This study evaluated the semantic proximity between terms in clinical archetypes and SNOMED CT concepts. The researchers analyzed 25 observation archetypes and manually mapped their data fragments to SNOMED CT concepts. They found that 30% of element fragments were subtypes of the root fragment, and 80% of value fragments were hierarchically related to other values in the same archetype. This high degree of semantic relatedness between archetype terms suggests that mapping archetypes to SNOMED CT could be improved by leveraging the relationships between concepts in SNOMED CT.
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Semantic proximity between archetype terms and SNOMED CT
1. Background
Objectives
Semantic proximity in archetypes
Mapping archetypes to SNOMED
.
A Study of Semantic Proximity between Archetype
Terms based on SNOMED CT Relationships
.
J.L.Allones, D.Penas, M.Taboada, D.Martinez and S.Tellado
KEAM Research Group
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
2. Background
Objectives
Semantic proximity in archetypes
Mapping archetypes to SNOMED
. Outline
.
1 Background
OpenEHR archetypes
SNOMED CT
Related Work
.
2 Objectives
.
3 Semantic proximity in archetypes
Dataset
Methods
Results
Conclusion
.
4 Mapping archetypes to SNOMED
Methods
Evaluation
Results
Discussion
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
3. Background
OpenEHR archetypes
Objectives
SNOMED CT
Semantic proximity in archetypes
Related Work
Mapping archetypes to SNOMED
. Outline
.
1 Background
OpenEHR archetypes
SNOMED CT
Related Work
.
2 Objectives
.
3 Semantic proximity in archetypes
Dataset
Methods
Results
Conclusion
.
4 Mapping archetypes to SNOMED
Methods
Evaluation
Results
Discussion
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
4. Background
OpenEHR archetypes
Objectives
SNOMED CT
Semantic proximity in archetypes
Related Work
Mapping archetypes to SNOMED
. OpenEHR archetypes
.
What is openEHR?
.
Open standard speciļ¬cation that describes the management,
storage and exchange of clinical data in EHR.
.
.
What are the archetypes?
.
OpenEHR deļ¬nes clinical data models called archetypes.
They model the clinical information required to record particular
clinical statements, such as tobacco use and exposure.
.
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
5. Background
OpenEHR archetypes
Objectives
SNOMED CT
Semantic proximity in archetypes
Related Work
Mapping archetypes to SNOMED
. OpenEHR archetypes
Extract of the archetype tobacco:
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
6. Background
OpenEHR archetypes
Objectives
SNOMED CT
Semantic proximity in archetypes
Related Work
Mapping archetypes to SNOMED
. OpenEHR archetypes
.
Current status of archetypes
.
Important institutions have participated in the
development of archetypes.
Problem: Archetypes hardly contain mappings
to standard concepts
.
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
7. Background
OpenEHR archetypes
Objectives
SNOMED CT
Semantic proximity in archetypes
Related Work
Mapping archetypes to SNOMED
. OpenEHR archetypes: Need for clinical terminologies
.
Terminologies are required:
To capture, use and transfer clinical data in a
standard form.
To reuse information collected in the course of
patient care.
Challenge of health informatics:
. To integrate archetypes and terminologies.
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
8. Background
OpenEHR archetypes
Objectives
SNOMED CT
Semantic proximity in archetypes
Related Work
Mapping archetypes to SNOMED
. SNOMED CT
.
SNOMED CT is the best positioned terminology
to semantically annotate archetypes because it is
an international standard which provides a consistent
terminology across all health care domains.
.
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
9. Background
OpenEHR archetypes
Objectives
SNOMED CT
Semantic proximity in archetypes
Related Work
Mapping archetypes to SNOMED
. SNOMED CT
.
Features:
Over 300,000 medical concepts.
Concepts can have several descriptions and semantic
relationships to other concepts.
.
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
10. Background
OpenEHR archetypes
Objectives
SNOMED CT
Semantic proximity in archetypes
Related Work
Mapping archetypes to SNOMED
. SNOMED CT
.
IS A relationships are also known as āSupertype -
Subtype relationshipsā. IS A relationships are the
basis of SNOMED CTās hierarchies.
