Medical informaticsLecture 2

Formalising clinical data and medical knowledge, Clinical coding systems, Formal knowledge representation… if time … formalising research

results

Creating and using medical knowledge

Understanding

diseases and their

treatment

Understanding

diseases and their

treatment

Ensure rightPatients receiveright

intervention

Ensure rightPatients receiveright

intervention

Service delivery,

performance

assessment

Service delivery,

performance

assessment

Develop and test

treatments

Develop and test

treatments

HealthRecords

… using medical knowledgeUnderstandin

gdiseases and

their treatment

Understanding

diseases and their

treatment

Ensure rightPatients receiveright

intervention

Ensure rightPatients receiveright

intervention

Service delivery,

performance

assessment

Service delivery,

performance

assessment

Develop and test

treatments

Develop and test

treatments

HealthRecords

Standardising clinical terms

• Very difficult to use ordinary medical language in computer systems – Extremely complex vocabulary.– Terms often vague and imprecise.– Same disease known by several names or

expressions (synonymy).– A single term may have several meanings

according to the context (polysemy).

• Addressed by adopting formal coding and classification systems.

Formal coding and classification systems

• Different systems use same code or term in same way– Unique codes, precisely defined coding process

• Benefits include abilities to– Share data between many systems– Gather data about diseases/treatments from many sources.– Deliver reminders, alerts and other information to clinicians

based on standardised clinical patterns or situations– Identify eligible patients for recruitment into clinical trials

based on well-defined criteria– Search professional literature based on standard queries

• … and many other benefits

Coding systems

• International Classification of Diseases (ICD)• Diagnosis Related Groups (DRGs)• Standard Nomenclature for Medicine (SNOMED) • Logical Observation Identifiers Names and Codes

(LOINC)• Medical Subject Headings (MeSH)• Specialised coding systems

– National Cancer Institute– Centre for Disease Control – …

WHO ICD

• The International Classification of Diseases has been used since 1853 to classify diseases and other health problems recorded on many types of records, including death certificates and health records

• In addition to enabling the storage and retrieval of diagnostic information for clinical, epidemiological and quality purposes, ICD also provides a basis for the compilation of national mortality and morbidity statistics by WHO Member States (e.g. AIDS, “swine flu”).

International Classification of Diseases

I. Certain infectious and parasitic diseasesII. NeoplasmsIII.Diseases of the blood and blood-forming organs, immune

mechanismIV.Endocrine, nutritional and metabolic diseasesV. Mental and behavioural disordersVI. Diseases of the nervous systemVII. Diseases of the eye and adnexaVIII.Diseases of the ear and mastoid processIX. Diseases of the circulatory systemX. Diseases of the respiratory systemXI. Diseases of the digestive systemXII. Diseases of the skin and subcutaneous tissueXIII.Diseases of the musculoskeletal system and connective tissueXIV. Diseases of the genitourinary systemXV. Pregnancy, childbirth and the puerperiumXVI. Certain conditions originating in the perinatal periodXVII.Congenital malformations, deformations and chromosomal abnormalitiesXVIII.Symptoms, signs and abnormal clinical and laboratory findings, not elsewhere classifiedXIX. Injury, poisoning and certain other consequences of external causesXX. External causes of morbidity and mortalityXXI. Factors influencing health status and contact with health servicesXXII.Codes for special purposes

ICD family of disease and health related classifications

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

ICD-10

• Uses an alphanumeric code that indicates the location of the concept within a disease hierarchy.

• L93 Lupus erythematosus. •Excludes exedens A18.4, vulgaris A18.4 . . . •Use additional external cause code, if drug

induced.

– L93.0 Discoid lupus erythematosus – L93.1 Subcutae cutaneous lupus

erythematosus

Diagnosis Related Groups

• DRGs developed for relating the type of patients a hospital treats (“case mix”) to treatment costs

• All discharged patients in US classified into a DRG– a limited, clinically coherent set of patient classes – based on age, sex, principal diagnosis, secondary

diagnoses, surgical procedures, and discharge status

• All patients are unique but groups of patients have common demographic, diagnostic and therapeutic attributes that determine resource needs.

