Transcript Document

R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
Bioinformatics and Technology Applications in
Medication Management.
Ontology: background and application to
Medication Management
Buffalo, NY, USA, June 13th, 2008
Werner CEUSTERS, MD
Center of Excellence in Bioinformatics and Life Sciences, and
National Center for Biomedical Ontology, University at Buffalo, NY, USA
R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
‘Ontology’ is
popular
‘Ontology’ in
Buffalo is famous
R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
‘Ontology’: one word, two meanings
• In philosophy:
– Ontology (no plural) is the study of what entities exist and how they
relate to each other;
• In computer science and (biomedical informatics)
applications:
– An ontology (plural: ontologies) is a shared and agreed upon
conceptualization of a domain;
• Our ‘realist’ view within the Ontology Research Group
combines the two:
– We use realism, a specific theory of ontology, as the basis for
building high quality ontologies, using reality as benchmark.
R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
Realism-based ontology
• Basic assumptions:
1. reality exists objectively in itself, i.e. independent of
the perceptions or beliefs of cognitive beings;
2. reality, including its structure, is accessible to us,
and can be discovered through (scientific) research;
3. the quality of an ontology is at least determined by
the accuracy with which its structure mimics the
pre-existing structure of reality.
R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
Three major views on reality
Realism
• Basic questions:
– What does a
general term
such as ‘tree’
refer to?
– Do generic
things exist?
Conceptualism Nominalism
Universal
Concept
Collection
of
particulars
yes: in
particulars
perhaps: in
minds
no
R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
Dominant view in computer science is conceptualism
Realism
• Basic questions:
– What does a
general term
such as ‘tree’
refer to?
– Do generic
things exist?
Conceptualism Nominalism
Universal
Concept
Collection
of
particulars
yes: in
particulars
perhaps: in
minds
no
R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
Dominant view in computer science is conceptualism
Realism
Conceptualism Nominalism
concept
Embedded in
Terminology
Semantic
Triangle
object
term
R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
‘Terminology’: one word, two meanings
• Terminology is the study of identifying and labelling
‘concepts’ pertaining to a subject field.
• Terminology related activities:
– analysing the concepts and concept structures,
– identifying the terms assigned to the concepts,
– establishing correspondences between terms, possibly in various
languages,
– compiling a terminology, on paper or in databases,
– managing terminology databases,
– creating new terms, as required.
R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
Why this interest in biomedical terminologies?
• ‘Nuances in the English language can be both
challenging and amusing, however, when variants in
language impact treatment, safety and billing, it is all
challenge and no humor.
Although English contains a reasonable degree of
conformity, divergence in phrasing and meaning can
compound comprehension problems and impact patient
safety. These language "woes" can be minimized through
the use of sophisticated healthcare IT systems with
terminology management services.’
Schwend GT. The language of healthcare. Variance in the English language is harming patients and hospitals'
bottom lines. Is healthcare IT the solution? Health Manag Technol. 2008 Feb;29(2):14, 16, 18
R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
An example of a terminology: RxNorm
• What:
‘a standardized nomenclature for the smooth
exchange of information between and within
organizations’;
• Goal:
‘to allow various systems using different drug
nomenclatures to share data efficiently at the
appropriate level of abstraction’;
• Method: ‘a standard format in the naming of clinical drugs
reflecting the active ingredients, strengths, and dose form
comprising that drug. When any of these elements vary, a
new name is created as a separate concept. An RxNorm
name should exist for every strength and dose of every
available combination of clinically significant ingredients.
http://www.nlm.nih.gov/research/umls/rxnorm/overview.html
R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
RxNorm for expressing similarities in medications
• Orajel Mouth Sore Rinse 150 MG/ML Mucous
Membrane Topical Solution
• Perimax Perio Rinse 15 MG/ML Mucous
Membrane Topical Solution
• Peroxyl 0.015 MG/MG Oral Gel
• Peroxyl 15 MG/ML Mucous Membrane Topical
Solution
• Proxacol 30 MG/ML Topical Solution
• Superoxol 350 MG/ML Topical Solution
R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
Method: standardized name composition
Ingredient
Strength
Form
with a cheat for ‘packs’
R T U New York State
Center of Excellence inRxNorm
Bioinformatics & Life Sciences
through RxNav
R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
However …
• Terminology:
– solves certain issues related to language use, i.e. with respect to
how we talk about entities in reality (if any);
• Relations between terms / concepts
– does not provide an adequate means to represent independent of
use what we talk about, i.e. how reality is structured;
• Women, Fire and Dangerous Things (Lakoff).