.
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
11. Background
OpenEHR archetypes
Objectives
SNOMED CT
Semantic proximity in archetypes
Related Work
Mapping archetypes to SNOMED
. SNOMED CT
.
Attribute relationships associate two concepts speci-
fying a deļ¬ning characteristic of one of the concepts.
.
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
12. Background
OpenEHR archetypes
Objectives
SNOMED CT
Semantic proximity in archetypes
Related Work
Mapping archetypes to SNOMED
.
Need for automated mapping
.
SNOMED is a huge terminology
ā
Manual annotation of archetypes with SNOMED
concepts is very time-consuming.
ā
Automated mapping methods are needed.
.
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
13. Background
OpenEHR archetypes
Objectives
SNOMED CT
Semantic proximity in archetypes
Related Work
Mapping archetypes to SNOMED
. Related Work
.
Some studies have used lexical and linguistic
techniques to compare the strings of archetype
fragments and SNOMED CT concepts.
The works have not achieved optimum results:
They map correctly about 60% of archetype fragments.
They obtain too many candidate concepts for each
fragment (many of them are not relevant).
.
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
14. Background
OpenEHR archetypes
Objectives
SNOMED CT
Semantic proximity in archetypes
Related Work
Mapping archetypes to SNOMED
. Related Work
.
Diļ¬culties in automated mapping
.
.
1 Modelling archetypes separately from SNOMED
leads to diļ¬erences between them: disparity in
documentation granularity or naming diļ¬erences
.
Example of naming diļ¬erences:
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
15. Background
OpenEHR archetypes
Objectives
SNOMED CT
Semantic proximity in archetypes
Related Work
Mapping archetypes to SNOMED
. Related Work
.
Diļ¬culties in automated mapping
.
.
2 Some archetype terms have not been explicitly
modelled in the archetypes.
.
Example:
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
16. Background
OpenEHR archetypes
Objectives
SNOMED CT
Semantic proximity in archetypes
Related Work
Mapping archetypes to SNOMED
.
There are plenty of situations in which archetype clinical
information is semantically related
Similarities between the structure of the archetypes and the
network of SNOMED relationships
ā
. This may help in the automated mapping
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
17. Background
Objectives
Semantic proximity in archetypes
Mapping archetypes to SNOMED
. Outline
.
1 Background
OpenEHR archetypes
SNOMED CT
Related Work
.
2 Objectives
.
3 Semantic proximity in archetypes
Dataset
Methods
Results
Conclusion
.
4 Mapping archetypes to SNOMED
Methods
Evaluation
Results
Discussion
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
18. Background
Objectives
Semantic proximity in archetypes
Mapping archetypes to SNOMED
. Objectives
.
.
1 To understand better how archetype clinical
information is semantically related.
. To evaluate whether a combination of context
2
and structure-based techniques with lexical and
linguistic techniques can improve the automated
mapping of archetypes.
.
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
19. Background Dataset
Objectives Methods
Semantic proximity in archetypes Results
Mapping archetypes to SNOMED Conclusion
. Outline
.
1 Background
OpenEHR archetypes
SNOMED CT
Related Work
.
2 Objectives
.
3 Semantic proximity in archetypes
Dataset
Methods
Results
Conclusion
.
4 Mapping archetypes to SNOMED
Methods
Evaluation
Results
Discussion
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
20. Background Dataset
Objectives Methods
Semantic proximity in archetypes Results
Mapping archetypes to SNOMED Conclusion
. Studying semantic proximity between archetype terms
.
We checked the frequency and type of semantic
relationships between data fragments of 25
archetypes.
SNOMED relationships are the reference.
.
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
21. Background Dataset
Objectives Methods
Semantic proximity in archetypes Results
Mapping archetypes to SNOMED Conclusion
. Dataset: 25 Observation archetpes
.
25 OBSERVATION archetypes of the NHS repository.
information about the condi-
These archetypes record
tion of patients, such as the measurement of heart rate
and tobacco use.
.
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
22. Background Dataset
Objectives Methods
Semantic proximity in archetypes Results
Mapping archetypes to SNOMED Conclusion
. Parsing archetypes
.
