an old problem

1O p en G A L E N CO-ODE/HyOntUse

Making Terminologies useful and usable:Making Terminologies useful and usable:Clinical Terminologies in the 21Clinical Terminologies in the 21stst Century: Century:

What are they for? What might they look like?What are they for? What might they look like?

Alan RectorAlan Rector

Bio and Health Informatics Forum/Bio and Health Informatics Forum/Medical Informatics GroupMedical Informatics Group

Department of Computer ScienceDepartment of Computer ScienceUniversity of ManchesterUniversity of Manchester

[email protected]@cs.man.ac.ukwww.cs.man.ac.uk/mig img.man.ac.ukwww.cs.man.ac.uk/mig img.man.ac.uk

www.clinical-escience.orgwww.clinical-escience.orgmygrid.man.ac.ukmygrid.man.ac.uk


An Old ProblemAn Old Problem

“On those remote pages it is written that animals are divided into:

a. those that belong to the Emperor b. embalmed ones c. those that are trained d. suckling pigse. mermaids f. fabulous ones g. stray dogs h. those that are included in this classificationi. those that tremble as if they were mad j. innumerable ones k. those drawn with a very fine camel's hair brush l. others m. those that have just broken a flower vase n. those that resemble flies from a distance"

From The Celestial Emporium of Benevolent Knowledge, Borges


But why in healthcare?But why in healthcare?

• What’s it for? What’s the purpose?– Terminologies are of little use in

themselves• How will it make care better? new things

possible?• How will it make information systems better?

– Painful experience of 20 years of over-selling and under performance

• Do we need it: Clinically? Technically?– If we need it

• what is ‘it’? Is ‘it’ one thing or many?• How will we know if we have ‘it’?• How will we know if ‘it’ is fit for purpose


Why Now?Why Now?

• What’s different now?– Web, E-Science, Grids

• Web speed• New technologies – OWL, new DLs, hybrid frame-DL

environments www.semanticweb.org

– Post genomic medicine – personalised medicine• Joining up Healthcare Medical and Bioscience research –

CLEF

– Systemisation of healthcare• Clinical error reduction, clinical governance, Clinical error reduction, clinical governance,

evidence based medicine, …evidence based medicine, …

• Does anybody else have similar problems?– Ontologies are ‘flavour of the month’ in E-Science

& Web• Bioinformatics is building them very rapidly

– What can we learn from them?


A Convergence of NeedA Convergence of Need

• Post genomic research

Knowledge is Fractal

• Safe, high quality, evidence based health care

Need more and better clinical information

• Which scales– In Size– In Complexity


The requirements & Tools chainThe requirements & Tools chain

• Clinical users with needs to improve care / clinical knowledge

• Applications for clinical users that meet those needs

• Developers’ needs for terminology to build those applications

• Terminologies which fit the applications’ builders’ needs to meet the clinical users’ needs


Who is it for?Who is it for?(Useful & usable to whom?)(Useful & usable to whom?)

• Clinical users – Carers - prospective– Reviewers – retrospective

• Researchers, managers, assessors, …– The community – how it shares its knowledge

• Knowledge creators / distributors

• Application developers– Easier to re-use what exists than to build new– Re-use or bust

• Terminology authors– Quick responsive evolution


Useful and UsableUseful and Usable

• Useful – for what?– Supports needed applications

• Purpose

– Does it well• Quality

• Usable – by whom?– Intuitive / understandable– Handy

• What you need is “to hand”

– Timely


Preview of ArgumentsPreview of Arguments

• The priorities are clinical needs supported by applications supported by terminology

• Clinical quality is critical

• Useful and usable to: clinical users, developers, ‘reviewers’, authors

• In an open evolving world, open managed evolution is the only plausible way forward

• Current technology gives us the opportunity to cope

• Tools and environments are as important as content


Where we come from Where we come from

Best Practice

Clinical Terminology

Data EntryPEN&PAD

Clinical Record

Decision Support

Best Practice

Data EntryLanguage

Technology:CLEF

Electronic Health

Records:CLEF

Decision Support &Aggregated

Data

GALEN Clinical Terminology

HealthCard

Mr Ivor BigunMr Ivor BigunDun RoaminDun RoaminAnytownAnytownAny countryAny country4431 3654 902734431 3654 90273

O p en G A L E N CO-ODE/HyOntUse

Terminology is Now MiddlewareTerminology is Now Middlewarehuman-machine / machine - machinehuman-machine / machine - machine

