Dave Parry Auckland University of Technology (Wednesday, 12.30, Data Analysis Workshop)

1. I KNOW JUST WHAT YOU
MEAN - ONTOLOGIES
AND THEIR USES
Dave Parry
Dave.parry@aut.ac.nz

2. Agenda
 What is an ontology ?
 Why use them ?
 How do you do that ?
 Where next ?

3. Words
`When I use a word,' Humpty Dumpty said
in rather a scornful tone, `it means just
what I choose it to mean -- neither more
nor less.„
Lewis Carroll “Through the Looking
Glass – and what Alice found there”
Image from “Mathematics Enrichment”

4. Ontologies
 “ Shared understanding of
a conceptualisation”
Deborah L. McGuinness
 Controlled set of concepts
that are themselves linked
by concepts

5. What are they for ?
 Mapping different terms to the same concept
 Search and information retrieval – mapping terms
to concepts that are broader or narrower
 Disambiguation – deciding WHICH concept you
mean
 Finding and converting concepts – especially for
coding

6. Why use an Ontology ? example…
 Pre-eclampsia
 Gestational Proteinuric Hypertension
 Toxaemia
 GPH
 PET
 PE
 All the same all map to.. pre-eclampsia 398254007 -
code

7. Why standardise ?
 Synonyms and obsolescent terms
 (HTLVIII vs HIV)
 Needed for clinical activity
 Communication
 Data analysis
 Coding
 Reminders etc.

8. Why use it ?
 In EHR systems, to replace/enhance free text.
 To support reminders “If patient has allergy to
a drug code recorded then alert if drug is being
prescribed”
 Converting free text to coded data….

9. What are they for ?
 Mapping different terms to the same concept
 Search and information retrieval – mapping
terms to concepts that are broader or narrower
 Disambiguation – deciding WHICH concept
you mean
 Finding and converting concepts – especially
for coding

10. Example
 Medical ontology
A finger is “part of” a hand
 A hand is “attached to” an arm
 Soif your left arm is amputated – the fingers are not
present on that side of the body !

11. Medical Ontologies
Is a
Limb Arm
Attached to
Hand
Part of
Fingers

12. What are they for ?
 Mapping different terms to the same concept
 Search and information retrieval – mapping terms
to concepts that are broader or narrower
 Disambiguation – deciding WHICH concept you
mean
 Finding and converting concepts – especially for
coding

13. 13
Obstetric
Small Surgical
Which
Forceps ?

14. What are they for ?
 Mapping different terms to the same concept
 Search and information retrieval – mapping terms
to concepts that are broader or narrower
 Disambiguation – deciding WHICH concept you
mean
 Finding and converting concepts – especially for
coding

16. Systematized Nomenclature of
Medicine-Clinical Terms -
SNOMED CT
 >600,000K Concepts
 SNOMED CT is a clinical vocabulary currently
administered by the international health terminology
standards development organisation (IHTSDO)
http://www.ihtsdo.org/. Member countries are;
Australia, Canada, Denmark, Lithuania, The
Netherlands, New Zealand, Sweden, United Kingdom
and United States.

17. SNOMED CT
 Very large clinical vocabulary that verges into being
an ontology
 Includes Subsets to simplify disambiguation and
reduce search space
 Mapping between SNOMED concepts and clinical
coding already exists.

18. General model
Extract SNOMED terms
Unstructured text EHR
Map to ICD 10 Send/receive messages

19. Ontology in Action
Original text Potential
fragments that
relate to
SNOMED terms
Potential
SNOMED
Concepts
Expanded
Selected Concepts SNOMED
Descriptions

20. Why is coding difficult ?
 Experts don’t agree – even when a loose standard
of agreement is required (Chiang 2006)
 SNOMED CT is very large and changes by 5-10%
each release
 Data is used in ways that might be unfamiliar to
the originator
 Ontologies can help resolve the meaning
Reliability of SNOMED-CT Coding by Three Physicians using Two Terminology Browsers
Michael F. Chiang, John C. Hwang, Alexander C. Yu, Daniel S. Casper, James J. Cimino, and Justin Starren
AMIA Annu Symp Proc. 2006; 2006: 131–135.

21. So what ?
 Errors propagate through systems
 SNOMED >ICD10 >DRG
 Free text present in many places in systems.
 Systems supporting coding may do better in
avoiding “Paper trail” errors (O’Malley 2005)
O'Malley, K. J., Cook, K. F., Price, M. D., Wildes, K. R., Hurdle, J. F., & Ashton, C. M.
(2005). Measuring diagnoses: ICD code accuracy.(International Classification of
Diseases). Health Services Research, 40(5), 1620(1620).

22. Cliniclue http://www.clinical-
info.co.uk

24. The semantic web and ontologies
 Tim Berners-Lee 2000

25. OWL – representing ontologies on
the web
 Ontology web language
http://www.w3.org/TR/owl-ref/
Example :
http://owl.man.ac.uk/2003/why/latest/

26. Designing ontologies
 Identify relationships between objects
 Relationships depend on domain
 Relationships can be simple “is-a” or extremely
complex e.g. “happens after all of the previous
events”

27. Take home message
 Ontologies allow real-world
knowledge to be represented
in computer systems
 Managing concepts is a key
task of health informatics
 The semantic web allows us
to store knowledge on the
web – and even move to
wisdom on the web