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New York State Center of Excellence in Bioinformatics & Life Sciences R T U The Role of Terminologies and Ontologies in the Context of the Electronic Health Record Dagstuhl May 23th, 2006 Werner Ceusters, MD Ontology Research Group Center of Excellence in Bioinformatics & Life Sciences SUNY at Buffalo, NY
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Page 1: RoleOfTerminologies

New York State Center of Excellence in Bioinformatics & Life Sciences

R T U

The Role of Terminologies and Ontologies in the Context of the

Electronic Health Record

Dagstuhl May 23th, 2006

Werner Ceusters, MDOntology Research Group

Center of Excellence in Bioinformatics & Life Sciences

SUNY at Buffalo, NY

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New York State Center of Excellence in Bioinformatics & Life Sciences

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Electronic Health Records

• ISO/TS 18308:2003– Electronic Health Record (EHR):

• A repository of information regarding the health of a subject of care, in computer processable form.

– EHR system:• the set of components that form the mechanism by which electronic

health records are created, used, stored, and retrieved. It includes people, data, rules and procedures, processing and storage devices, and communication and support facilities.

• More common meaning of EHR system: – only the “software being executed”

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A replacement for

This and that

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typicalEHR

screen

www.comchart.com

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Current US GOV eHealth goals & strategies• Goal 1: Inform Clinical Practice:

– S1. Provide incentives for EHR adoption. – S2. Reduce risk of EHR investment. – S3. Promote EHR diffusion in rural and underserved areas.

• Goal 2: Interconnect Clinicians. – S1. Regional collaborations. – S2. Develop a national health information network. – S3. Coordinate federal health information systems.

• Goal 3: Personalize Care. – S1. Encourage use of Personal Health Records. – S2. Enhance informed consumer choice. – S3. Promote use of telehealth systems.

• Goal 4: Improve Population Health. – S1. Unify public health surveillance architectures. – S2. Streamline quality and health status monitoring. – S3. Accelerate research and dissemination of evidence.

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Functions to be supported (HL7)

• Direct Care– functions that enable hands-on delivery of health care and offer

clinical decision support.

• Care Support– functions that are not used for direct care of patients, but assist

with the administrative, financial, research, public health, and quality monitoring aspects of an EHR-S

• Information Infrastructure– functions that provide the framework for proper operation of all

Direct Care and Supportive functions.

HL7 EHR System Functional Model. Draft May 2006

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Direct Care Functions

• DC.1 Care Management – ordering medications– creating clinical documentation

• DC.2 Clinical Decision Support– alerting the provider that immunizations are due or

drug interactions are indicated. • DC.3 Operations Management and

Communication– ???

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Care support functions

• S.1 Clinical Support

• S.2 Measurement, Analysis, Research and Reports

• S.3 Administrative and Financial– verifying insurance eligibility – reporting encounter data to public health systems

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Information Infrastructure Functions

• Information Infrastructure– I.1 Security– I.2 Health Record Information and Management– I.3 Identity, Registry, & Directory Services– I.4 Terminology Standards & Services– I.5 Standards-based Interoperability– I.6 Business Rules Management– I.7 Workflow Management

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‘Terminology’

1) The discipline of terminology management– homonymous with terminology– synonymous with terminology work (used in ISO

704)

2) The set of designations used in the special language of a subject field, such as the terminology of chemistry

– Used in in both the singular and plural– Used with an article in the singular: a terminology

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Fundamental Activities of Terminology Work

• Identifying ‘concepts’ and ‘concept relations’;– Analyzing and modeling concept systems on the basis of

identified concepts and concept relations;

– Establishing representations of concept systems through concept diagrams;

– Crafting concept-oriented definitions;

– Attributing designations (predominantly terms) to each concept in one or more languages; and,

– Recording and presenting terminological data, principally in terminological entries stored in print and electronic media (terminography).

This is not the right approach to ontology !

