Transcript Future_of_Health_Inf.. - Buffalo Ontology Site

The Future of Health Information
Barry Smith
Ontology Research Group
Center of Excellence in Bioinformatics and Life
Sciences
University at Buffalo
ontology.buffalo.edu/smith
Collaborations
• National Center for Biomedical Ontology
(http://NCBO.us)
• WHO Collaborating Center for Terminology
• Cleveland Clinic Semantic Database
• SNOMED CT – Disease Ontology
• German national Electronic Health Record
initiative [Health Version 11]
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Overview of this talk
• The role of ontology
• The role of HL7
• The future of health information
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Overview of this talk
• The role of ontology
• The role of HL7
• The future of health information
4
5
we need to know
where in the body,
where in the cell
we need to know
what kind of
disease process
we need semantic annotation of data
= we need ontologies
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Ontologies are systems of terms for
annotating data
They are controlled vocabularies designating
the types of entities in reality
Data designate the instances of these types
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The Gene Ontology:
A set of standardized textual descriptions of
• cellular locations
• molecular functions
• biological processes
• used to annotate the entities represented in the
major biochemical databases
• thereby creating integration across these
databases
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what cellular component?
what molecular function?
what biological process?
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The process of data annotation
• yields a slowly growing computer-interpretable
map of biological reality within which major
databases are automatically integrated in
semantically searchable form
12
But now
need to extend the methodology to other
domains, including clinical medicine
 need disease, symptom (phenotype)
ontologies
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The Problem
need for prospective standards to ensure mutual
consistency and high quality of clinical
counterparts of GO
need to ensure consistency of the new clinical
ontologies with the basic biomedical sciences
if we do not start now, the problem will only get
worse
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The Solution
• establish common rules governing best
practices for creating ontologies and for
using these in annotations
• apply these rules to create a complete suite
of orthogonal interoperable biomedical
reference ontologies
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First step (2003)
• a shared portal for (so far) 58 ontologies
• (low regimentation)
• http://obo.sourceforge.net  NCBO BioPortal
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Second step (2004):
reform efforts initiated, e.g. linking GO to other OBO ontologies to ensure
interoperability
GO
id: CL:0000062
name: osteoblast
def: "A bone-forming cell which secretes an extracellular matrix.
Hydroxyapatite crystals are then deposited into the matrix to form
bone."
is_a: CL:0000055
relationship: develops_from CL:0000008
relationship: develops_from CL:0000375
Osteoblast differentiation: Processes whereby an
osteoprogenitor cell or a cranial neural crest cell
acquires the specialized features of an osteoblast, a
bone-forming cell which secretes extracellular matrix.
+
Cell type
=
New Definition
Third step (2006)
The OBO Foundry
http://obofoundry.org/
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The OBO Foundry
• a family of interoperable gold standard biomedical
reference ontologies to serve the annotation of




scientific literature
model organism databases
clinical data
experimental results
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Compare the UMLS Metathesaurus
a system of post hoc mappings between
independent source vocabularies
built by trained experts
massively useful for information retrieval and
information integration
creates out of literature a semantically searchable
space
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for UMLS
local usage respected
regimentation frowned upon
cross-framework consistency not important
no concern to establish consistency with basic science
different grades of formal rigor, different degrees of completeness,
different update policies
no path towards improvement
no path towards support for logical reasoning
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The OBO Foundry is a prospective standard
designed to guarantee interoperability of ontologies from
the very start (contrast to: post hoc mapping)
established March 2006
12 initial candidate OBO ontologies – focused primarily
on basic science domains
several being constructed ab initio
now 16 ontologies
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Ontology
Scope
URL
Custodians
Cell Ontology
(CL)
cell types from prokaryotes
to mammals
obo.sourceforge.net/cgibin/detail.cgi?cell
Jonathan Bard, Michael
Ashburner, Oliver Hofman
Chemical Entities of Biological Interest (ChEBI)
molecular entities
ebi.ac.uk/chebi
Paula Dematos,
Rafael Alcantara
Common Anatomy Reference Ontology (CARO)
anatomical structures in
human and model organisms
(under development)
Melissa Haendel, Terry
Hayamizu, Cornelius Rosse,
David Sutherland,
Foundational Model of
Anatomy (FMA)
structure of the human body
fma.biostr.washington.
edu
JLV Mejino Jr.,
Cornelius Rosse
Functional Genomics
Investigation Ontology
(FuGO)
design, protocol, data
instrumentation, and analysis
fugo.sf.net
FuGO Working Group
Gene Ontology
(GO)
cellular components,
molecular functions,
biological processes
www.geneontology.org
Gene Ontology Consortium
Phenotypic Quality
Ontology
(PaTO)
qualities of anatomical
structures
obo.sourceforge.net/cgi
-bin/ detail.cgi?
