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Knowledge Representation in Practice: SNOMED CT
Kent A. Spackman, MD, PhD
Chief Terminologist, IHTSDO
Clinical Professor, Oregon Health & Science University, Portland Oregon USA
KR-MED 2008 TutorialPhoenix – May 31, 2008
Tutorial 2nd Half Topics
• Description logic basics• Concept model domains, ranges and attributes• Application of additional description logic features to
special requirements: – Right identities: partonomies (SEP)– Role groups: complex procedures, disorders, situations– Role hierarchies: direct and indirect objects; causal and associational relationships
• Composition and syntax– normal forms– SNOMED compositional syntax, KRSS, and OWL
• Current redesign efforts – substances, observables, anatomy, events, conditions, organisms
• The context model & negation• The terminology / information model interface
2
DESCRIPTION LOGIC BASICS
3
What is description logic?
• Mathematical viewpoint:– A family of logics characterized by
• Formal set-theoretic semantics• Proofs of correctness and completeness of computation• Proofs of algorithmic complexity (PSpace, NP-complete,
NExpTime, etc)
• Knowledge representation viewpoint:– A set of constructs for representing terminological
knowledge (that which is always true of a meaning)– Algorithms and their implementations for performing:
• Subsumption (testing pairs of expressions to see whether one is a subtype of the other & vice versa)
• Classification (structuring a set of expressions according to their subsumption relationships)
4
Constructs for a very simple DL: EL
Name of construct Notation Semantics Primitive concept name A AI⊆∆I Primitive role name R RI⊆∆I×∆I Top (everything) > ∆I Conjunction (AND) CuD CI∩DI Exists restriction ∃R.C {x|∃y.RI(x,y)∧CI(y)}Concept definition (sufficient) A≡C AI=CI Primitive concept introduction AvC AI⊆CI
5
Reading DL expressions
u is the symbol for Boolean conjunction
– Short name: “and”– Operands are placed on either side: C u D– Both operands C and D must be true in order for the expression to be
true
∃ is the symbol for existential restriction
– Short name: “some”– Operands follow the backwards E symbol: ∃R·C
• R represents a “role” or relationship• C represents the value or target of the relationship
– Requires that there be an instance of relationship named R to someinstance of the class named C in order for the expression to be true
6
The logic of green frogs
How could you use EL to define a green frog?
First, some concept names (A in the EL notation table):FrogGreenGreenFrog
Then a role name (R in the EL notation table):hasColor
Now introduce a definition of GreenFrog, using Frog, Green, and hasColor, along with C u D and ∃R·C as follows:
GreenFrog ≡ Frog u ∃ hasColor.Green
7
The logic of green frogs
How do we read these expressions?
Usual DL syntaxGreenFrog ≡ Frog u ∃ hasColor.Green
KRSS syntax:(defconcept GreenFrog (and Frog (some hasColor Green)))
Every instance of the class named GreenFrogis an instance of the class named Frog which alsohas a “hasColor” relationship to an instance of the class named “Green”
And, every instance of the class named Frog which alsohas a “hasColor” relationship to an instance of the class named “Green”is an instance of the class named GreenFrog.
8
The logic of green frogs
Right hand side only:
Usual DL syntaxFrog u ∃ hasColor.Green
KRSS syntax:(and Frog (some hasColor Green))
SNOMED compositional syntax:Frog: hasColor = Green
an instance of the class named Frog which alsohas a “hasColor” relationship to an instance of the class named “Green”
Exercise for the reader: how do you represent frogs that arecompletely green?
9
A SNOMED example
• Headache is-a ache: finding-site = head structure – (and headache is marked as “defined” in concepts table).
• The class “headache” is sufficiently defined as the set of instances of the class “ache” which also have at least one finding-site relationship to an instance of the class “head structure”.
• And all instances of class “ache” with some finding-site relationship to an instance of “head structure” are instances of “headache”.
• Now, is that what you mean when you say “headache”?
10
EXPRESSIONS & COMPOSITION
11
SNOMED CT Expressions
• SNOMED CT coded information consists of structured (composed) collections of concept codes– These are called expressions– The meaning of an expression depends on the situation in which it is used
Example• The SNOMED CT code for “fracture of femur” represents the meaning
of “a break in a femur”– Depending on where it is used in a patient record, the code may mean
• The patient has a fractured femur• The patient’s main diagnosis is a fracture of the femur• The patient has a past history of fractured femur• The patient is suspected of having a fractured femur …. etc
– In a query it may be one of several criteria for retrieving the records of patients with particular types of injury
– In an index to the clinical literature it might indicate a paper that is relevant to this condition
12
Expressions can be pre-coordinated or post-coordinated
• Pre-coordinated expression– Terminology producer provides a single ConceptId for the
meaning• 31978002
– means “fracture of tibia”
• Post-coordinated expression– A user composes a combination of ConceptIds to represent
the meaning• 31978002 : 272741003 = 7771000
– (fracture of tibia : laterality = left)– In human readable form … “fracture of left tibia”
13
• Refinement
– Replacing value C with a more specific value C1 within an existing (defining) ∃R·C relationship in the definition, giving ∃R·C1
– Example• Fracture of femur
– Defined as: finding-site = bone structure of femur– May be refined to: finding-site = structure of neck of femur
• Yielding the new meaning: Fracture of neck of femur
Refinement and qualification:Two common ways to derive post-coordinated expressions
14
• Qualification (also called “subtype qualification”)
– Replacing value C with a more specific value C1 within a qualifier ∃R·C relationship (found in the qualifying relationships in the relationships table), giving ∃R·C1
– Example
• Bronchitis– Qualifier exists as: clinical-course = courses (any course value)– May be qualified to: clinical-course = acute (sudden onset
AND/OR short duration)• Yields the meaning: Acute bronchitis
• End results of refinement or qualification are post-coordinated expressions with an identical logical structure
Refinement and qualification:Two common ways to derive post-coordinated expressions
15
Compositional grammar (1)
• Simplest expression is a single conceptid– For example
• 71620000
• Optionally conceptId may be followed by a term enclosed in pipe delimiters– For example
• 71620000|fracture of femur|
• Concepts can be combined with a plus sign that means logical “and” (conjunction)– For example
• 31978002|fracture of tibia| +75591007|fracture of fibula|
16
Compositional grammar (2)
• Refinements can be added after a colonFor example
125605004: 363698007=29627003• Refinements can be nested in parentheses
For example53057004|hand pain|:
363698007|finding site| =(76505004|thumb structure|:272741003|laterality| =7771000|left|)
• Refinements can be grouped in bracesFor example71388002|procedure|:
{260686004|method| =129304002|excision - action|,363704007|procedure site| =66754008|appendix structure|}
Note: the comma also means logical “and” in this expression
17
Severe pain, left thumb
Pain
Finding site
Severity
Thumb structure
Severe
Laterality Left
22253000|pain|:363698007|finding site|=
(76505004|thumb structure|:272741003|laterality|=7771000|left|),
246112005|severity|=24484000|severe|
18
Severe pain, left thumb
Hand Pain
Finding site
Severity
Thumb structure
Severe
Laterality Left
53057004|hand pain|:363698007|finding site|=
(76505004|thumb structure|:272741003|laterality|=7771000|left|),
246112005|severity|=24484000|severe|
19
Subtype relationships
• Every concept is a refined type of one or more other concepts
• For example– “Pain in the leg” is a type of “pain”– “Pain in the leg” is a type of “lower limb
finding”• SNOMED CT represents these defining
relationships with the relationship type called “is a”
20
Subtype relationships
PainLower limb finding
Pain in lower limb
Pain in calf
A pain in the calf is-a pain the lower limb, andPain in the lower limb is-a pain, and is-a lower limb finding
21
Subtype relationships
Infectious diseaseLung disease
Infectious pneumonia
Bacterial pneumonia
Bacterial pneumonia is-a infectious pneumonia, andInfectious pneumonia is-a lung disease, and is-a Infectious disease
22
Why have subtype relationships?