• Explicit– Machines can only manipulate what is represented

explicitly• More re-use more manipulation more explicitness

• Understandable– People can only build, maintain and use it if they can

understand it

• Adequate– Expressive enough to do the job but still

computationally tractable

• Reliable– People can use it consistently

• Scalable and maintainable


Where we think we are going: Where we think we are going:

• Pre-1980: paper– Application specific retrospective human oriented

systems• ICD, early SNOMED, CPT, OPCS, …

• Mid 1980s – 1990s: “electronic paper”– Retrospective reporting + Prospective collection

ICPC Read I, II

• Mid 1990s – mid 2000s:Centralised computer based – Retrospective reporting + Prospective collection

OpenGALEN, Read III, SNOMED-RT…PEN&PAD

• Mid 2000s – ?: Web based open managed evolution– ???? – but see the Semantic Web, Gene Ontology, etc.


How we will know when we get How we will know when we get therethere

Criteria for successCriteria for success• Re-use

– A recognised growing library of common decsision support modules

• Stop starting from scratch!Stop starting from scratch!

• Integration– 2+ independently developed DSSs

integrated with2+ independently developed EPRS withoutexponentially increasing effort.


Criteria for successCriteria for success

• Authoring– No individual invests in their own

terminology• enterprise-wide terminology servers

• Indexing– Simplification of systems

• a sharp drop in special cases and exceptions

• a sharp increase in authors’ productivity


Criteria for successCriteria for success

• User interfaces – Real systems in real use with real

patients by real clinicians• transparent systems


Stones in the RoadStones in the Road

• Why are we not there yet?

– Some background definitions

– Some hypotheses


Clinical quality & logical qualityClinical quality & logical quality

• Clinical quality – do users put in the right things? – Repeatability of information captue (inter rater

reliability)• For decision support in prospective use• For retrieval in retrospective use

– Salience • Relevance to clinical decisions for prospective use• Significance to questions for retrospective use

– A better measue than “coverage”

• Logical quality – do systems give the right responses? – Correct organisation (classification)

• Correct inferences given correct input


Hypothesis 1Hypothesis 1

• Most computer oriented terminology development ignores clinical quality …– The EHR as black hole

• Bigger is not necessarily better

…although clinical quality was the primary concern of traditional paper/human oriented terminologies(and there are honourable exceptions – e,g, ICPC).

– Evidence: High variability in recorded use Systematic failure to use data from GP systems in clinical studies (despite PRIMIS) Our own & colleagues’ experience in repeated studies Current planned cost of cohort ‘post genomic’ studies


Three modelsThree models

• Meaning - ontologies– Can I depend on the answers?

• “Dyspnoea is a respiratory problem”

• Clinical significance – decision support– What should I think of / how does it affect

decisions• “Dyspnoea can be a symptom of congestive heart

failure”

• Model of use – EHR/human factors– Is what I want ‘to hand’ – is it ‘handy’?”

• “Dyspnoea should be a question on a cardiac history”



• Early terminologies emphasised models of use and significance and failed for lack of model of meaning– “Heart diseases” are in 13 Chapters of ICD9

• Recent terminologies emphasise model of meaning and fail for lack of models of use and significance– Evidence:

• User dissatisfaction, non-use, and poor quality data• The few systems based on models of use have been

surprisingly popular with doctors, e.g. MedCin, ORCA– But hard to use for retrieval

• We have fewer formal models of use than of meaning– We have almost no models of ‘significance’


Grounding cost vs Clean-up costGrounding cost vs Clean-up cost(with thanks to Enrico Coiera)(with thanks to Enrico Coiera)

• “Grounding cost”– The cost of establishing a given quality

of communication• How much French do you need to order a

meal?

• “Clean up cost”– The cost of fixing miscommunication

• How many surprises will you accept? of what kind?


Special purpose vs Re-usable Special purpose vs Re-usable MultipurposeMultipurpose

• Special purpose terminologies– Almost all retrospective

• Reporting for remuneration – ICD9-CM, CPT• Reporting for epidemiology - ICD10, OPCS

• Multipurpose re-usable terminologies – Aspire to be the glue for ‘Patient centred

systems’ & ‘Personalised Medicine’• Decision support• Electronic Health Records• Research • Integration with Bioscience• …

– But too often ‘multipurpose’ means ‘no purpose’ ‘multiapplication’ means ‘no application’


Need “Multipurpose” mean “no Need “Multipurpose” mean “no purpose”?purpose”?

