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Clinical Coding Principles and Practice

Learn about medical terminologies, coding schemes, and terminologies' integration with clinical information systems. Understand diverse components of medical terminologies and how to classify them for efficient use. Explore challenges and benefits of using medical terminologies.

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Clinical Coding Principles and Practice

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  1. Clinical Coding 2 Dr JL FisteinMA MB BChir BarristerE-mail: jfistein@hiconsultants.com March 2003

  2. Aims • Some learning objectives & quick recap of part 1 • Hands-on-coding exercise • Tools and examples

  3. Aims • Some learning objectives & quick recap of part 1 • Hands-on-coding exercise • Tools and examples

  4. Learning objectives 1 • Know what a medical terminology is • Be aware that many medical terminologies exist Source: RCSEd

  5. Learning objectives 2 • Know where medical terminologies fit in with other technologies • Integrating with other medical knowledge bases • Integrating with data models Source: RCSEd

  6. Learning objectives 3 • Know what the component parts of medical terminologies are: • Concept • Link • Term • Code • Organisation Source: RCSEd

  7. Learning objectives 4 • Know how to classify medical terminologies • By domain type (or content) • Scope • Coverage • By use or intended purpose • Fitness for purpose • By technical properties Source: RCSEd

  8. Learning objectives 5 • Understand the problems in creating / using medical terminologies • Scaling • Usability • Analytic capability Source: RCSEd

  9. Learning objectives 1 • Know what a medical terminology is • Be aware that many medical terminologies exist Source: RCSEd

  10. What is a medical terminology? • NB Strictly terminologies are just collections of terms (see later) without any kind of link to concepts!

  11. What is a medical terminology? • Controlled vocabularies • Collections of words (terms) usually assembled for a specific purpose • Hard to reuse • Coding schemes • Some kind of term list where each term has a code • Often arranged hierarchically according to the meaning of the terms but may be flat (unordered)

  12. What is a medical terminology? • Classifications / taxonomies / ontologies • Term list + codes + hierarchy • Hierarchy should be “is-a” (this is not the case in many real-world examples – expedience) • Concepts usually richly represented • Usually creates a model of the domain that aims to allow maximum reuse

  13. Learning objectives 1 • Know what a medical terminology is • Be aware that many medical terminologies exist Source: RCSEd

  14. How many different terminologies exist? • Remember there are hundreds! • We’ll recap why this is later • E.g. UMLS contains cross-references between 79 different schemes

  15. How many different terminologies exist? • Graph of Primary Care schemes used in different countries (1995) Source: Coding and nomenclatures: a snapshot from around the world (Wilson & Purves)

  16. Learning objectives 2 • Know where medical terminologies fit in with other technologies • Integrating with other medical knowledge bases • Integrating with data models Source: RCSEd

  17. Medical Terminologies and Clinical Information Systems Source: the OpenGALEN organisation www.opengalen.org

  18. Terminologies and CISs • Terminologies must integrate with CISs to be useful – cannot exist in isolation • Terminologies become bits of software not static resources (like books) • Requires good “interfaces” between terminology and the CIS

  19. Integrating Terminologies with other knowledge sources • Particularly • post hoc analysis • Prediction (decision support) • Typically using IF…THEN reasoning (although remember other approaches)

  20. Integrating terminologies with other data models • Different data models for different purposes • Rich codes & simple data model vs. simple codes & rich data model • Encapsulation • (A slight aside: interface layers to present related concepts e.g. cough / smoking)

  21. Learning objectives 3 • Know what the component parts of medical terminologies are: • Concept • Link • Term • Code • Organisation Source: RCSEd

  22. Concept • NB Semantic triangle • Further refinement • Primitive concept – not composed of other concepts • Composed concept – composed of a (sensible) combination of other concepts

  23. Link • NB Object-Attribute-Value triples • A relationship between two concepts • Types: • Is-A • Symmetrical (e.g. is parallel to) • Asymmetrical (e.g. has part)

  24. Term • NB Semantic Triangle • A text label for something • Also • Synonyms • Homonyms • Eponyms

  25. Code • A (usually abstract) identifier for a concept or link

  26. Putting it all together A classification (ontology / taxonomy) fragment Femoral pathology Fracture (P-23) Fractured Femur (MS-1100) Fractured Shaft of Femur (MS-1233) Fractured NOF (MS-1234) NOF (A-99) Fracture (P-23) hasLocation (L-2)

  27. Putting it all together An is-A relationship Femoral pathology Fracture (P-23) Fractured Femur (MS-1100) Fractured Shaft of Femur (MS-1233) A composed concept Fractured NOF (MS-1234) NOF (A-99) Fracture (P-23) hasLocation (L-2) A primitiveconcept A link Codes