• Because when you selectively retrieve information you usually want to include subtypes
• For example– When searching for “Deep Venous Thrombosis”
you would usually want to retrieve all kinds of DVT including …
• DVT of specific sites (e.g. lower limb)• DVT with particular causes (e.g. air travel related DVT)
… and others
23
Leaf
Root
Deep vein thrombosis of leg related to air travel
Deep venous thrombosis of lower extremity
Deep venous thrombosis
Venous thrombosis
Thrombotic disorder
Vascular disease
Disorder of cardiovascular system
Disorder of body system
Disorder by body site
Finding by site
Clinical finding
Disorder
Disease of vein
Thrombosis of vein of lower limb
Vascular disorder of lower extremity
Disorder of lower extremity
Finding of lower limb
Finding of limb structure
Finding of body region
Disorder of extremity
Peripheral vascular disease
DVT leg assoc w air travel
Subtype hierarchyLooking from leaf to root
24
Other defining relationships
• The difference between two concepts may be represented by other defining relationships– Only relationships that are necessarily
true are defining relationships• For example
– “Pain in calf” has “finding site” “calf structure”
25
Other defining relationships
PainLower limb finding
Pain in lower limb
Pain in calf
A pain in the calf has finding site calfPain in the lower limb has finding site lower limb
lower limbstructure
Calf structure
26
Other defining relationships
Lung diseaseBacterial disease
Bacterial pneumonia
RLL bacterialpneumonia
Bacterial pneumonia has finding site lung structureRLL bacterial pneumonia has finding site RLL structure
Lung structure
RLL structure
27
Why have other defining relationships?
• Other defining relationships– Confirm and enhance the accuracy of the subtype
hierarchy• For example, all “pain” findings with a “finding site” of
“lower limb” (or a subtype of lower limb structure) must be subtypes of “lower limb pain”
– Enable concepts to be refined by increasing the specificity of a defined relationship• For example, a “pain in the foot” could be refined to
specify a more precise “finding site” such as the “third toe of the left foot”, even if SNOMED CT did not include a specific concept for pain in a such a specific location.
– Allow recognition of equivalence between different ways of expressing the same concept
28
Primitive & sufficiently-defined concepts
• A concept is “sufficiently defined” – if its definition is sufficient to
distinguish it from all its supertype concepts
• A concept is “primitive” – if it is not “sufficiently defined”
29
Primitive & sufficiently defined concepts
• Head injury– Is a = Disease– Associated morphology = Traumatic abnormality– Finding site = Head structure– Sufficiently Defined
• Aching pain– Is a = Pain– Primitive
• Headache– Is a = Aching pain– Finding site = Head structure– Sufficiently Defined
30
The value of sufficiently defining concepts
• Allows auto-classification– Consistent hierarchy and definition
• Allows computation of equivalence and subsumption between– Different ways of expressing the same meaning
• E.g. “open fracture of left femur”
or– “fracture of bone”
site=“femur”: laterality=“left”morphology=“open fracture”
31
Different views of relationships
• Stated view– The view that SNOMED CT modelers edit– Includes only the defining relationships that an
author has explicitly stated to be true– (soon will be distributed in KRSS and/or OWL
syntax)• Inferred view
– The view distributed in the distribution file– Generated by auto-classification– Includes relationships inferred from the stated view– Excludes redundant relationships
• Normalized view– The view best suited to comparing expressions– Reduces all values to their proximal primitive
subtypes
32
Auto-classification
• Many relationships are inferred by auto-classification rather than authored directly
• Auto-classification– Takes definitions “stated” by SNOMED authors and uses
them to “infer” other relationships– Removes redundant (less specific) defining relationships– Creates a logically consistent parsimonious set of
relationships• Review the results of classification
– Although logically consistent … it may not be “correct” due to errors in “stated” definitions
– Human errors that might otherwise be overlooked are often highlighted by auto-classification
– Auto-classification is repeated frequently during authoring and the results are then rechecked
33
An example of a stated view
pain
pain in lower limb
pain in calf
lower limb structure
calf structure
is a
is a
is a
The diagram is a “directed acyclic graph”, or DAG, of the is-a relationships
34
Auto-classification can addinferred relationships to the stated view
pain
pain in lower limb
pain in calf
lower limb structure
calf structure
Inferredfrom other relationships is a
is a
is a
is a
35
For the distributed inferred view less specific subtype relationships are removed
pain
pain in lower limb
pain in calf
lower limb structure
calf structure
Redundant after adding inferred
relationship
is a
is a
is a
is a
In computer science terms this structure is called the “transitive reduction”i.e. the distributed is-a relationships are the transitive reduction of the DAG
36
In another view all the possible subtype relationships are stated directly
• This is “transitive closure” view is useful for optimization
• It can be computed from distributed data
• SNOMED is likely to release this view later this year
pain
pain in lower limb
pain in calf
is a
is a
is a
finding
is ais a
is a
Description Logic Classifiers
• Various DL Classifiers exist• SNOMED uses the Apelon TDE classifier
– It has some limitations but performs well on a large database
• Some other classifiers testing in past failed or became very slow with so many concepts
• Others include– FaCT++ (Fast Classifier of Terminologies)– Pellet– CEL– RacerPro
38
Definition of Normal Forms
• In original RT work, dual independent modeling required exact agreement on stated definition– Resulted in unresolved arguments about modeling style
• State most immediate parent concepts only, and only those relationships that have changed, or
• State proximal primitives only, and all defining relationships
• Defining a normal form allowed different modeling styles for different purposes or preferences
39
Spackman KA. Normal forms for description logic expression of clinical concepts in SNOMED RT. Proceedings/AMIA Annual Symposium. :627-631, 2001.
Illustration of need for normal form:basal cell carcinoma (BCC) of skin of eyelid
• Multiple different ways to post-coordinate:– Disorder, M=BCC, T=skin of eyelid– Malignant disorder, M=BCC, T=skin of eyelid– Skin disorder, M=BCC, T=skin of eyelid– Disorder of skin of eyelid, M=BCC– Malignant neoplastic disorder of skin eyelid,
M=BCC– Basal cell carcinoma (disorder), T=skin of
eyelid– ...