• Multiple purposes held by multiple groups – Multiple sources of expertise & authority

• One size does not fit all

– Multiple collaborations• Multiple legacies

• Multiple purposes use multiple applications– Applications are the point of interaction

• Applications make needs concrete & testable


Multipurpose means interacting with Multipurpose means interacting with othersothers

It’s a big open world out there…It’s a big open world out there…• Bioscience

– Gene Ontology, National Cancer Institute Center for Bioinformatics (NCICB), The Digital Anatomist/ Mouse Anatomy/Mammalian Anatomy, BioJava,PRINTS, EMBL, Microarrays, Protemoics, Metabalomics, Systems Biology…

• Medicine meets bioscience– Cancer therapeutics, New imaging, …

• E-Health: sharing and pooling data: Collections based research”– BioBank, NTRAC, NCRI, NCTR, CLEF, …– “Health Intelligence”– MRC policy on data sharing– …



• Grounding costs can be delimited for special purpose terminologies

• Grounding costs are indefinite for re-usable terminologies (& is historically high)– Without purposes testable through

applications there– Danger of the escalating deadly embrace

• “Must have terminology to build applications; but Must have applications before terminology”

– Evolutionary approach the only exit


Central Control vs Central Control vs Open managed evolutionOpen managed evolution

• Académie française vs Oxford English Dictionary– Scholasticism vs Empiricism

• The ‘arrogance of the a prior’People don’t know what they do

• Look to see what is actually used» Language technology shows time and again

that our predictions are faulty

– Command economy vs Social Market

• Participation is the issue rather than money– Somebody will still have to pay

• But at least they might pay for something useful


Central managementCentral management

• Owned by one “Authority”

• Coupling tight / autonomy low/ participation low

• “Grounding costs” high / “Clean up costs” low?– must have everything before you can do

anything

• Change slow & lockstep

• A product


Open managed evolutionOpen managed evolution

• “Owned” by the community – multiple “authorities”

• Coupling loose/ autonomy high / participation high– To be useful & usable involve users using systems

• “Grounding costs” low / “Clean up costs” high?– “Just in time” “Just enough”

• Agree where it counts

• Change quick and local - “threaded with annealing”

– A process


Hypotheses 4Hypotheses 4a) Single purpose clinical terminologies can be best

managed centrally– By definition are developed in conjunction with an

application

b) Re-usable terminologies can only succeed by open managed evolution– Many purposes require many contributors

• Evidence: Speed of uptake of HL7/LOINC W3C & the evolution of the Web

c) Re-usable terminologies can only be developed in open collaboration with applications– Otherwise “multipurpose” become “no purpose”



• Modern technology provides the means to support open managed evolution without compromising clinical quality or technical stability– Trade lower grounding cost for greater clean up

cost– Focus on minimal stable core. Defer

commitments.• Evidence: OpenGALEN, Gene Ontology

– Utilise Web/Grid technologies for rapid dissemination and coordination

• Evidence: Current developments at Mayo clinic using LDAP

– Distribute terminology like domain names


The technologiesThe technologies• Applications centric development

Decoupled development– Special purpose languages / “Intermediate Representations”

• Deferred commitment• Clinical before technical

• Logic based ontologies + – Models of clinical significance– Models of clinical use– Models of EHRs

• Web services & Grid technology – Authentication/authorisation/accounting– Distributed directories & LDAP– Service discovery


Decoupled development using Decoupled development using “Conceptual Lego”“Conceptual Lego”

• If we manage the connectors and the pieces the users can build most things for themselves– Without compromising quality


Common Terminology/Ontology

clinicalapplications

authoringenvironmentsIntermediate Representations

clinicians / Applications buildersEmpowered Authors

templates/

views

templates/

views

Applications centric DevelopmentApplications centric Development

Meta-authoringMeta-authoring


Loosely Coupled DevelopmentLoosely Coupled Development

LocalOntology

Local Authorneeds new terms for application

Server validates &organises

CentralOntology

Central Gurusintegrate & fix problems

Local authoruses resources & templates to formulate definition

templates

WorldwideResources

Local authorchecks

problems

updates


The templates are more The templates are more important than the underlying important than the underlying

formalism…formalism…"Open fixation of a fracture of the neck of the left femur"

