CIMI – SemanticHealthNet Meeting Brussels 2014
Presentation of WP 4:
"Harmonised Resources for
Semantic Interoperability"
Activity domain:
Tangible evidence
Workstream I
Health-directed
requirements,
success criteria,
governance
Workstream II
SDO-harmonised
and tailored
resources, tools
and methods
WP 1
 Patient care exemplar:
chronic heart failure
WP 2
 Public health
exemplar: cardiovascular prevention
WP 4
 Harmonised
resources for
EHRs/PHRs &
aggregation
WP 5
 Infostructure & tools
 Artefact governance,
certification & testing
WP 9
 Project management, dissemination, promotion
Activity domain:
Generalisability & scalability and sustainability
WP 3
 Stakeholder validation
 Additional conditions and
patient populations
 Professional communities
 Clinical governance
 Citizen communities
 Health authorities
 Global public health
WP 6
 Industrial engagement
 Integration into
clinical/public health
information systems
 Industrial exploitation
 Recommendations to
SDOs
Workstream III
Sustainability / Network
co-ordination
WP 7
 Adoption & sustainability
strategies
 Business success factors
 Sustainability models
WP 8
 European Virtual Organisation
 Community building
 Organisational governance
 Liaison with EU initiatives
 Liaison with national bodies
 Education, training
…planned follow up of
SemanticHealthNet
Activity domain:
Tangible evidence
Workstream I
Health-directed
requirements,
success criteria,
governance
Workstream II
SDO-harmonised
and tailored
resources, tools
and methods
WP 1
 Patient care exemplar:
chronic heart failure
WP 2
 Public health
exemplar: cardiovascular prevention
WP 4
 Harmonised
resources for
EHRs/PHRs &
aggregation
WP 5
 Infostructure & tools
 Artefact governance,
certification & testing
WP 9
 Project management, dissemination, promotion
Activity domain:
Generalisability & scalability and sustainability
WP 3
 Stakeholder validation
 Additional conditions and
patient populations
 Professional communities
 Clinical governance
 Citizen communities
 Health authorities
 Global public health
WP 6
 Industrial engagement
 Integration into
clinical/public health
information systems
 Industrial exploitation
 Recommendations to
SDOs
Workstream III
Sustainability / Network
co-ordination
WP 7
 Adoption & sustainability
strategies
 Business success factors
 Sustainability models
WP 8
 European Virtual Organisation
 Community building
 Organisational governance
 Liaison with EU initiatives
 Liaison with national bodies
 Education, training
Workpackage 4
Mission: Provide an
intermediate semantic layer
able to deal with the
unavoidable heterogeneity
which arises when clinical
information is represented
across or within the same
medical domain.
• Leader: Medical University of Graz
• Participants:
- Geneva Univ. Hospital
- INSERM, Paris
- IHTSDO
- WHO
- Ocean Informatics
- EN 13606
- HL7 International
- Eurorec
External experts:
Daniel Karlsson, Rahil Qamar, Ronald
Cornet, Alan Rector, Rong Chen,
Jesualdo Tomás, Diego Boscá,
Mathias Brochhausen, Bill Hogan,
5
Mar Marcos
Basic assumption of WP 4
– Plurality of Information Model approaches exists:
• openEHR, 13606 / SIAMM / HL7 v3 / CIMI, …
• Local schemas are still largely predominant
• Information model like structures in existing terminology systems:
context model of SNOMED CT
• Free text (on purpose out of scope in SHN)
– Plurality of representations within one specification exists
– WP4's relation to information models
• does not develop "yet another" information model
• maintains equidistance and neutrality
• does not contribute to the development of new information models or
model variants
• looks at content and not at structure
– WP4 wants to explore formal approaches to improve
interoperability
15 Mar 2014
6
Role of Ontology and Logic
– Transform existing resources (terminologies,
clinical models) into “semantically enhanced”
ones, using ontology-based formalisms
– Rationales for using formal ontology:
• Possibility to detect equivalences across different
distributions of content between information models
and terminologies using logic-based reasoning
• Advanced exploitation of clinical information by means
of semantic query possibilities
also
• Terminologies like SNOMED CT increasingly using
ontology languages such as OWL
• Fuzziness of terminology / information model boundary
15 Mar 2014
7
Overlap Terminologies / Information Models
Clinical Terminologies
Clinical Information Models
• Clinical Information models to
be used without or with
inexpressive terminologies
• Terminologies to be
used without
information models
• Contextual statements (negation,
plans, beliefs…) within
terminologies
– SNOMED CT context model
– ICD 11 content model
• Local terminology within IMs
• Postcoordination within IMs
Consequence: Plurality of isosemantic expressions
Consequence:
Plurality of isosemantic expressions
It provides some semantics but does
not distinguish between information
and what it represents.
Reference to terminological /
ontological standard is optional
• Information model
representation (no binding)
cancer
confirmed
Consequence:
Plurality of isosemantic expressions
It provides some semantics but does
not distinguish between information
and what it represents.
Reference to terminological /
ontological standard is optional
Everything packaged in one code
No separate information model needed
• Terminology representation
• Information model
395099008 |cancer confirmed|
representation (no binding)
cancer
confirmed
Consequence:
Plurality of isosemantic expressions
It provides some semantics but does
not distinguish between information
and what it represents.