  28. Putting it all together Femoral pathology Fracture (P-23) Fractured Femur (MS-1100) Fractured Shaft of Femur (MS-1233) Fractured NOF (MS-1234) NOF (A-99) Fracture (P-23) hasLocation (L-2) “NOF” “Femoral neck” “neck of femur” Terms

  29. Learning objectives 4 • Know how to classify medical terminologies • By domain type (or content) • Scope • Coverage / depth • By use or intended purpose • Fitness for purpose • By technical properties Source: RCSEd

  30. Specialist topic • Nurses: ICNP, NANDA, NIC, OMAHA, HHCC • Surgery only: OCPS-4, CPT • Diseases: ICD • Cancer: ICD-O • Impairment, disability & handicap: ICIDH • All of medicine: READ, SNOMED

  31. Intended Application • Billing: CPT4, ICD9-CM, CCAM • Epidemiology & Statistics: ICD • Healthcare record: READ • Reference: ? SNOMED-CT, UMLS

  32. Technical Properties • Enumerated vs compositional schemes • Lexical schemes

  33. Learning objectives 5 • Understand the problems in creating / using medical terminologies • Scaling • Usability • Analytic capability Source: RCSEd

  34. Scale • (Particularly enumerative schemes) tend to become very large 150-200,000 terms • Hard to remember what’s in there • Hard to organise • Hard to analyse • Different people use the same code to mean different things

  35. Organisation • Needs organisation for different purposes • Navigation • Statistical analysis • Underlying collection of terms and concepts is large and complex • Hard to guess every possible use for the concepts

  36. Technical • Assigning meanings to codes (may mislead the user) • Having limited code lengths (READ2)

  37. Other problems • Compositional nonsense • Redundancy • Post-hoc classification • Computational intractability

  38. Aims • Some learning objectives & quick recap of part 1 • Hands-on coding exercise • Tools and examples

  39. Objective • See how hard it is to devise clinical terminologies! • Pity the poor coding clerks

  40. The Task • Come up with the one true, correct, complete classification for children’s party food, etc. (Output: a single OHP sheet) • Time limit: • 15 minutes (in groups) • 15 minutes debrief / comparisons (argument!)

  41. Perspectives • Caterers • Nutritionists • Parents • Children

  42. Approaches • Use any that we have discussed so far • (hint: you will need to devise a classification so don’t adopt a purely enumerative approach) • Don’t worry that you can’t classify everything perfectly – that’s what computers are for!

  43. A starter for 10… • Some concepts you might consider… • Hula hoops • Jammie dodgers • Paper plates • Orange squash • Gluten-free birthday cake • Candles • Barbie

  44. Results • I predict: completely different classifications between the groups, argument within the groups re: the best approach and where concepts should fit.

  45. Results • But: don’t be discouraged • Even professionals disagree (that’s why there are many different coding schemes) • Different purposes • Different individuals • Limited time

  46. Results of another coding exercise • Students asked to describe Magritte’s “The Heart of the Matter” using the Art & Architecture Thesaurus (AAT) from the Getty Museum Thanks to Jeremy Rogers, MIG, University of Manchester

  47. Coding Confusion: An example Suitcase Luggage Attaché case Model Person Woman Adults Headcloth Cloth Scarf Standing Background Brown Blue Chemise Dress Tunics Clothes Brass Instrument French Horn Horn Tuba X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X

  48. Real-life examples • Clue (Read 3) • KnoME (GALEN) • Clinergy – a clinical application!

  49. Recommended Web Links and Papers • Bechhofer SK, Goble CA, Rector AL, Solomon WD, and Nowlan WA. Terminologies and Terminology Servers for Information Environments. In: Proceedings of STEP '97 Software Technology and Engineering Practice, 1997. URI: http://citeseer.nj.nec.com/354766.html • Chute CG, Elkin PL, Sheretz DD and Tuttle MS. Desiderata for a Clinical Terminology Server. In: Proceedings of AMIA'99 Annual Symposium, 1999. URI: http://www.amia.org/pubs/symposia/D005782.PDF • Rector AL. Clinical Terminology: Why Is it so Hard? Methods Inf Med. 1999;38(4-5):239-52 • The British Association of Clinical Terminology Specialists: http://www.bacts.org.uk/ • OpenGALEN: http://www.opengalen.org/and the Medical Informatics Group of Manchester Universitywww.cs.man.ac.uk/migparticularly www.cs.man.ac.uk/mig/links/RCSEd/terminology.htm Jeremy Roger’s excellent set of teaching materials; has links to other sources & more exercises • Read Codes Engines: http://www.cams.co.uk/and http://www.visualread.com • See also “Related Web Links” section at:https://wwws.soi.city.ac.uk/intranet/students/courses/mim/mi/lect2_2.htm

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