A parser was used to preserve data fragments with clinical meaning.
Parser gets a dependency tree of data fragments for each
archetype.
.
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
23. Background Dataset
Objectives Methods
Semantic proximity in archetypes Results
Mapping archetypes to SNOMED Conclusion
. Parsing archetypes: Types of data fragments in archetypes
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
24. Background Dataset
Objectives Methods
Semantic proximity in archetypes Results
Mapping archetypes to SNOMED Conclusion
. Creating manual mappings
.
SNOMED concepts are required to study semantic proximity.
Problem: Bindings to SNOMED concepts are very scarce.
We manually created mappings through manual searches.
. This process was very tedious and time-consuming.
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
25. Background Dataset
Objectives Methods
Semantic proximity in archetypes Results
Mapping archetypes to SNOMED Conclusion
. Evaluating the semantic proximity
.
We checked if the concepts mapped to these archetype fragments
are linked through hierarchical and logical relationships of the
SNOMED terminology.
.
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
26. Background Dataset
Objectives Methods
Semantic proximity in archetypes Results
Mapping archetypes to SNOMED Conclusion
. Results
.
A high ratio of archetype terms are semantically related:
30% of Element fragments are subtypes of the Root fragment.
80% of Value fragments are connected through hierarchical
. relationships to any other Value fragment of the archetype
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
27. Background Dataset
Objectives Methods
Semantic proximity in archetypes Results
Mapping archetypes to SNOMED Conclusion
. Conclusion
.
A high ratio of archetype terms are semantically related
ā
The network of SNOMED relationships should
be exploited during the automated mapping of
archetypes.
.
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
28. Background Methods
Objectives Evaluation
Semantic proximity in archetypes Results
Mapping archetypes to SNOMED Discussion
. Outline
.
1 Background
OpenEHR archetypes
SNOMED CT
Related Work
.
2 Objectives
.
3 Semantic proximity in archetypes
Dataset
Methods
Results
Conclusion
.
4 Mapping archetypes to SNOMED
Methods
Evaluation
Results
Discussion
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
29. Background Methods
Objectives Evaluation
Semantic proximity in archetypes Results
Mapping archetypes to SNOMED Discussion
. Automated mapping between archetypes and SNOMED
.
Several mapping techniques were developed to
bind archetype fragments to SNOMED concepts:
Lexical techniques
Linguistic resource-based techniques
Terminological context-based techniques
Structure-based techniques
.
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
30. Background Methods
Objectives Evaluation
Semantic proximity in archetypes Results
Mapping archetypes to SNOMED Discussion
. Lexical techniques
.
Lexical techniques identify SNOMED concepts and
archetype terms with similar names.
Both the archetype terms and SNOMED descriptions are nor-
malized, including plurals, singulars, case-insensitive, etc.
.
Example:
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
31. Background Methods
Objectives Evaluation
Semantic proximity in archetypes Results
Mapping archetypes to SNOMED Discussion
. Linguistic resource-based techniques
.
We used several linguistic resources provided by the UMLS.
These resources use a knowledge-intensive approach based on
symbolic and natural-language processing, to discover biomed-
ical concepts referred in a text.
.
Example:
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
32. Background Methods
Objectives Evaluation
Semantic proximity in archetypes Results
Mapping archetypes to SNOMED Discussion
. Degree of lexical similarity
.
Two degrees of lexical similarity:
Full or exact match occurs when an archetype terms is exactly
the same as some SNOMED CT description after normalization.
Partial match occurs when the archetype term is contained in-
side some SNOMED CT description.
.
Example:
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
33. Background Methods
Objectives Evaluation
Semantic proximity in archetypes Results
Mapping archetypes to SNOMED Discussion
. Mapping algorithm
.
The mapping algorithm consists of three steps:
. Exact Match in entire SNOMED
1
. Partial Match in SNOMED contexts
2
. Structural similarity
3
.
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
34. Background Methods
Objectives Evaluation
Semantic proximity in archetypes Results
Mapping archetypes to SNOMED Discussion
. First step of Mapping: Exact Match in entire SNOMED
.