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Reason for our rejection: The terminological View• Objects

• perceived or conceived, concrete or abstract• abstracted or conceptualized into concepts

• Concepts• depict or correspond to a set of objects based on a defined set of

characteristics• represented or expressed in language by designations or by definitions• organized into concept systems

• Designations• represented as terms, names (appellations) or symbols• designate or represent a concept• attributed to a concept by consensus within a special language

community

Terminology is a tool for dealing with language,not one for representing reality.

?

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Peirce, Ogden & Richards, …

Unit of Thinking (Concept)

Designation (Symbol, Sign,Term, Formulaetc.)

Referent(Concrete Object,Real Thing,Conceived Object)

(Unit of Thought, Unit of Knowledge)

~ Universal ???

Universal

Particular

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Success of concept-based view in healthcare IT

Concept ‘dog’

ChienDog

HondHund

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Why terminologies ?

• As such ?– Fixing/stabilizing the language within a domain and a

linguistic community;– Unambiguous communication.

• In relation to EHRs ?– Semantic Indexing;– Information exchange and linking between

heterogeneous systems;– Terminologies as basis for coding and classification

systems

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Some systems and their purpose• Remuneration

– ICD9/10-CM in US for insurance and medicare for diseases– Clinical Procedures Terminology (CPT) for surgical procedures

• Public Health Reporting– ICD9/10

• Clinical Recording– Read 1-3, SNOMED-CT, ICPC

• Indexing publications– MeSH (MedLine/PubMed), EMTree (EMBASE)

• Support for applications and decision support– GALEN, FMA

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‘Traditional’ semantic indexing

• Statement:– ‘ Joe Smith has a fracture of the left tibia ’

• Becomes indexed as :– #12 M-2xg41 A-2t68

– M-2xg41 code in SnowMeat with terms:– fracture, fractures, fracture NOS, broken, ...

– A-2t68 ibidem associated with:– left tibia, left tibia NEC, ...

– Additional terms through– hierarchy: bone, bones, os, ...– associations: lower leg, limb, body part, ...

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Classification: ICD• ...• Chapter II: Neoplasms (C00-D48)• Chapter III: Diseases of the Blood and Blood-forming organs and certain disorders

involving the immune mechanism (D50-D89)• Excludes : auto-immune disease (systemic) NOS (M35.9)• ....• Nutritional Anemias (D50-D53)• D50 Iron deficiency anaemia• Includes: ...• D50.0 Iron deficiency anaemia secondary to blood loss (chronic)• Excludes : ...• D50.1 ...• D51 Vit B12 deficiency anaemia• Haemolytic Anemias (D55-D59) • ...• Chapter IV: ...

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Coding versus classification

• Coding:– Annotate terms in the EHR with codes from a coding

system synonyms, translations, hierarchies

• Classification:– Assign patients exhibiting certain features to a

predefined class purpose oriented, culture dependent

• Frequently mixed up !

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Fracturednose

= ???

Fractureof

nose

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Coding / classification confusion

• “patient with fractured nose” =

“patient with fracture of nose”

• But therefor not “fractured nose”

=

“fracture of nose” !

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Classification: culture dependent

Dyirbal classification of objects in the universe,• Bayi: men, kangaroos, possums, bats, most snakes, most fishes,

some birds, most insects, the moon, storms, rainbows, boomerangs, some spears, etc.

• Balan: women, anything connected with water or fire, bandicoots, dogs, platypus, echidna, some snakes, some fishes, most birds, fireflies, scorpions, crickets, the stars, shields, some spears, some trees, etc.

• Balam: all edible fruit and the plants that bear them, tubers, ferns, honey, cigarettes, wine, cake.

• Bala: parts of the body, meat, bees, wind, yamsticks, some spears, most trees, grass, mud, stones, noises, language, etc.

Lakoff 1987. Women, fire and dangerous things

Categories derived through analysis of the structure of the language used by these people.

Language is NOT a thrustworthy basis for (realist) ontology development.