• Ontology (of the right sort):
– Language and perception neutral view on reality.
• Relations between entities in first-order reality
This is the ‘terminology / ontology divide’
R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
The semantic triangle revisited
Representation and Reference
concepts
concepts
terms
about
objects
terms
First Order Reality
R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
Terminology
Realist Ontology
Representation and Reference
terms
concepts
representational units
about
objects
universals
First Order Reality
particulars
R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
Terminology
Realist Ontology
Representation and Reference
terms
concepts
representational units
about
objects
universals
First Order Reality
particulars
R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
Terminology
Realist Ontology
Representation and Reference
representational units
terms
concepts
cognitive
units
communicative
units
about
objects
universals
First Order Reality
particulars
R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
Three
Terminology
levels of reality in Realist Ontology
Representation and Reference
representational units
(3) Representational units in various
forms about (1), (2) or (3)
cognitive
units
communicative
units
universals
particulars
(2) Cognitive entities which are our
beliefs about (1)
(1) Entities with objective existence
which are not about anything
First Order Reality
R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
The three levels applied to medication management
Generic
3. Representation
2. Beliefs
(knowledge)
1.
First-order
reality
‘person’ ‘drug’ ‘penicillin’
CONTRA-INDICATION
INDICATION
PATHOLOGICAL
STRUCTURE
DRUG
MOLECULE
Specific
‘W. Ceusters’ ‘my pneumonia’
my doctor’s
work plan
my doctor
PERSON
DISEASE
PORTION OF
PENICILLIN
me
my doctor’s
diagnosis
my pharmacist’s
computer
my bronchitis
my toxic reaction
to penicillin
R T U New York State
Center of Excellence in
Places for
ontology in medication management
Bioinformatics & Life Sciences
Medication Management Detailed Use Case June 18th, 2007.
(www.hhs.gov/healthit/documents/UseCaseMM.pdf)
R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
Terminology is too reductionist
Generic
3. Representation
2. Beliefs
(knowledge)
1.
First-order
reality
‘person’ ‘drug’ ‘penicillin’
CONTRA-INDICATION
INDICATION
PATHOLOGICAL
STRUCTURE
DRUG
MOLECULE
Specific
‘W. Ceusters’ ‘my pneumonia’
my doctor’s
work plan
my doctor
PERSON
DISEASE
PORTION OF
PENICILLIN
me
my doctor’s
diagnosis
my pharmacist’s
computer
my bronchitis
my toxic reaction
to penicillin
R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
Terminology is too reductionist
What concepts do we need?
How do we name concepts properly?
R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
Terminological versus Ontological approach
• The terminologist defines:
– ‘a clinical drug is a pharmaceutical product given to (or taken
by) a patient with a therapeutic or diagnostic intent’. (RxNorm)
• The ontologist thinks:
– Does ‘given’ includes ‘prescribed’?
– Is manufactured with the intent to … not sufficient?
• Are newly marketed products – available in the pharmacy, but not yet
prescribed – not clinical drugs?
• Are products stolen from a pharmacy not clinical drugs?
• What about such products taken by persons that are not patients?
– e.g. children mistaking tablets for candies.
R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
RxNorm from an ontological perspective
Use-mention
confusion
http://www.nlm.nih.gov/research/umls/rxnorm/overview.html
R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
Why is this important ?
• Not as much for humans:
– Our ‘minds’ are very good in resolving ambiguities,
even at ‘unconscious’ levels.
• But for machines (computers, software):
– They can’t deal with imprecise, vague or ambiguous
statements.
R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
Standards for ePrescribing under Medicare Part D
• Formulary and benefits information:
– NCPDP Formulary and Benefits Standard 1.0.
• Identification of providers:
– National Provider Identifier (NPI)
• Medication history
– Medication History Standard in NCPDP SCRIPT 8.1
• Fill status notification
– RxFill in NCPDP SCRIPT 8.1
42 CFR Part 423. Federal Register / Vol. 73, No. 67 :18917-42/ Monday, April 7, 2008 / Rules and Regulations
R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
A realist ontological view on ‘data’ standards
Use/mention confusion: is the medication history record dispensed,
prescribed, …, or the drug mentioned in he record?
CSC. Record Locator Service Prototype. Medications History Implementation Guide. V0.4. 2005-11-15.