MAIN fixingACTS_ON fracture

HAS_LOCATION neck of long boneIS_PART_OF femur

HAS_LATERALITY leftHAS_APPROACH open

““Intermediate Representations” Intermediate Representations” are criticalare critical


……complex underpinnings can &will complex underpinnings can &will changechange

hasSpecificSubprocess (‘SurgicalAccessing’

hasSurgicalOpenClosedness (SurgicalOpenClosedness which

hasAbsoluteState surgicallyOpen))

(‘SurgicalProcess’ which

isMainlyCharacterisedBy (performance which

isEnactmentOf (‘SurgicalFixing’ which

actsSpecificallyOn (PathologicalBodyStructure which <

involves Bone

hasUniqueAssociatedProcess FracturingProcess

hasSpecificLocation (Collum which

isSpecificSolidDivisionOf (Femur whichhasLeftRightSelector leftSelection))>))))


Decoupling & FlexibilityDecoupling & Flexibility

• Use formality to permit flexibility– Change need not mean instability

• Formality means effects can be predited

– Most users only need change in tightly controlled areas

• Lesson from the Semantic Web:“Forking” a natural part of development– Harmless if strictly local – Manageable if controlled from standard “Lego” &

templates• “Clean up cost”

– 10%-20% central effort is a reasonable target

– Necessary to cope with change and ignorance• Evolution by “annealing”


Scalable models of useScalable models of use


FRACTURE SURGERY FRACTURE SURGERY

Scalable models of Use: Scalable models of Use: PEN&PADPEN&PAD

Structured Data Entry

File Edit Help

TibiaTibia FibulaFibula AnkleAnkle More...More...

RadiusRadius UlnaUlna WristWrist More...More...HumerusHumerus

FemurFemur

LeftLeft RightRight

More...More...Gt TrochGt TrochShaftShaft NeckNeck

FemurFemur

LeftLeft

NeckNeck

ReductionReduction FixationFixation

OpenOpen ClosedClosedOpenOpen

FixationFixation

250,000 forms from 10,000 Facts“Fractal tailoring”


Idiopathic Hypertensionin Study a phase 2

Idiopathic Hypertensionin our co’s phase 2 study a

Scalable models of use:Scalable models of use:Fractal tailoring forms for clinical trialsFractal tailoring forms for clinical trials

Hypertension

Idiopathic Hypertension

In our company’s studies

In Phase 2 studies

Hypertension

Idiopathic Hypertension`

In our company’s studies

In Phase 2 studies


It can workIt can work

• The Lessons of GALEN – Loosely coupled development based on formal

ontologies works• “Coherence without uniformity”• 90% of work done locally

– Ontologies can be modular rather than monolithic• “Plug and play” terminology development

• The Lessons of PEN&PAD– Models of use based on formal ontologies scale

• 250,000+ forms from 10,000 ‘facts’

• The Lessons of the Semantic Web– It works for knowledge management– Growing user community outside of medicine

• No longer “rocket science”


So what areSo what are“Logic based ontologies”“Logic based ontologies”


Logic-based Ontologies: Logic-based Ontologies: Conceptual LegoConceptual Lego

“SNPolymorphism of CFTRGene causing Defect in MembraneTransport of ChlorideIon causing Increase in Viscosity of Mucus in CysticFibrosis…”

“Hand which isanatomicallynormal”


Logic based ontologiesLogic based ontologies

• A formalisation of semantic nets, frame systems, and object hierarchies via KL-ONE and KRL

• “is-kind-of” = “implies” (“logical subsumption”)– “Dog is a kind of wolf”

means“All dogs are wolves”

• Modern examples: DAML+OIL /“OWL”?)• Older variants LOOM, CLASSIC, BACK, GRAIL, K-REP, …


Encrustation

+ involves: MitralValve

Thing

+ feature: pathological

Structure

+ feature: pathological

+ involves: Heart

Logic Based Ontologies: The basicsLogic Based Ontologies: The basics

Thing

Structure

Heart MitralValve EncrustationMitralValve* ALWAYS partOf: Heart

Encrustation* ALWAYS feature: pathological

Feature

pathological red

+ (feature: pathological)

red

+ partOf: Heart

red

+ partOf: Heart

Primitives Descriptions Definitions Reasoning Validating(constraining cross products)