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The “exploding bicycle” (J. Rogers)• 10 things to hit…

– Pedestrian / cycle / motorbike / car / HGV / train / unpowered vehicle / a tree / other

• 5 roles for the injured…– Driving / passenger / cyclist / getting in / other

• 5 activities when injured…– resting / at work / sporting / at leisure / other

• 2 contexts…– In traffic / not in traffic

V12.24 Pedal cyclist injured in collision with two- or three-wheeled motor vehicle, unspecified pedal cyclist, nontraffic accident, while resting, sleeping, eating or engaging in other vital activities

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Border’s classification of Medicine• Medicine

– Mental health– Internal medicine

• Endocrinology– Oversized endocrinology

• Gastro-enterology• ...

– Pediatrics– ...– Oversized medicine

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Ambituous claims have been made …

• The Unified Medical Language System (UMLS) is designed to “facilitate the development of computer systems that behave as if they ‘understand’ the meaning of the language of biomedicine and health”.

UMLS fact sheet, updated 7 May 2004 (http://www.nlm.nih.gov/pubs/factsheets/umls.html).

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Mesh: Medical Subject Headings

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Mesh: Medical Subject Headings

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MeSH: typing myocardial infarction

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Hierarchical

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MeSH: Different context, different meaning ?

???

??????

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MeSH Tree Structures - 2004

• Body Regions [A01] – Extremities [A01.378]

• Lower Extremity [A01.378.610] – Buttocks [A01.378.610.100] – Foot [A01.378.610.250]

» Ankle [A01.378.610.250.149] » Forefoot, Human [A01.378.610.250.300] + » Heel [A01.378.610.250.510]

– Hip [A01.378.610.400] – Knee [A01.378.610.450] – Leg [A01.378.610.500] – Thigh [A01.378.610.750]

The most abundantsort of mistakes if used

as an ontology!

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Intermediate conclusion (1)

• Concept-based terminology (and standardisation thereof) is there as a mechanism to improve understanding of messages by humans.

• It is NOT the right device – to explain why reality is what it is, how it is organised,

etc., (although it is needed to allow communication), – to reason about reality, – to make machines understand what is real,– to integrate across different views, languages,

conceptualisations, ...

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Why not ?• Does not take care of universals and particulars

appropriately• Concepts not necessarily correspond to something that

(will) exist(ed)– Sorcerer, unicorn, leprechaun, ...

• Definitions set the conditions under which terms may be used, and may not be abused as conditions an entity must satisfy to be what it is

• Language can make strings of words look as if it were terms– “Middle lobe of left lung”

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Ok, then Description Logics and OWL will save us ... ?

Description logics:• A decidable fragment of FOL• A propositional modal logic• A classes and properties (concepts and roles) oriented

KR language• Subsumption and satisfiability (consistency) are the key

inferences• Most DLs are supersets of ALC

– Boolean operators on concepts– Existential and Universal quantifiers

• OWL-DL is a large superset (SHOIN):– Property hierarchies & Transitive roles (SH)– Inverse (I)– Nominals (O) (hasValue and one of)– Number restrictions (counting quantifiers)

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SNOMED and DL

SNOMED-RT (2000)

SNOMED-CT (2003)

DL don’t guarantee you to get parthood right !

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NCI Thesaurus

• a biomedical thesaurus created specifically to meet the needs of the National Cancer Institute.

• semantically modeled cancer-related terminology built using description logics

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NCI Thesaurus Root concepts

Anatomic Structure, Anatomic System, or Anatomic Substance ?Or ? Does the NCI not know to which categoryAny item classified there belongs ?Anatomic Substance ? If yes, why is geneproduct not subsumed by it ? If no, why aredrugs and chemicals not subsumed by it ?

