exceptions — a sharp increase in authors’ productivity

46. OpenGALEN Slide No.: 46 Criteria for success User interfaces  Real systems in real use with real patients by real clinicians — transparent systems

47. OpenGALEN Slide No.: 47 Open GALEN www.opengalen.org