Lexical and linguistic techniques are used to discover exact or
almost exact correspondeces between all the SNOMED concepts
and archetype fragments
.
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
35. Background Methods
Objectives Evaluation
Semantic proximity in archetypes Results
Mapping archetypes to SNOMED Discussion
. Second step of Mapping: Partial Match in SNOMED contexts
.
SNOMED contexts are extracted from the concepts obtained in
the previous step.
.
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
36. Background Methods
Objectives Evaluation
Semantic proximity in archetypes Results
Mapping archetypes to SNOMED Discussion
. Second step of Mapping: Partial Match in SNOMED contexts
.
Lexical and linguistic techniques are used to discover partial and
approximate correspondeces in the extracted contexts.
.
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
37. Background Methods
Objectives Evaluation
Semantic proximity in archetypes Results
Mapping archetypes to SNOMED Discussion
. Third step of Mapping: Structural similarity
.
Structure-based techniques identify structural similarities between
the tree structure of archetypes and the network of SNOMED rela-
tionships ā Equivalent entities with diļ¬erent names can be mapped
.
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
38. Background Methods
Objectives Evaluation
Semantic proximity in archetypes Results
Mapping archetypes to SNOMED Discussion
. Evaluation
.
Our mapping algorithm was applied to 25 archetypes.
The evaluation entailed the automated revision of each mapping
generated by the method against the manual mappings that we
had created for the study.
.
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
39. Background Methods
Objectives Evaluation
Semantic proximity in archetypes Results
Mapping archetypes to SNOMED Discussion
. Results
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
40. Background Methods
Objectives Evaluation
Semantic proximity in archetypes Results
Mapping archetypes to SNOMED Discussion
. Results: Comparison with other approaches
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
41. Background Methods
Objectives Evaluation
Semantic proximity in archetypes Results
Mapping archetypes to SNOMED Discussion
. Discussion
.
Lessons learned in the work
.
Objetive 1: To understand better how archetype clinical infor-
mation is semantically related.
We now know the frequency and type of semantic
relationships between data fragments of archetypes.
We found that a high ratio of archetype fragments are seman-
tically related.
.
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
42. Background Methods
Objectives Evaluation
Semantic proximity in archetypes Results
Mapping archetypes to SNOMED Discussion
. Discussion
.
Lessons learned in the work
.
Objetive 2: To evaluate whether a combination of context and
structure-based techniques with lexical and linguistic techniques
can improve the automated mapping.
Context and structure-based techniques are able to exploit
SNOMED CT relationships to improve the automated mapping
of archetypes.
.
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
43. Background Methods
Objectives Evaluation
Semantic proximity in archetypes Results
Mapping archetypes to SNOMED Discussion
. Future Work
.
We will test the automatic mapping with diļ¬erent types of
archetypes.
We will explore ways to use medical knowledge from SNOMED:
To facilitate the semi-automatic creation of new archetypes.
To recommend extensions in existing archetypes.
.
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
44. Background Methods
Objectives Evaluation
Semantic proximity in archetypes Results
Mapping archetypes to SNOMED Discussion
. Summary
.
Clinical models, such as archetypes, need to be inte-
grated with terminologies to capture, use and transfer
clinical data in a standard way.
Manual integration is very time-consuming...
.
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
45. Background Methods
Objectives Evaluation
Semantic proximity in archetypes Results
Mapping archetypes to SNOMED Discussion
. Summary
.
We propose a novel automated method to link data
fragments of archetypes with concepts of medical ter-
minologies.
Besides conventional name-based techniques, the
method exploits the medical knowledge represented
in SNOMED to improve the automated mapping and
thus reduce human participation in the process.
.
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o
46. Background Methods
Objectives Evaluation
Semantic proximity in archetypes Results
Mapping archetypes to SNOMED Discussion
. Acknowledgements
Thank you for your attention!
MEC National research project GestiĀ“n de TerminologĀ“ MĀ“dicas
o ıas e
para Arquetipos TIN2009-14159-C05-05
. . . . . .
J.L. Allones, D. Penas, M. Taboada, D. Martinez et al. A Study of Semantic Proximity between Archetype Terms based o