40
D Disorder
D4Neoplastic disorder of skin
D1Neoplasticdisorder
D3Malignant neoplasm
D2 Disorder of skin
D5 Disorder of skin of eyelid
D7Malignant neoplasm of skin D8 Neoplastic disorder
of skin of eyelidD6 Basal cell
malignancy
D10 Malignant neoplasmof skin of eyelid
D11 Basal cell carcinomaof skin of eyelid
D9Basal cell carcinoma of skin
41
D Disorder
D4Neoplastic disorder of skin
D1Neoplasticdisorder
D3Malignant neoplasm
D2 Disorder of skin
D5 Disorder of skin of eyelid
D7Malignant neoplasm of skin D8 Neoplastic disorder
of skin of eyelidD6 Basal cell
malignancy
D10 Malignant neoplasmof skin of eyelid
D11 Basal cell carcinomaof skin of eyelid
D9Basal cell carcinoma of skin
NeoplasticMorphology
MalignantMorphology
BCCMorphology
M3
M2
M1T1
T2
Skin structure
Skin structure of eyelid
42
D Disorder
D4Neoplastic disorder of skin
D1Neoplasticdisorder
D3Malignant neoplasm
D2 Disorder of skin
D5 Disorder of skin of eyelid
D7Malignant neoplasm of skin D8 Neoplastic disorder
of skin of eyelidD6 Basal cell
malignancy
D10 Malignant neoplasmof skin of eyelid
D11 Basal cell carcinomaof skin of eyelid
D9Basal cell carcinoma of skin
NeoplasticMorphology
MalignantMorphology
BCCMorphology
M3
M2
M1T1
T2
Skin structure
Skin structure of eyelid
43
D Disorder
D4Neoplastic disorder of skin
D1Neoplasticdisorder
D3Malignant neoplasm
D2 Disorder of skin
D5 Disorder of skin of eyelid
D7Malignant neoplasm of skin D8 Neoplastic disorder
of skin of eyelidD6 Basal cell
carcinoma
D10 Malignant neoplasmof skin of eyelid
D11Basal cell carcinomaof skin of eyelid
D9Basal cell carcinoma of skin
NeoplasticMorphology
MalignantMorphology
BCCMorphology
M3
M2
M1T1
T2
Skin structure
Skin structure of eyelid
44
D Disorder
D4Neoplastic disorder of skin
D1Neoplasticdisorder
D3Malignant neoplasm
D2 Disorder of skin
D5 Disorder of skin of eyelid
D7Malignant neoplasm of skin D8 Neoplastic disorder
of skin of eyelidD6 Basal cell
malignancy
D10 Malignant neoplasmof skin of eyelid
D11 Basal cell carcinomaof skin of eyelid
D9Basal cell carcinoma of skin
NeoplasticMorphology
MalignantMorphology
BCCMorphology
M3
M2
M1T1
T2
Skin structure
Skin structure of eyelid
Note that D1 through D11 are all sufficiently defined (non-primitive)45
D Disorder
D4Neoplastic disorder of skin
D1Neoplasticdisorder
D3Malignant neoplasm
D2 Disorder of skin
D5 Disorder of skin of eyelid
D7Malignant neoplasm of skin D8 Neoplastic disorder
of skin of eyelidD6 Basal cell
malignancy
D10 Malignant neoplasmof skin of eyelid
D11 Basal cell carcinomaof skin of eyelid
D9Basal cell carcinoma of skin
NeoplasticMorphology
MalignantMorphology
BCCMorphology
M3
M2
M1T1
T2
Skin structure
Skin structure of eyelid
Attributes and values are all inheriteddownwards (redundant ones are removed)
M=M1
M=M2
M=M3
T=T1
T=T2M=M1T=T1
M=M1T=T2
M=M2T=T1
M=M2T=T2
M=M3T=T1
M=M3 T=T246
D Disorder
D4Neoplastic disorder of skin
D1Neoplasticdisorder
D3Malignant neoplasm
D2 Disorder of skin
D5 Disorder of skin of eyelid
D7Malignant neoplasm of skin D8 Neoplastic disorder
of skin of eyelidD6 Basal cell
malignancy
D10Malignant neoplasmof skin of eyelid
D11 Basal cell carcinomaof skin of eyelid
D9Basal cell carcinoma of skin
NeoplasticMorphology
MalignantMorphology
BCCMorphology
M3
M2
M1T1
T2
Skin structure
Skin structure of eyelid
Some valid forms for D11:
D9 and T=T2
D10 and M=M3
D6 and D547
D Disorder
D4Neoplastic disorder of skin
D1Neoplasticdisorder
D3Malignant neoplasm
D2 Disorder of skin
D5 Disorder of skin of eyelid
D7Malignant neoplasm of skin D8 Neoplastic disorder
of skin of eyelidD6 Basal cell
malignancy
D10Malignant neoplasmof skin of eyelid
D11 Basal cell carcinomaof skin of eyelid
D9Basal cell carcinoma of skin
NeoplasticMorphology
MalignantMorphology
BCCMorphology
M3
M2
M1T1
T2
Skin structure
Skin structure of eyelid
Some valid forms for D11:
D9 and T=T2
D10 and M=M3
D6 and D548
D Disorder
D4Neoplastic disorder of skin
D1Neoplasticdisorder
D3Malignant neoplasm
D2 Disorder of skin
D5 Disorder of skin of eyelid
D7Malignant neoplasm of skin D8 Neoplastic disorder
of skin of eyelidD6 Basal cell
malignancy
D10Malignant neoplasmof skin of eyelid
D11 Basal cell carcinomaof skin of eyelid
D9Basal cell carcinoma of skin
NeoplasticMorphology
MalignantMorphology
BCCMorphology
M3
M2
M1T1
T2
Skin structure
Skin structure of eyelid
Some valid forms for D11:
D9 and T=T2
D10 and M=M3
D6 and D549
Summary of BCC example:
• Because of the many different valid forms, it is useful to define a “normal form” to which we can transform all expressions for comparison
• In this case, the normal form combines the proximate primitive (disorder) with the non-redundant existential restrictions
disorder :finding-site = skin of eyelid (body structure),associated-morphology = basal cell carcinoma (morphologic abnormality)
50
CONCEPT MODEL
51
Procedure site
Direct morphology
Direct substance
Procedure device
Indirect device
Using device
Anatomical structure, Acquired body structure
Substance, Pharmaceutical / biologic product
Procedure concept model (1)
Indirect morphology
Procedure Morphology
Morphologically abnormal structure
Direct deviceDevice
Method Action
Procedure
Procedure site - direct
Procedure site - indirect
Using access device Endoscope and subtypes
52
Procedure site
Direct morphology
Direct substance
Procedure device
Indirect device
Using device
Anatomical structure, Acquired body structure
Substance, Pharmaceutical / biologic product
Procedure concept model (1)
Indirect morphology
Procedure Morphology
Morphologically abnormal structure
Direct deviceDevice
Method Action
Procedure
Procedure site - direct
Procedure site - indirect
Using access device Endoscope and subtypes
DirectObject
53
Has intent
Recipient category
Revision status
Procedural approaches
Priorities
Clinical findings, Procedures
Intents
Person, Family, Community, Donor, Group
Revision-value, Part of multistage procedure, Primary operation
Surgical Approach
Priority
Has focus
Procedure concept model (2)
Route of administration Route of administration value
Physical forcesUsing energy
Substances
Procedure
Using substance
Access Open, closed, percutaneous(surgical access values)
54
Attributes Procedures (1)
• Method– The action being performed to accomplish the procedure
• Does not include access (e.g., percutaneous) or approach (e.g., translumbar)– Values are subtypes of “action”
• Procedure site• Values are subtypes of “anatomical concept”
– Procedure site – direct• The site directly affected by the action
– Procedure site – indirect• A site that is acted on but is not the direct target of the action
appendectomy
Gmethod excision - action
procedure site - direct appendix structure55
Attributes Procedures (2)
• Morphology• Values are subtypes of “morphologically abnormal structure”
– Direct morphology• The morphology to which the procedure is directed
– Indirect morphology• A morphology that is acted upon, but is not the direct target of
the action being performed
Evacuation of intracerebral hematoma
Gmethod evacuation - action
procedure site - indirect cerebral structuredirect morphology hematoma
56
Attributes Procedures (3)
• Device• Values are subtypes of “device”
– Direct device• The device to which the procedure is directed.