Reference to terminological /
ontological standard is optional
Everything packaged in one code
No separate information model needed
• Terminology representation
• Information model
395099008 |cancer confirmed|
representation (no binding)
NO SEMANTIC
INTEROPERABILITY
cancer
confirmed
• Information model / Terminology representation
Cancer
Terminology expression
cancer
confirmed
15 Mar 2014
12
Ontologies – chances and difficulties
• Our hypothesis: ontologies can act as a “semantic glue” to
create an unambiguous representation by relating
information model entities and clinical terminologies
• Ontologies will help us to distinguish between:
– Clinical entities “what does Heart Failure exactly mean?”
– Information entities “what is documented about a specific heart failure
instance?”
– Epistemic entities “how sure am I whether it is heart failure?”
– Clinical process entities “what is done to acquire the knowledge I need?”
• Known limitations
– expressiveness limited if computable (subset FOL)
– the difficulty of "thinking ontologically"
15 Mar 2014
13
Ontologies re-used and created in SemanticHealthNet
Information
Artifacts
Clinical
Processes
"Clinical
entities"
(findings,
disorders,
procedures,
substances,
organisms...)
Ontologies re-used and created in SemanticHealthNet
Information
Artifacts
Clinical
Processes
SNOMED CT
Domain
Ontology
"Clinical
entities"
(findings,
disorders,
procedures,
substances,
organisms...)
Ontologies re-used and created in SemanticHealthNet
Toplevel Categories
Information
Artifacts
Clinical
Processes
Basic relations
Constraining axioms
SNOMED CT
Domain
Ontology
"Clinical
entities"
(findings,
disorders,
procedures,
substances,
organisms...)
BioTopLite
Upper Level
Ontology
Constraining axioms
existence can be taken for granted
existence of concrete instances
in a real patient may be
hypothetic
Information
Artifacts
Clinical
Processes
"Clinical
entities"
(findings,
disorders,
procedures,
substances,
organisms...)
?
? ?
?
Basic representational pattern for terminology binding
Demographics
Time stamps
Metadata
• Example: Diagnosis (statement
about clinical situation)
Patient X
annotation of an information item
"this is an information entity of a certain type (e.g. diagnostic statement)
which has an attribute (e.g. "suspected") , which is created by a health
professional at a given time and is about some type of clinical entity
(e.g. neoplasia)…"
EHR
WHAT?
WHO?
WHEN?
Neoplasia
Example:
“Suspected heart failure caused by ischaemic heart disease”
 One code or postcoordinated expression in SNOMED CT
 Reference to two kinds of disorders
(ontological types / concepts)
 Semantic relation between both
 Epistemic context: represents state of knowledge about a
clinical situation
 Not clear whether there is really some heart failure at all!
• Many entries in EHRs must not be interpreted as factual statements
• Blending of ontological and epistemic information in one code
characteristic for many clinical terminologies
“Suspected heart failure caused by ischaemic heart disease”
• Three heterogeneous representations of the same statement
• Three different atomic information entities
Organ Failure Diagnosis
Organ
Heart
Status
Suspected
Caused by
ischaemic
heart disease
Yes
No
Unknown
Diagnosis
Suspected heart failure caused
by ischaemic heart disease
Diagnosis
Heart Failure
Status
x
Suspected
Cause
Ischaemic heart
disease
20
“Suspected heart failure caused by ischaemic heart disease”
Annotation 1
is a diagnosis
about organ
failure
is a
diagnosis
about heart
failure
Organ Failure Diagnosis
Organ
Heart
Status
Suspected
Caused by
ischaemic
heart disease
Yes
No
Unknown
x
is a suspected
organ failure
diagnosis
is a organ failure diagnosis
about a disorder caused by
ischaemic heart disease
21
“Suspected heart failure caused by ischaemic heart disease”
Annotation 1
is a diagnosis
about organ
failure
is a
diagnosis
about heart
failure
Organ Failure Diagnosis
Organ
Heart
Status
Suspected
Caused by
ischaemic
heart disease
Yes
No
Unknown
x
is a suspected
organ failure
diagnosis
is a organ failure diagnosis
about a disorder caused by
ischaemic heart disease
22
“Suspected heart failure caused by ischaemic heart disease”
Annotation 2
is a diagnosis
Diagnosis
Suspected heart failure caused
by ischaemic heart disease
is a suspected diagnosis
about heart failure
caused by ischaemic
heart disease
23
“Suspected heart failure caused by ischaemic heart disease”
Annotation 3
is a diagnosis
about heart
failure
is a diagnosis
Diagnosis
Heart Failure
Status
Suspected
Cause
Ischaemic heart
disease
is a diagnosis
about sth caused
by ischaemic
heart disease
24
is a
suspected
diagnosis
One diagnosis instance for each model
Organ Failure Diagnosis
Organ
Heart
Status
Suspected
Caused by
ischaemic
heart disease
Yes
No
Unknown
Diagnosis
Suspected heart failure caused
by ischaemic heart disease
Diagnosis
Heart Failure
Status
x
Suspected
Cause
Ischaemic heart
disease
25
Query 1
All three information instances found
26
Query 2
All three information instances found
27
How do we apply that?
SEMANTIC
PATTERNS
compliant with
SHN
Ontology
Framework
Use cases: heart
failure and
cardivascular
health
28
How do we apply that?
CIMI
SEMANTIC
PATTERNS
compliant with
SHN
Ontology
Framework
Use cases: heart
failure and
cardivascular
health
29