a common ground theory of medical decision-making 2: the knowledge ladder john fox department of...

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A common ground theory of medical decision-making 2: The knowledge ladder John Fox Department of Engineering Science University of Oxford and OpenClinical

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A common ground theory of medical decision-making

2: The knowledge ladder

John Fox Department of Engineering Science

University of Oxford and OpenClinical

Knowledge based systems and theories of knowledge

• Expert systems– “a piece of software which uses databases of expert knowledge to

offer advice or make decisions in such areas as medical diagnosis”

• Knowledge based systems– “A KBS is a computer program that reasons and uses knowledge

to solve complex problems”

• Knowledge representation– “use of symbols … in a conceptual model of the world; symbols

are arranged in order to form semantic constructions and express relations between concepts”

Knowledge engineering

• Representation and formalisation of knowledge– Domain specific and general knowledge– Theory and semantics of concepts and ontologies

• Knowledge acquisition– Elicitation of knowledge from human experts – Semi-automatic methods (e.g. machine learning)

• Symbolic processing techniques– Computational architectures for knowledge processing– Practical tools for creating and maintaining knowledge

bases

PROforma: A knowledge representation language for decision engineering

• A general notation for modelling clinical processes

• Grounded in a logical theory of decisions, plans and knowledge

• Applications are composed out of a minimal set of generalised task models

Fox et al, Proc. MIE 1996;Fox and Das, MIT Press, 2000

Sutton and Fox JAMIA, 2003

OpenClinical.net: a repertoire of medical compositions

Formalising and sharing knowledge

Source content

Trials, systematic reviews, guidelines,

evidence

Point of care

e.g. Routine care, clinical research, patient services

Machine executablemodels of practice

PROforma+

Open access, open source repository

Repertoire

The CREDO stack

The medical knowledge ladder

Concepts

Terms

Descriptions

Rules

Decisions

Plans

Agents

WHO International classification of diseases

Terms

Primary healthcare

Information Support

Otherhealthcare

related classifications

3-character core

• Diagnoses• Symptoms• Abnormal Lab findings• Injuries and poisonings• External causes of morbidity and

mortality• Factors influencing health status

Speciality codes

• oncology• dentistry• dermatology• psychology• neurology• obstetrics & gynaecology• rheumatology &

orthopaedics• general medical practice

International Nomenclature

of Diseases

SNOMED Systematized NOmenclature of MEDicine

• A general purpose, comprehensive medical terminology

• Computer-readable standard• Representing and indexing “virtually all of the

events found in the medical record”• SNOMED CT (Clinical Terms) is being widely

promoted as a global language (English)

Concepts

Terms

Concepts

• Formalisms for organising and formalising the meaning of concepts in a domain

• Domain concepts linked together in a network using relations characteristic of the domain

• Class hierarchies – Inheritance of attributes over classes

Ontologies and descriptions

• Capture common understanding of the meaning of information – Between people, computers, both

• Enable sound techniques for reasoning, decision-making, planning, learning … by computers

• Introduce standards across medical specialties • Enable trustworthy use and reuse of domain

knowledge

Concepts

Terms

Ontologies and descriptions(compare semantic networks, dependency graphs, BNs)

Descriptions

Cancer

Breast cancer

IS_A

Chemotherapy

Radiotherapy

Treatments

IS_A

IS_A

Symptoms

Lump

Weight loss

IS_A

IS_A

causes

caused_by

Patient1 Patient2

instanceinstance

Concepts

Terms

Descriptions

Rules

Rule-based decision support

if last_creatinine is not present thenalert_text := "No recent creatinine available.

Consider ordering creatinine before giving IV

contrast.";conclude true;

elseif last_creatinine > 1.5 thenalert_text := ”This patient has an elevated

creatinine.Giving IV contrast may worsen renal

function." ;conclude true;

else conclude false;endif;

Reasoning over ontologies

if Subclass is a kind of Class andProperty is a property of Class

then Property is a property of SubClass

If Disease is a cause of Symptom andPatient has Symptom

then possible diagnosis of Symptom in Patient is Disease

Description logics

• Descriptions of medical facts and clinical data stated in propositional sentences in some L

• First order predicate calculus is a commonly used and versatile/powerful tool for reasoning over ontologies and descriptions

• Known to be computationally intractable in worst case – do not need all the power of FOPC; – adopt simpler axioms with more favourable

computational properties– http://en.wikipedia.org/wiki/Description_Logics

PROforma “task” ontology

Concepts

Terms

Descriptions

Terms to descriptions

Concepts

Terms

Descriptions

Rules

Rules in PROforma

Concepts

Terms

Descriptions

Rules

Decisions

PROforma decision engineering

Concepts

Terms

Descriptions

Rules

Decisions

PROforma decision model

Concepts

Terms

Descriptions

Rules

Decisions

Plans

Decisions in context: workflows, care plans and pathways

Kinds of decision-making and expertise

Concepts

Terms

Descriptions

Rules

Decisions

Plans

Agents

https://en.wikipedia.org/wiki/Expert_system

Conclusions

• Understanding medical expertise requires general models for reasoning, decision-making, planning etc (of course)

• … but a key (the largest?) component of medical expertise is what the expert knows

• AI and knowledge representation research have shown that knowledge is semantically complex but systematically structured

• Theories of knowledge and techniques of knowledge engineering open up exciting possibilities for formalising and sharing medical expertise and exploring new techniques for improving decision-making and the quality and safety of common medical practice

Conversations are two way…

• OpenClinical.net is based on a kind of publishing model (compare Wikipedia)

• Question to behavioural scientists - how can we engage the stakeholders to use it?– Professionals– Patients– Providers

• “The problem is in the implementation” … incentives, bonuses, payoffs, …?