– Indirect device• A device that is acted upon, but which is not the direct
target of the action being performed
Replacement of electronic heart device battery
direct device pacemaker battery
indirect device cardiac pacemaker
57
Attributes Procedures (4)
• Using device– Specifies the instrument utilized to perform the procedure– Value are subtypes of “device”
core needle biopsy of larynx
Using device core biopsy needle
Using access device
– Specifies the instrument utilized to gain access to the site– Value are subtypes of “endoscope”
Endoscopic biopsyUsing access device endoscope
58
Attributes Procedures (5)
• Using energy– Specifies the energy utilized to perform the procedure– Value are subtypes of “physical force”
gamma ray therapy
Using energy gamma radiation
59
Attributes Procedures (6)
• Access– Used to distinguish open, closed, endoscopic, and percutaneous
procedures• Only used if access is specified in the name of the concept
– Values are subtypes of “surgical access values”
transurethral laser prostatectomySurgical approach transurethral approach
open reduction of fracture
access open approach
Surgical Approach– Specifies the directional, relational or spatial access to the
site of a surgical procedure. – Values are subtypes of “surgical approach”
60
Measurement procedure concept model
Component
Measurement method
Time Aspect
Scale Type
Cell structure, organism, substance, observable
Laboratory procedure categorized by method
Time frame
Property Property of measurement
Nominal, narrative, ordinal,Quantitative, qualitative, Text, ordinal OR quantitative
Has Specimen Specimen
MeasurementProcedure
61
Attributes Measurement procedures
• Has specimen– Specifies the type of specimen on which a measurement or
observation is performed– Values are subtypes of “specimen”
• Component– Specifies the substance or observable being observed or
measured by a procedure– Values are subtypes of “substance”, “observable entity”, or “cell
structure”
creatinine measurement, 24 hour urinehas specimen 24 hour urine sample
component creatinine
62
Clinical finding concept model (1)
Finding site
Causative agent
Associated morphology
Interprets
Acquired body structure, Anatomical concepts
Organism, Substance, Physical object, Physical force
Morphologically abnormal structure
Laboratory procedure, Observable entity, Patient evaluation procedure
Due to
After Clinical finding, Procedure
Clinical finding, Event
Has interpretation Findings values, Result comments
Associated withClinical finding, Substance, Physical object, Physical force, Events, Organisms, Pharmacological / Biological product, Procedure
Clinical finding
63
Clinical finding concept model (2)
Has definitional manifestation
Occurrence
Pathological process
Clinical finding
Periods of life
Clinical Course
Episodicity
Courses
First episode, New episode, Ongoing episode
Severity
Finding method
Pathological process
Mild, Moderate, SevereClinical finding
Finding informer
Procedure
Performer of method, Subject of recordProvider of history other than subject,Subject of record or other provider of history
64
Attributes Clinical Findings (1)
• Associated morphology– Specifies morphologic change seen at tissue or cellular level as
a characteristic feature or the disease– Values are subtypes of “morphologically abnormal structure”
• Finding site– Specifies the body site affected by a condition– Values are subtypes of “anatomical concept”
open fracture of femur
associated morphology fracture, open
finding site bone structure of femur
65
Attributes Clinical Findings (2)
• Causative agent– Specifies the direct causative agent of the disease
• Does not include vectors (e.g. not mosquito for malaria)
– Values are subtypes of “organisms”, “substances”, “physical objects” or “physical forces”
bacterial pneumonia
causative agent bacteria
66
Attributes Clinical Findings (3)
• Due to– Used when one finding/disorder is a cause of another finding, disorder
or procedure. Differs from Causative agent in that the cause is not an Organism, Substance, Physical Object, or Physical agent
– Values are subtypes of “clinical findings”
post-viral disorderafter viral disease
• After– Specifies a temporal relationship between a Finding/Disorder and a
Finding, Disorder, or Procedure when there is not necessarily a causal relationship
– Values are subtypes of “clinical findings” or “procedures”
diabetic retinopathy
due to diabetes mellitus
67
Attributes Clinical Findings (4)
acute myocardial infarctionClinical course acute
Clinical Course– Specifies the course of a condition. – Used for acute and chronic conditions. – Not used to refer to rapidity of onset or severity of a
condition. – Values are subtypes of “courses”
68
Attributes Clinical Findings (5)
• Episodicity– Specifies the particular episode of a finding that may recur– If an episode is not the initial episode and is not an ongoing
episode, it is considered a new episode– Values are “first episode”, “new episode” & “ongoing episode”
• Severity– Specifies the level of severity for a Disease concept. – Values are “mild”, “moderate”, and “severe”
severe vertigo
severity severe
new onset angina
episodicity new episode
69
Attributes Clinical Findings (6)
• Interprets– Specifies the “observable entity” or “function” being evaluated or
interpreted by a finding.– Values are subtypes of “observable entity”, “biological function” or
“measurement procedure”• Has interpretation
– Specifies the judgement being made about an observable or function (e.g., presence, absence, degree, normality, etc.)