attribute_and_value
Michael Ashburner, Suzanna
Lewis, Georgios Gkoutos
Protein Ontology
(PrO)
protein types and
modifications
(under development)
Protein Ontology Consortium
Relation Ontology (RO)
relations
obo.sf.net/relationship
Barry Smith, Chris Mungall
RNA Ontology
(RnaO)
three-dimensional RNA
structures
(under development)
RNA Ontology Consortium
Sequence Ontology
(SO)
properties and features of
nucleic sequences
song.sf.net
Karen Eilbeck
RELATION
TO TIME
CONTINUANT
INDEPENDENT
OCCURRENT
DEPENDENT
GRANULARITY
ORGAN AND
ORGANISM
Organism
(NCBI
Taxonomy)
CELL AND
CELLULAR
COMPONENT
Cell
(CL)
MOLECULE
Anatomical
Organ
Entity
Function
(FMA,
(FMP, CPRO) Phenotypic
CARO)
Quality
(PaTO)
Cellular
Cellular
Component Function
(FMA, GO)
(GO)
Molecule
(ChEBI, SO,
RnaO, PrO)
Molecular Function
(GO)
Building out from the original GO
Biological
Process
(GO)
Molecular
Process
(GO)
The vision
OBO low-regimentation ontology portal
OBO Foundry high-regimentation
collaborative initiative to create a gold
standard suite of interoperable ontologies
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Ontologies under construction
 Common Anatomy Reference Ontology
 Disease Ontology (DO) [SNOMED CT]
 Biomedical Image Ontology (BIO)
 Environment Ontology (EnvO)
 Biobank Ontology (BrO)
 Clinical Trial Ontology (CTO) [with WHO Global Trial
Bank, Immune Tolerance Network, ACGT Advancing
Genomics Clinical Trials in Cancer EU IP]
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Clinical Trial Ontology
• part of a larger project called the Ontology for
Biomedical Investigations (OBI)
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OBI
controlled vocabulary for biomedical
investigations including
 protocols
 instrumentation
 material
 data
 types of analysis and statistical tools
applied to the data
http://obofoundry.org/
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Clinical Trial Ontology
• To serve merger of data schemas
• To serve flexibility of collaborative clinical trial
research
• To serve design and management of clinical trials
• To serve data access and reuse – send me all trials
which ...
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Ontology vs. Database Schema
• Separate development of data schemas and
‘information models’ (HL7) and terminologies
such as SNOMED CT
• the two do not work together
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Ontology vs. Database Schema
• diabetes => disease
• diabetes => string
• temperature => quality
• temperature => integer
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CTO
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CTO Continuant
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CTO Occurrent
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Clinical Trial Ontology Working Group
• http://www.bioontology.org/wiki/
• Workshop on May 16-17, 2007
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• The role of ontology
• The role of HL7
• The future of health information
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HL7 V3
“the data standard for
biomedical informatics”
•
http://aurora.regenstrief.org/~schadow/
HL7TheDataStandardForBiomedicalInformatics.ppt
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HL7 V2
a workable messaging standard
faced the problem of local dialects
HL7 V3
seeks to solve this problem by having all HL7
artifacts conform to a single ‘Reference
Information Model’ (the RIM)
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is there a single, successful RIM-implementation?
After 10 years?
And many attempts?
And gigantic investments of energy and funding?
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There are clear examples of failure of billion-dollar
implementations resting on the RIM
and of programmers involved in such failures who
are tearing out their hair, and blaming HL7
Is it justified, in these circumstances, to promote
HL7 V3 as an ISO Standard
in the domain of patient care?
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One indispensable foundation for a successful standard
a correct and uniform interpretation of its basic
terms
• Act
• Participation
• Entity
• Role
• ActRelationship
• RoleLink
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Demonstrably, the HL7 community does not
understand its own basic terms
• Sometimes ‘Act’ means information about an
act
• Sometimes ‘Act’ means real-world action
• Sometimes ‘Act’ means a mixture of the
above
• Sometimes in the very same sentence
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Consequences of unclarity here
• Different user groups have interpreted the
same classes in different ways
• Different message specifications used different
interpretations
• This recreates interoperability problems
• Can we be sure that these problems will not
lead to incidents relevant to patient safety?
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Even with clarity – and clear
documentation – the RIM would still be in
bad shape
http://hl7-watch.blogspot.com/
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Where are diseases
• Acts ?
• Things, Persons, Organizations ?
• Participations ?
• Roles ?
• ActRelationships ?
• RoleLinks ?
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The HL7 Clinical Genomic Standard
• defines an allele as the observation of an allele
• defines a phenotype as the observation of an
observation
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The $ 35 bn. NHS Program “Connecting for
Health”
• has applied the RIM rigorously, using all the
normative elements, and it discovered that it
needed to create dialects of its own to make the
V3-based system work for its purposes (it still
does not work)
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The RIM has no coherent answer
• Basic categories cannot be agreed upon
even for common phenomena like
snakebites.
• HL7 V3 dialects are formed – and the
RIM does not do its job.