R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
A realist ontological view on ‘data’ standards
Inconsistent representation: is ‘E.g.’ part of the drug name?
Where is the strength and dosage?
CSC. Record Locator Service Prototype. Medications History Implementation Guide. V0.4. 2005-11-15.
R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
A realist ontological view on ‘data’ standards
Vocabularies with ontologically unclear semantics:
10
11
12
13
14
147
148
149
tablet
enteric coated tablet
sustained release tablet
buccal or sublingual tablet
chewable tablet
tablet, chewable
tablet, coated particles
tablet, disintegrating
15
150
151
16
23
24
72
soluble tablet
tablet, effervescent
tablet, extended release
tablet unspecified
tablet 21 day supply
tablet 28 day supply
vaginal tablet
CSC. Record Locator Service Prototype. Medications History Implementation Guide. V0.4. 2005-11-15.
R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
A realist ontological view on ‘data’ standards
Mixing types and instances: there is only one NDC (=particular),
there are many manufacturers (=defined class)
CSC. Record Locator Service Prototype. Medications History Implementation Guide. V0.4. 2005-11-15.
R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
The cost of ignoring the type/instance distinction
PtID
Date
ObsCode
Narrative
5572
04/07/1990
26442006
closed fracture of shaft of femur
5572
04/07/1990
81134009
Fracture, closed, spiral
5572
12/07/1990
26442006
closed fracture of shaft of femur
5572
12/07/1990
9001224
Accident in public building (supermarket)
5572
04/07/1990
79001
Essential hypertension
0939
24/12/1991
255174002
benign polyp of biliary tract
2309
21/03/1992
26442006
closed fracture of shaft of femur
2309
21/03/1992
9001224
Accident in public building (supermarket)
47804
03/04/1993
58298795
Other lesion on other specified region
5572
17/05/1993
79001
Essential hypertension
298
22/08/1993
2909872
Closed fracture of radial head
298
22/08/1993
9001224
Accident in public building (supermarket)
5572
01/04/1997
26442006
closed fracture of shaft of femur
5572
01/04/1997
79001
Essential hypertension
0939
20/12/1998
255087006
malignant polyp of biliary tract
R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
Codes for types AND identifiers for instances
PtID
Date
ObsCode
Narrative
5572
04/07/1990
26442006
IUI-001
closed fracture of shaft of femur
5572
04/07/1990
81134009
IUI-001
Fracture, closed, spiral
5572
12/07/1990
26442006
IUI-001
closed fracture of shaft of femur
5572
12/07/1990
9001224
IUI-007
Accident in public building (supermarket)
5572
04/07/1990
79001
IUI-005
Essential hypertension
0939
24/12/1991
255174002
IUI-004
benign polyp of biliary tract
2309
21/03/1992
26442006
IUI-002
closed fracture of shaft of femur
2309
21/03/1992
9001224
IUI-007
Accident in public building (supermarket)
47804
03/04/1993
58298795
IUI-006
Other lesion on other specified region
5572
17/05/1993
79001
IUI-005
Essential hypertension
298
22/08/1993
2909872
IUI-003
Closed fracture of radial head
298
22/08/1993
9001224
IUI-007
Accident in public building (supermarket)
5572
01/04/1997
26442006
IUI-012
closed fracture of shaft of femur
5572
01/04/1997
79001
IUI-005
Essential hypertension
IUI-004
malignant polyp of biliary tract
0939
20/12/1998
255087006
7 distinct
disorders
R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
The power of realism in ontology design
Reality as benchmark !
1. Is the scientific ‘state of the art’
consistent with biomedical reality ?
R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
The power of realism in ontology design
Reality as benchmark !
2. Is my doctor’s knowledge up to date?
R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
The power of realism in ontology design
Reality as benchmark !
3. Does my doctor have an accurate
assessment of my health status?
R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
The power of realism in ontology design
Reality as benchmark !
4. How can we use case studies better
to advance the state of the art?
R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
The power of realism in ontology design
Reality as benchmark !
5. Is our terminology rich enough
to communicate about all three levels?
R T U New York State
Center of Excellence in
Bioinformatics & Life Sciences
In summary
• Medication management involves many actors and IT
systems: semantic interoperability is thus a key issue.
• Ontologies (of the right sort) provide a deep level of
semantic interoperability between IT systems, thereby
keeping track:
– of what is the case;
– of what is known by some actor(s);
– of what has been and still needs to be done.
• Realism-based ontology, as a discipline, helps in creating
ontologies of the right sort.