– Values are subtypes of “findings values” or “result comments”
decreased cardiac output
has interpretation decreasedinterprets cardiac output
70
Associated procedure Procedure
Procedure contextContext values for actions• Done, not done• Planned, requested
Associated findingClinical finding; or Observable / Observation with result
Finding context
Finding context value• Present, absent, possible• Unknown• Goal, risk, etc
Situation concept model
Situation with explicit context
Subject relationship contextSubject relationship value• Subject of record• Family member, etc
Temporal context Temporal context value• Current• Past, etc
71
Specimen concept model
Specimen Specimen source morphology Morphology
Specimen substance
Specimen source identity Person, Family, Donor, Device, Environment, Community
Substance
Specimen source topography
Specimen procedure
Body structure
Procedure
72
Pharmaceutical/Biologic Product concept model
Has dose form
Pharmaceutical / Biologic product Type of drug preparation (product)
Has active ingredient Substance (substance)
73
Body structure concept model
Left, Right, Right and left, (unilateral)Body structure Laterality
Part-of Body structure
Note: use of “unilateral” implies one side and not the other.This is a type of negation, and therefore unilateral procedures and unilateral findingsactually must be in the situation hierarchy.
74
RIGHT IDENTITIES
75
Right identity(restricted role value maps)
• R ° S ⊑ R
• x Ry y Sz → x Rz
• R is causative agent• S is has active ingredient
• allergyToAspirin v ∃ causativeAgent.aspirinSubstance• aspirinProduct v ∃ hasActiveIngredient.aspirinSubstance• allergyToAspirinProduct v ∃ causativeAgent.aspirinProduct
• Allows the automated inference that:
– allergyToAspirinProduct v allergyToAspirin
76
Right identity(restricted role value maps)
• R ° S ⊑ R
• x Ry y Sz → x Rz
• R is finding-site• S is part-of
• femurFracture v ∃ site.femur• headOfFemurFracture v ∃ site.headOfFemur• headOfFemur v ∃ part-of.Femur
• Allows the automated inference that:– headOfFemurFracture v FemurFracture
• But this isn’t the purpose for which we use right identity in the current release !
77
Avoiding Right Identities by Using SEP Triplets
Liver Structure
Entire liverLiver Part
XM0Ps Liver structureT-62000 Liver
T-D0535 Liver part 7N330 Liver
Lobe of liver
78
ROLE GROUPS
79
Role Groups
• Certain defining relationships may be grouped to indicate the way they relate to each other
• For example:– Laparoscopy inspects the peritoneal cavity– Appendicectomy excises the appendix– Laparoscopic appendicectomy
• inspects the peritoneal cavityand• excises the appendixbut does not• Excise the peritoneal cavity
– Grouping action and site avoids misinterpretation
80
Role groups
• Another example
Method: ExcisionProcedure site: Gallbladder
Method: ExplorationProcedure site: Bile duct
Cholecystectomy and exploration of bile duct
Role group 1
Role group 2
81
Role Grouping as a Compromise
• Implementers and modelers fear/loathe nesting of expressions– Nesting violates simple flat frame-based model
• Reality demands faithful representation
• Role grouping attempted (with partial success) to hide the complexity– But it was misunderstood by some in DL community as
being a proprietary hack
82
Spackman KA, Dionne R, Mays E, Weis J. Role grouping as an extension to the description logic of Ontylog motivated by concept modeling in SNOMED. Proceedings/AMIA Annual Symposium. :712-716, 2002.
Need for Role Groups
• When a single concept may have more than one value for a particular attribute– for example, “bone fusion with tendon transfer”
• method = fusion, site = bone, and• method = transfer, site = tendon
• And, one attribute-value pair needs to be associated with another.– How can we specify that the fusion is done to the bone and
not to the tendon? and that the transfer is done to the tendon and not to the bone?
83
Role Groups as a Solution
• Informally: – don’t nest or create sub procedures– simply “group” the attribute-value pairs
• Using curly braces as a syntactic marker:{ site=bone, method=fusion}, {site=tendon, method=transfer}
• Or, in tabular form, use a “group” column:attr value groupsite bone 1method fusion 1site tendon 2method transfer 2
84
Role Grouping Logical Form: A Nested Existential Restriction
• C ⊑ ∃ RRG .(∃R1.C1 ⊓ ∃R2.C2) ⊓ ∃ RRG .(∃R3.C3 )
• Distributed as three 4-tuples in relationships table:C R3 C3 0
C R1 C1 1
C R2 C2 1
– Role group numbers are arbitrary integers, and not designed to be stable across changes in the concept definition
85
ROLE HIERARCHIES
86
Role (attribute) hierarchies
• Selected SNOMED CT attributes have a hierarchical relationship to one another known as “role hierarchies.” In a role hierarchy, one general attribute is the parent of one or more specific subtypes of that attribute. Concepts defined using the more general attribute can inherit concepts modeled with the more specific subtypes of that attribute.
87
Role hierarchies – procedures
• PROCEDURE DEVICE – DIRECT DEVICE – INDIRECT DEVICE – USING DEVICE – USING ACCESS DEVICE
• PROCEDURE MORPHOLOGY – DIRECT MORPHOLOGY – INDIRECT MORPHOLOGY
• PROCEDURE SITE – PROCEDURE SITE - DIRECT – PROCEDURE SITE - INDIRECT
88
Role hierarchies – clinical findings
• ASSOCIATED WITH role hierarchy: • ASSOCIATED WITH
– AFTER – DUE TO – CAUSATIVE AGENT
89
SNOMED version
Concept & Role-forming Operators
Role axioms
Language Role grouping
Early work (1996-1999)
(⊓, ∃R:C)( ) EL No
SNOMED RT (2000-2001)
(⊓, ∃R:C)(+) EL+ No
SNOMED CT (Jan02-Jan04)
(⊓, ∃R:C)( ) EL Yes
SNOMED CT (Jul04-present)
(⊓, ∃R:C)(+) R⊑ S ELH+ Yes
Summary of SNOMED’s use of DL
90
Notation mostly follows Donini in Ch.3 Description Logic Handbook(+) means right identities were used
CONTEXT MODEL
91
Common patterns
• Caveat: these are intended for illustrative purposes only, as examples of ways that system builders might simplify post-coordination for their clinical experts
• They are full logical models for which the meaning can be represented in the interface and in storage with more than one split between the information model and terminology model
92
Common patterns
• Clinical finding present• Clinical finding absent• Clinical finding unknown• History of• No history of• Family history of• No family history of• Observable + value• Procedure done• Procedure not done• (Drug or procedure) contraindicated
• Plus:– all the above with site, or site & laterality
93
Clinical finding present
SituationAssociated finding <finding>
Finding context Known present
Temporal context Current
Group
Subject relationship context Subject of record
Current or specified time
94Clinical-finding-present (<finding>)
Abrasion of upper limb
SituationAssociated finding Abrasion of upper limb
Finding context Known present
Temporal context Current
Group
Subject relationship context Subject of record
Current or specified time
95Clinical-finding-present (abrasion of upper limb)
Clinical finding absent
SituationAssociated finding <finding>
Finding context Known absent
Temporal context Current
Group
Subject relationship context Subject of record
Current or specified time
96Clinical-finding-absent (<finding>)
No chest retractions
SituationAssociated finding Chest wall retraction
Finding context Known absent
Temporal context Current
Group
Subject relationship context Subject of record
Current or specified time
97Clinical-finding-absent (chest wall retraction)
Clinical finding unknown
SituationAssociated finding <finding>
Finding context Unknown
Temporal context Current
Group
Subject relationship context Subject of record