Building with Conceptual Building with Conceptual LegoLegoGenesSpecies

Protein

Function

Disease

Protein coded by(CFTRgene & in humans)

Membrane transport mediated by (Protein coded by (CFTRgene in humans))

Disease caused by (abnormality in (Membrane transport mediated by (Protein coded by (CTFR gene & in humans))))

CFTRGene in humans


Avoiding combinatorial explosionsAvoiding combinatorial explosions

• The “Exploding Bicycle” From “phrase book” to “dictionary + grammar” – 1980 - ICD-9 (E826) 8 – 1990 - READ-2 (T30..) 81– 1995 - READ-3 87– 1996 - ICD-10 (V10-19 Australian) 587

• V31.22 Occupant of three-wheeled motor vehicle injured in collision with pedal cycle, person on outside of vehicle, nontraffic accident, while working for income

– and meanwhile elsewhere in ICD-10• W65.40 Drowning and submersion while in bath-tub, street

and highway, while engaged in sports activity

• X35.44 Victim of volcanic eruption, street and highway, while resting, sleeping, eating or engaging in other vital activities


The Cost: Normalising (untangling) The Cost: Normalising (untangling) OntologiesOntologies

StructureFunction

Part-wholeStructure Function

Part-w

hole


The Cost: Normalising (untangling) The Cost: Normalising (untangling) OntologiesOntologies

Making each meaning explicit and separateMaking each meaning explicit and separatePhysSubstance Protein ProteinHormone Insulin Enzyme Steroid SteroidHormone Hormone ProteinHormone^ Insulin^ SteroidHormone^ Catalyst Enzyme^

Hormone = Substance & playsRole-HormoneRoleProteinHormone = Protein & playsRole-HormoneRoleSteroidHormone = Steroid & playsRole-HormoneRoleCatalyst = Substance & playsRole CatalystRoleInsulin playsRole HormoneRole

…build it all by combining simple trees

Enzyme ?=? Protein & playsRole-CatalystRole

PhysSubstance Protein ‘ ProteinHormone’ Insulin ‘Enzyme’ Steroid ‘SteroidHormone’ ‘Hormone’ ‘ProteinHormone’ Insulin^ ‘SteroidHormone’ ‘Catalyst’ ‘Enzyme’

… ActionRole PhysiologicRole HormoneRole CatalystRole …

… Substance BodySubstance Protein Insulin Steroid …


But none of it works without But none of it works without toolstools

None of it works without None of it works without communication & cooperationcommunication & cooperation


Communicating software Communicating software environments environments “Environments” rather than “Environments” rather than

“servers”“servers”

• Clinical users - care and review – Environments for entering& retrieving information– Methodologies for measuring and monitoring quality of

information– Human factors, language technology, fractal tailoring to

needs

• Application developers– Configuration tools – much more than “terminology servers”

• The key to success

• Ontology authors– Tools for distributed loosely coupled authoring

• Ontology managers (the “gurus”)– Tools for reconciliation, change management, &

meta-authoring of templates


Summary of ArgumentsSummary of Arguments• The priorities are clinical needs supported by applications

supported by terminology– Unless they serve clinical needs, applications are useless– Unless they serve applications, terminologies are useless– Unless used reliably, terminologies are meaningless

“Meaning is a social construct”

Clinical quality should be our watchword

• Useful and usable to: clinical users, developers, ‘reviewers’, authors– Requires models of use & clinical significance– Requires tools and environments

• In an open evolving world, open managed evolution is the only plausible way forward– Participation and control are the issues – not money

• Current technology gives us the opportunity to cope– If we let development follow need

• If we use them to the full– 19th century methods won’t cope with 21st century problems


Making Terminologies useful and usable:Making Terminologies useful and usable:Clinical Terminologies in the 21Clinical Terminologies in the 21stst Century: Century:

What are they for? What might they look like?What are they for? What might they look like?

Alan RectorAlan Rector

Bio and Health Informatics Forum/Bio and Health Informatics Forum/Medical Informatics GroupMedical Informatics Group

Department of Computer ScienceDepartment of Computer ScienceUniversity of ManchesterUniversity of Manchester

[email protected]@cs.man.ac.ukwww.cs.man.ac.uk/mig img.man.ac.ukwww.cs.man.ac.uk/mig img.man.ac.uk

www.clinical-escience.orgwww.clinical-escience.orgmygrid.man.ac.ukmygrid.man.ac.uk

an old problem

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