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Definition of “cancer gene”

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Terminologies and ontologies for EHR use:

the quest for principles

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Requirements for clinical vocabularies (1)

• Domain completeness: coverage of all possible terms that lie within a vocabulary’s domain

• Non-vagueness: the term should represent the concept behind it as close as possible

• Non-ambiguity: the same term cannot refer to more than one concept

• Non-redundancy: each concept must be represented by one unique identifier

(Cimino, 1989)

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Requirements for clinical vocabularies (2)

• Synonomy: multiple ways for expressing a word (or concept) must be allowed

• Multiple classification: concepts must be allowed to be classified in multiple hierarchies

• Consistency of view: concepts must have the same relationships in all views

• Explicit relationships: all relationships (e.g. class, synonymy,…) must be explicitly labelled.

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The Desiderata Revisited

• Concept orientation - what is the alternative?• Concept permanence and graceful evolution - version

control• Formal definitions - add to knowledge vs. recognize

change• Reject NEC - store what the patient has and classify later• Multiple granularities - patient level vs. reuse• Representing context - the implicit meaning in the EMR

designCimino 2003, Rome Ontology Workshop (pushed by Smith)

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New desiderate for biomedical terminologies

• Provide identifiers for meanings we want to apply to the patient

• Make sure the semantics are universally understood, separate from linguistics

• Make sure that, as our understanding changes, original meaning is not forgotten

• Provide a bridge between what we record and how we reason

Cimino 2003, Rome Ontology Workshop (pushed by Smith)

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Desiderata for Controlled Medical Data

I - Capture what is known about the patient

II - No information loss

III - No false implications

IV - Support retrieval

V - Support reuse

VI - Support aggregation

VII - Support inferenceCimino 2003, Rome Ontology Workshop (pushed by Smith)

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Take off of ontology in biomedical informatics

• Concept/terminology-based systems make implicit knowledge explicit

• Ontologies aim to push explicitness further:– reasoning by machines

• Classification

• Prediction

• Triggering of alerts

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A practical example• At <timestamp> lab reports <procedure> with id <ID>

and value <value> for <patient>• At <timestamp> <clinician> interprets <ID> as

indicating <condition> for <patient>

• At <timestamp> <clinician> orders pharmacy item <formulary item> with order id <ID> for <patient>

• At <timestamp> pharmacy delivers <inventory item> with inventory id <ID> for order id <ID> for <patient>

• At <timestamp> decision support system suggests <condition> for <patient>

Cimino 2003, Rome Ontology Workshop

However !

Is this a procedure or the documentation of

a procedure ?Is this condition really a patient condition or just

an idea ?How are these related ?

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The dispute between …

• “Practical engineers”:– If it works for our purposes, it is ok

• Good philosophers:– If it works always, it is ok, and– It can only always work if it represents the relevant

portion of reality faithfully.

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Ontology desiderata (C. Goble) for engineersPrecision

formal, unambiguoushigh fidelity

Systematiccontrol, quality, clarity

Explicitnessclarity, commitment,

reuse

Flexibilityexpressivity, evolution

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Ontology description space (C. Goble)Coverage

upper, domain general, domain specific

Expressivitytaxonomy, relationships, axioms

Knowledge representation languages and

modelswords, OO, frames,

logics

Inference mechanismsclassification, coherency

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But not to forget: change management

The reasons for changes in ontologies AND health records should be explicitly motivated, possibilities being

1. changes in the underlying reality (does the appearance or disappearance of an entry relate to the appearance or disappearance of entities or of relationships among entities in reality?);

2. changes in our scientific understanding;

3. reassessments of what is considered to be relevant for inclusion ;

4. corrections of encoding mistakes introduced during ontology curation or data entry

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Conclusions• Main role of:

– Terminologies: standardise language use– Ontologies: represent what is generic in reality– EHR: document what is specifically related to particulars

(patients directly, (sub)populations indirectly)

• Role of terminologies in the context of the EHR:– Make the documentation intelligable to humans other than those

who entered the data

• Role of ontologies in the context of the EHR:– Ensure that the regimentation imposed by the EHR system does

not interfere with the re-usability of the data for a variety of purposes, other than patient documentation.