Current or specified time
98Clinical-finding-unknown (<finding>)
Splenomegaly: unknown
SituationAssociated finding splenomegaly
Finding context Unknown
Temporal context Current
Group
Subject relationship context Subject of record
Current or specified time
99Clinical-finding-unknown (splenomegaly)
History of <finding>
SituationAssociated finding <finding>
Finding context Known present
Temporal context Current
Group
Subject relationship context Subject of record
In the past
100History-of (<finding>)
History of MI
SituationAssociated finding Myocardial
infarction
Finding context Known present
Temporal context Current
Group
Subject relationship context Subject of record
In the past
101History-of (myocardial infarction)
No history of <finding>
SituationAssociated finding <finding>
Finding context Known absent
Temporal context Current
Group
Subject relationship context Subject of record
All times past
102No-history-of (<finding>)
No history of seizure
SituationAssociated finding seizure (finding)
Finding context Known absent
Temporal context Current
Group
Subject relationship context Subject of record
All times past
103No-history-of (seizure (finding) )
Family history of <finding>
SituationAssociated finding <finding>
Finding context Known present
Temporal context Current
Group
Subject relationship context Family member
In the past
104Family-history-of (<finding>)
Family history of ischemic heart disease
SituationAssociated finding Ischemic heart
disease
Finding context Known present
Temporal context Current
Group
Subject relationship context Family member
In the past
105Family-history-of (ischemic heart disease)
No family history of <finding>
SituationAssociated finding <finding>
Finding context Known absent
Temporal context Current
Group
Subject relationship context Family member
All times past
106No-family-history-of (<finding>)
No family history of dementia
SituationAssociated finding dementia
Finding context Known absent
Temporal context Current
Group
Subject relationship context Family member
All times past
107No-family-history-of (dementia)
Switch to procedures
• Slightly different:– Two attributes:
• Associated-procedure• Procedure-context
• Same:– Temporal context– Subject relationship context
108
Procedure done
SituationAssociated procedure <procedure>
Procedure context Done
Temporal context Current
Group
Subject relationship context Subject of record
Current or specified time
109Procedure-done (<procedure>)
Tetanus booster given
SituationAssociated procedure
Booster tetanus vaccination (procedure)
Procedure context Done
Temporal context Current
Group
Subject relationship context Subject of record
Current or specified time
110Procedure-done (booster tetanus vaccination)
Procedure not done
SituationAssociated procedure <procedure>
Procedure context Not done
Temporal context Current
Group
Subject relationship context Subject of record
Current or specified time
111Procedure-not-done (<procedure>)
Neurological examination not done
SituationAssociated procedure
Neurological examination (procedure)
Procedure context Not done
Temporal context Current
Group
Subject relationship context Subject of record
Current or specified time
112Procedure-not-done (neurological examination)
Current or specified time
Drug contraindicated
Situation Associated procedure
<substance>
Procedure context Contraindicated
Temporal context
Group
Subject relationship context Subject of record
Administrationof medication
Direct-substance
113Drug-contraindicated (<substance>)
Current or specified time
Warfarin contraindicated
Situation Associated procedure
warfarin
Procedure context Contraindicated
Temporal context
Group
Subject relationship context Subject of record
Administrationof medication
Direct-substance
114Drug-contraindicated (warfarin)
Add site to previous patterns
• Clinical finding present + site• Clinical finding present + site + laterality• Clinical finding absent + site• Clinical finding absent + site + laterality
115
Clinical finding present + site
Situation
Associated finding
Finding context
<finding>
Known present
Finding-site <site>
Group
Temporal context Current or specified time
Subject relationship context Subject of record
116Clinical-finding-present-with-site (<finding>,<site>)
Bleeding finger
Situation
Associated finding
Finding context
bleeding
Known present
Finding-site Finger structure
Group
Temporal context Current or specified time
Subject relationship context Subject of record
117Clinical-finding-present-with-site (bleeding, finger structure)
Bleeding index finger
Situation
Associated finding
Finding context
bleeding
Known present
Finding-site Index finger structure
Group
Temporal context Current or specified time
Subject relationship context Subject of record
118Clinical-finding-present-with-site (bleeding,index finger structure)
Clinical finding absent + site
Situation
Associated finding
Finding context
<finding>
Known absent
Finding-site <site>
Group
Temporal context Current or specified time
Subject relationship context Subject of record
119Clinical-finding-absent-with-site (<finding>,<site>)
No right femoral bruit
Situation
Associated finding
Finding context
Femoral bruit
Known absent
Finding-site Right femoral artery
Group
Temporal context Current or specified time
Subject relationship context Subject of record
120Clinical-finding-absent-with-site (femoral bruit,right femoral artery)
No right femoral bruit
Situation
Associated finding
Finding context
bruit
Known absent
Finding-site Right femoral artery
Group
Temporal context Current or specified time
Subject relationship context Subject of record
121Clinical-finding-absent-with-site (bruit,right femoral artery)
Clinical finding present + site + side
Situation
Associated finding
Finding context
<finding>
Known present
Finding-site <site>
Group
Temporal context Current or specified time
Subject relationship context Subject of record
Laterality <side>
122Clinical-finding-present-with-site-and-side (<finding>,<site>,<side>)
Right femoral bruit present
Situation
Associated finding
Finding context
bruit
Known present
Finding-site Femoral artery
Group
Temporal context Current or specified time
Subject relationship context Subject of record
Laterality Right
123Clinical-finding-present-with-site-and-side (bruit, femoral artery, right)
Clinical finding present + site + side
Situation
Associated finding
Finding context
<finding>
Known present
Finding-site <site>
Group
Temporal context Current or specified time
Subject relationship context Subject of record
Laterality <side>
124Clinical-finding-present-with-site-and-side (<finding>,<site>,<side>)
Bleeding of left index finger present
Situation
Associated finding
Finding context
bleeding
Known present
Finding-site index finger structure
Group
Temporal context Current or specified time
Subject relationship context Subject of record
Laterality left
125Clinical-finding-present-with-site-and-side (bleeding, index finger structure, left)
Bleeding skin, left index finger
Situation
Associated finding
Finding context
bleeding
Known present
Finding-site Skin of index finger
Group
Temporal context Current or specified time
Subject relationship context Subject of record
Laterality left
126Clinical-finding-present-with-site-and-side(bleeding, skin of index finger, left)
Clinical finding absent + site + side
Situation
Associated finding
Finding context
<finding>
Known absent
Finding-site <site>
Group
Temporal context Current or specified time
Subject relationship context Subject of record
Laterality <side>
127Clinical-finding-absent-with-site-and-side (<finding>,<site>,<side>)