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The moral of this story
• Don’t claim to be
• “the data standard for
biomedical informatics”
• until you have a system that works
•
http://aurora.regenstrief.org/~schadow/ HL7TheDataStandardForBiomedicalInformatics.ppt
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• The role of ontology
• The role of HL7
• The future of health information
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A New Paradigm for
Health Information
• How achieve semantic interoperability amongst
healthcare applications?
• Through referent tracking
www.org.buffalo.edu/RTU
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The myth of ‘unambiguous’ understanding
through biomedical terminologies
PtID
Date
ObsCode
Narrative
How
many
closed
fracture
of shaft numerically
of femur
different
disorders are
Fracture,
closed, spiral
closed
fracture
of shaft?of femur
listed
here
5572
04/07/1990
26442006
5572
04/07/1990
81134009
5572
12/07/1990
26442006
5572
12/07/1990
9001224
5572
04/07/1990
79001
0939
24/12/1991
255174002
2309
21/03/1992
26442006
2309
21/03/1992
9001224
47804
03/04/1993
58298795
Other lesion on other specified region
5572
17/05/1993
79001
Essential hypertension
298
22/08/1993
2909872
298
22/08/1993
9001224
5572
01/04/1997
26442006
How many disorders
have
patients
5572, 2309
Closed
fracture
of radial head
and in298
thus
Accident
publiceach
buildinghad
(supermarket)
closed
of shaftlifetime
of femur
farfracture
in their
?
5572
01/04/1997
79001
Essential hypertension
0939
20/12/1998
255087006
malignant polyp of biliary tract
*
Accident in public building (supermarket)
How many different
benign
polypof
of biliary
tract
types
disorders
are
closed fracture of shaft of femur
listed here ?
Essential hypertension
*
*
Accident in public building (supermarket)
* cause, not disorder
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Does seeing the labels help ?
PtID
Date
Different patients. Same supermarket?
Maybe the same freezer section ?
Or different supermarkets,
but always
ObsCode
Narrative
in the freezer
sections
? of femur
26442006
closed
fracture of shaft
Same patient,
same
hypertension
code:
81134009
Fracture,
closed, spiral
Same (numerically
identical)
hypertension ?
5572
04/07/1990
5572
04/07/1990
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
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Same patient, different
21/03/1992
26442006
closed fracturedates,
of shaft ofsame
femur fracture
Same
patient,
21/03/1992
9001224
Accident
in publicsame
buildingdate,
(supermarket)
codes:
same
03/04/1993patient,
58298795
Other lesion
on other specified
region
2patients,
different
fracture
codes:
Same
different
Differentdates,
same
fracture
codes:
(numerically
identical)
17/05/1993
79001
Essential
hypertension
same (numerically
Different codes.Same
Same(numerically
(numerically
identical)headfracture
? ?
22/08/1993
2909872
Closed fracture of radialfracture
identical) fracture ?
identical)
polyp
?
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
2309
2309
47804
5572
298
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We have unique IDs
•
•
•
•
for patients
for healthcare deliverers
for images
for invoices
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Let’s introduce unique IDs
• for everything that is mentioned in the record:
– lesions
– fractures
– presentings
– surgical procedures
http://sourceforge.net/projects/rtsystem
• IUI = instance unique identifier
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Better public health statistics
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
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
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
5572
01/04/1997
26442006
IUI-012
closed fracture of shaft of femur
5572
01/04/1997
79001
IUI-005
Essential hypertension
0939
20/12/1998
255087006
IUI-004
malignant polyp of biliary tract
IUI-007
Accident in public building (supermarket)
IUI-007
Accident in public building (supermarket)
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Better reasoning over health information
‘John Doe’s
person
inst-of
at t2
#10 ‘John Smith’s
instance-of
at t1
liver
inst-of
at t2
#20 liver
instance-of
at t1
tumor
inst-of
at t2
#30 tumor
#1
instance-of
at t1
liver
#2
tumor
#3
was treated
#4
instance-of
at t1
treating
inst-of
at t2
with
RPCI’s
irradiation device’
#40
was treated
with
#5
clinic
instance-of
at t1
#6
device
#5
inst-of
at t2
#6
RPCI’s
irradiation device’
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Application principles
Ontology
continuant
disorder
person
CAG repeat
EHR
Juvenile HD
#IUI-1 ‘affects’ #IUI-2
#IUI-3 ‘affects’ #IUI-2
#IUI-1 ‘causes’ #IUI-3
Referent Tracking
Database
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Goal: A New Form of Evidence Based Medicine
• Now:
– Decisions based on the outcomes of (reproducible)
results of well-designed studies
• Guidelines and protocols
– Evidence is hard to get, takes time to accumulate.
• Future:
– Each discovered fact or expressed belief should
instantly become available as contributing to the total
body evidence, wherever its description is generated.
– Data ‘eternally’ reusable independent of the purpose
for which they have been generated.
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