No right femoral bruit
Situation
Associated finding
Finding context
bruit
Known absent
Finding-site Femoral artery
Group
Temporal context Current or specified time
Subject relationship context Subject of record
Laterality right
128Clinical-finding-absent-with-site-and-side (bruit, femoral artery, right)
Using observables
• Finding present + observable + value
129
Finding present, observable + value
Situation Associated finding
Finding context
Clinical finding
Known present
Has-interpretation <value>
Group
Temporal context Current or specified time
Subject relationship context Subject of record
Group
Interprets <observable>
130Finding-present-observable-value (<observable>,<value>)
Knee jerk reflex 2+ (out of 4)
Situation Associated finding
Finding context
Clinical finding
Known present
Has-interpretation ++
Group
Temporal context Current or specified time
Subject relationship context Subject of record
Group
Interprets Knee jerk reflex271714006
260348001
131 Finding-present-observable-value (knee jerk reflex,++)
Situation Associated finding
Finding context
Clinical finding
Known present
Has-interpretation <value>
Group
Temporal context Current or specified time
Subject relationship context Subject of record
Group
Interprets <observable>
obs-site <site>
Finding present, observable + site + value (assuming we approve a site attribute for observables)
132Finding-present-obs-site-value (<observable>,<site>,<value>)
Situation Associated finding
Finding context
Clinical finding
Known present
Has-interpretation ++
Group
Temporal context Current or specified time
Subject relationship context Subject of record
Group
Interprets Knee jerk reflex
obs-site Left knee
Left knee jerk reflex ++(assuming we approve a site attribute for observables)
133Finding-present-obs-site-value (knee jerk reflex, left knee,++)
Procedure patterns
• Procedure done + method + site• Procedure done + method + site + laterality
134
Procedure done, method+site
Situation Associated procedure
Procedure context
procedure
Done
Procedure site - direct <site>
Group
Temporal context Current or specified time
Subject relationship context Subject of record
Group
Method <method>
135Procedure-done-plus-method-site (<method>,<site>)
X-ray of wrist done
Situation Associated procedure
Procedure context
procedure
Done
Procedure site - direct wrist
Group
Temporal context Current or specified time
Subject relationship context Subject of record
Group
Method Radiographic imaging
136Procedure-done-plus-method-site (x-ray, wrist)
Procedure done, method+site+side
Situation Associated procedure
Procedure context
procedure
Done
Procedure site - direct <site>
Group
Temporal context Current or specified time
Subject relationship context Subject of record
Laterality <side>
Group
Method <method>
137Procedure-done-method-site-side (<method>,<site>,<side>)
X-ray of left wrist done
Situation Associated procedure
Procedure context
procedure
Done
Procedure site - direct wrist
Group
Temporal context Current or specified time
Subject relationship context Subject of record
Laterality left
Group
Method radiographic imaging
138Procedure-done-method-site-side(radiographic imaging, wrist, left)
More specific patterns also possible
• For example:– Suture of skin done + site + laterality
139
Suture of skin done, site + side Situation Associated
procedure
Procedure context
Closure of skin by suture
Done
Procedure-site-indirect <site>
Group
Temporal context Current or specified time
Subject relationship context Subject of record
Laterality <side>
Group
Procedure-morphology-direct Laceration
Method Closure by device
Using-device Suture
140
Suture of laceration of skin of left index finger: done
Situation Associated procedure
Procedure context
Closure of skin by suture
Done
Procedure-site-indirect
Skin of index finger
Group
Temporal context Current or specified time
Subject relationship context Subject of record
Laterality left
Group
Procedure-morphology-direct Laceration
Method Closure by device
Using-device Suture
141
REDESIGN PROJECTS
142
Anatomy Redesign
• Reintroduce part-of roles• Sufficiently define the S and P of the SEP triad • Align the E with the Foundational Model of Anatomy
(FMA)
143
Reflexive roles
• Plan to introduce reflexive “part-of” as a way of handling “SEP” model evolution
proper-part-of v part-of ² v part-ofS ≡ ∃ part-of . EP ≡ ∃ proper-part-of . E
144
Suntisrivaraporn B, Baader F, Schulz S, and Spackman K. Replacing SEP-Triplets in SNOMED CT using Tractable Description Logic Operators. In Jim Hunter Riccardo Bellazzi, Ameen Abu-Hanna, editor, Proceedings of the 11th Conference on Artificial Intelligence in Medicine (AIME'07), Lecture Notes in Computer Science. Springer-Verlag, 287-291, 2007.
Substance Redesign
• Remove inappropriate is-a relationships• Add new attributes and values
• Many difficult decisions remain– How to represent “may be used as …”
• Timolol may be used as an eye medicine for glaucoma• Timolol may be used as a cardiac beta blocker
– Are H2CO3 and HCO3- the same or different? Do we
represent the various anions of drugs also?
145
Organism redesign
• Major steps:1. organize SNOMED's taxonomy into a
systematic and consistent Linneanhierarchy
2. remove all non-taxonomic information about living organisms from the taxonomic hierarchy
3. represent such information, when understandable, reproducible and useful, elsewhere in the terminology
146
• Linnean taxonomic terms (“Canis familiaris”)
• Common names for organisms (“Dog”)• Non-taxonomic information
– Use and Circumstances • Laboratory fur-bearing animal
– Pathogenicity• Parasite, pyogenic bacterium
– Life cycle stage of organisms • Worm eggs
Current taxonomy includes:
147
Common names in the FSN:
• Some organisms have many common names– Butorides virescens = green heron, green-backed heron,
little green heron, crab-catcher, fly-up-the-creek, green bittern, poke, shitepoke, skeow, skow, and swamp squaggin
• May be impossible to verify what organism is meant– Ex: Comte de Paris star frontlet (organism) ???
• A single common name may refer to more than one species:– Ex: Yellowhammer (organism) MAY BE A Emberiza
citrinella, MAY BE A Colaptes auratus
148
Non-taxonomic terms in a taxonomic hierarchy:
• a subtype is always and necessarily a "kind of" its parent (this is what subsumption means)
• interpolation of non-taxonomic terms in a taxonomic hierarchy violates this convention– these terms are often context-dependent rather than
defining. • An elephant may be a domestic animal in India• a dog may be a food animal in Korea• Is a canary a “Wild bird--chordate” or a “Domestic
fowl”? – Answer: Neither. It is Serinus canaria
149
Further enhancements of the model
• Attributes & values to represent contextual information about living organisms– Contexts of domesticity (domestic, feral, wild)– Contexts of use (food, laboratory, companion, service,
breeding, etc)– Contexts of life stage (oocyst, larva, spore, trophozooite,
etc)– Contexts of medical significance (parasite, renotrophic
organism, pathogen)???
150
Qualifiers for organisms?
• An organism might be qualified by non-taxonomic attributes/values, just as a disease might be qualified by severity, stage, episode, degree of control, etc.
• But: – Type 2 diabetes that is out of control is not really a different
type of disease; it is a different type of situation in which type 2 diabetes (the disease) is present.
– Dairy cattle and beef cattle are not really different types of organisms; they are different types of contexts in which cattle (organisms) are used for different purposes.
151
What about “infectious agents”?
• The taxonomy of parasites, bacteria and other potentially pathogenic microorganisms is also a mixture of scientific names, common names, and contextual information
• Attempting to convey “contexts of pathogenicity” creates errors in logic:– Ex: Helminth ISA Parasite?
• Wrong. Most helminths are not parasitic– Ex: Fungus ISA Infectious agent?
• Wrong. Most fungi are not infectious
152
Observable Redesign
• Separate processes, functions, and qualities
• Add attributes that define observables in terms of:– Properties they observe– Timing– Scales or units– Techniques of observation
• Add attributes that define qualities/properties in terms of:– the independent continuant in which they inhere
153
Substances, functions, processes, activities, organisms, cell structures
Observable entity
COMPONENT
PROPERTY
SYSTEM / OBSERVABLE SITE
Properties
Specimens, Sites
TIME ASPECT
SCALE / UNITS
Time aspects
Scale types, units
TECHNIQUE techniques
DRAFT model of observables
154
Observable entity
PROPERTY properties
independent continuant
TIME ASPECT
SCALE / UNITS
Time aspects
Scale types, units
TECHNIQUE techniques
INHERES INTOWARDS Functions, substances
DRAFT alternative model of observables
155
Events, conditions, episodes
• Need to define what is an event, what is a condition, what is an episode
• Need criteria for deciding whether we need one code or two– seizure, epilepsy: clearly different, so we need two codes– tachycardia, tachyarrhythmia: same or different?– low hemoglobin, anemia: same or different?– rash of forearm: do we need both a disorder and a finding?
156
Should we add more expressive DL features?
• General concept inclusion axioms• Transitive roles• Reflexive roles• Disjointness axioms• Value restrictions• Negation• Disjunction• Cyclic definitions• Number restrictions
157
General concept inclusion axioms
• Extremely useful feature• Compatible with a polynomial-time structural
subsumption algorithm
• Allows us to say what is true in addition to what is sufficient– Gastric ulcer is located in the stomach, and in addition it
necessarily involves the gastric mucosa
158
Transitive roles
• x Ry y Rz → x Rz
• Useful for causal/associational chains• Interaction with role hierarchy is interesting &
useful
• Example: Associated-with-after– Varicella (chicken pox)
– An infection with causative-agent = varicella virus– Herpes zoster
– Also has causative-agent = varicella virus, and occurs after varicella
– Post-herpetic neuralgia– Occurs after herpes zoster (therefore occurs after varicella),
but is not an infection with causative-agent varicella virus
159
Reflexive roles
• Plan to introduce reflexive “part-of” as a way of handling “SEP” model evolution
proper-part-of v part-of ² v part-ofS ≡ ∃ part-of . EP ≡ ∃ proper-part-of . E
160
Suntisrivaraporn B, Baader F, Schulz S, and Spackman K. Replacing SEP-Triplets in SNOMED CT using Tractable Description Logic Operators. In Jim Hunter Riccardo Bellazzi, Ameen Abu-Hanna, editor, Proceedings of the 11th Conference on Artificial Intelligence in Medicine (AIME'07), Lecture Notes in Computer Science. Springer-Verlag, 287-291, 2007.
Value restriction ∀R.C
• Not an intuitive construct– person u ∀hasCar.Jaguar– Includes people who have no car, but if they had one it
would have to be a Jaguar . . . . Do we encounter this kind of concept in common-sense thinking?
• Creates pernicious interactions with disjunction and negation that tend to make structural subsumption algorithms incomplete
• But it was included in ALC and FL−, so languages including it were studied extensively.
161
Negation ¬C
• Head injury without loss of consciousness
headInjury u ¬ lossOfConsciousness
situation u∃ includes.headinjury u¬ ∃ includes.lossOfConsciousness
162
Disjunction C t D
• Some high-level aggregators are naturally disjunctive
• We can address this need partially by using navigation hierarchies
163
Cyclic definitions, number restrictions
• ? No significant need for these at present
164
INFORMATION MODEL INTERACTIONS
165
Clinical Decision Support Model + Inference Rules
Terminology Model+ Compositional Expressions Information Model
+ Patient Data Structures
Diagram based on Figure 1 in Rector AL et al. “Interface of Inference Models with Concept and Medical Record Models” AIME 2001: 314-323
Interaction between Terminology and Information Models
166
Terminology vs Information modelWhat’s the issue?
• Information model:– Determines and organizes the kinds of entities which
carry values in a record– Loosely referred to as slots, facets, fields, questions
• Terminology model:– Determines and organizes the kinds of entities which
are the values– Variously referred to as the terminology or ontology
or value sets
167
Extremes (reductio ad absurdum)
• Put all meaning in the terminology– A code (or terminology expression) for every meaning
that needs to be expressed– Only one “field” in the record
• What about dates, numeric values, names, places, and relationships between them?
• Put all meaning in the information model– Two values: “yes” and “no”– A “question” for every meaning that needs to be
expressed, and a field for every question• What about combinatorial explosion of subtypes of
things in the real world?
168
Representing the semantics of clinical data
• For any given application– There needs to be a boundary between information
model and terminology• without gaps or overlaps
• There are several different choices for where to draw the boundary between
• No single choice of boundary is globally the best• How can we achieve standardization for
interoperability?
169
Terminology – information model interaction: broad tasks required
• Identify gaps and overlaps• Design a strategy to
– Fill the gaps– Manage the overlaps
• Demonstrate implementability
170
TermInfo – Specific advice
Act.code & Observation.value (1)• HL7 theory
– code nature of observation– value value of the observation
• Practical implementation– Simple for numeric observations
• Hemoglobin level (code) = 14g/dL (value)– Reasonable for observations with coded results
• Visual acuity (code) = Can count fingers (value)– Tricky for observations where the distinction between
the nature and value is arbitrary• “Blood group AB” could be …
1. ABO Blood grouping (code) Blood group AB (value)
2. Blood group A antigen (code) Present (value)and Blood group B antigen (code) Present
(value)3. Blood group AB (code)
171
TermInfo – Specific adviceAct.code & Observation.value (2)
• The code-value split is even more arbitrary for general clinical observations
• For example– Finding of abdominal tenderness …
1. Examination (code) abdomen tender (value)2. Abdominal examination (code) abdomen tender
(value)3. Abdominal palpation (code) abdomen tender
(value)4. Abdominal tenderness (code) present (value)5. Abdomen tender (code)
172
TermInfo – Specific advice
Code and Value – guidance• HL7 code and value distinction should be used for
– Numeric and non-numeric results of measurement procedures
• A single coded attribute should express the full semantics – If there is no non-arbitrary reproducible
distinction– Recommended Implementation
• Act.Code = ASSERTION• Observation.Value = Coded SNOMED
expression• Rationale
– SNOMED CT clinical findings are • not just the value of a particular type of
observation• equivalent to an observable or observation
type with a value
173
“Code-value” discussion
• Not unique to HL7• Suggests terminology-information model
standardization efforts may benefit from each other
174