DRGs1 HYPERTENSIVE ENCEPHALOPATHY2 23NONTRAUMATIC STUPOR & COMA24 SEIZURE & HEADACHE AGE >17 WITH COMPLICATIONS,

COMORBIDITIES (prior to 10-1-06)25 SEIZURE & HEADACHE AGE >17 WITHOUT COMPLICATIONS,

COMORBIDITIES (prior to 10-1-06)26 SEIZURE & HEADACHE AGE 0-171 TRAUMATIC STUPOR & COMA, COMA >1 HR

2 TRAUMATIC STUPOR & COMA, COMA <1 HR AGE >17 WITH COMPLICATIONS, COMORBIDITIES

29 TRAUMATIC STUPOR & COMA, COMA <1 HR AGE >17 WITHOUT COMPLICATIONS, COMORBIDITIES

30 TRAUMATIC STUPOR & COMA, COMA <1 HR AGE 0-17 31 CONCUSSION AGE >17 WITH COMPLICATIONS, COMORBIDITIES 32 CONCUSSION AGE >17 WITHOUT COMPLICATIONS, COMORBIDITIES

The Systematized NOmenclature of MEDicine

(SNOMED)• Intended to be a general purpose,

comprehensive and computer-interpretable terminology

• To represent and index “virtually all of the events found in the medical record”

SNOMED code for tuberculosis

DE-14800 X-referencing

Tuberculosis Bacterial infections

E = Infections or parasitic diseases D = Disease or diagnosis

X-ref e.g. living organism, morphology, function

Logical Observation Identifiers Names and Codes (LOINC)

• A database and universal standard for identifying medical laboratory observations.

• Applies universal code names and identifiers to medical terminology

• For use in– gathering of clinical results (such as laboratory

tests, clinical observations, outcomes management and research)

– electronic data exchange– electronic health records

LOINC

• LOINC currently includes over 58,000 terms

• A unique 6-part name is given to each test or observation.

• Each database record includes six fields – Component- what is measured, evaluated, or observed

– Kind of property - e.g. length, mass, volume, time stamp

– Time interval over which observation or measurement made

– System - or specimen type within which observation was made

– Scale - quantitative, ordinal, nominal or narrative

– Method procedure used to make measurement or observation

Problems with coding systems

• Terms are subjective, often vague, imprecise

• Codes often ad hoc (e.g. no systematic relationship between code and medical concepts and their uses)– Context dependent (e.g. “normal BP”)– Evolve over time

• Mapping between systems difficult• Computers don’t “understand” them –

we need to capture meaning rather than use ad hoc codes

Formalising medical concepts

Understanding

diseases and their

treatment

Understanding

diseases and their

treatment

Ensure rightPatients receiveright

intervention

Ensure rightPatients receiveright

intervention

Service delivery,

performance

assessment

Service delivery,

performance

assessment

Develop and test

treatments

Develop and test

treatments

HealthRecords

Formalising medical concepts

Symbols

Concepts

Relationships

Rules

Models

breast cyst breast lump breast cancer

breast cancer IS_Areproductive system and breast disorder

DF-400DB

REPRODUCTIVE SYSTEM AND BREAST DISORDERS

IS_A

WOMAN WITH POSSIBLE BREAST CANCER HYPOTHESIS DISEASE OF THORAX

HAS-HEALTHCARE-PHENOMENON IS_A IS_A

IS_A BREAST FINDING

BREAST CANCER HYPOTHESISBREAST DISEASE

IS-HYPOTHESIS-OF IS_A IS-RANGE-OF-DOMAIN-OF

MALIGNANT NEOPLASM OF BREAST BREAST SPECIALIST

IS_A IS-SPATIAL-PART-OF

MALIGNANT NEOPLASM BREAST STRUCTURE

HAS-WE-STATE IS_A IS-CONSEQUENCE-OF IS_A

MALIGNANT NEOPLASM BREAST CANCER

IS_CREATIVE_RESULT_OF IS_A

NEOPLASTIC PROCESS ADVANCED BREAST CANCER ADVANCED

IS_A HAS-WE-STATE

HAS-HEALTHCARE-PHENOMENON IS_A

ADVANCED CANCER

CANCER PATIENT

IS_A IS_A

PATIENT BREAST CANCER PATIENT

Core Ontology

breast cancer IS_Areproductive system and breast disorder

SNOMED CT

ConceptConcept

DescriptionDescription

RelationshipRelationship

For example the concept "headache (finding)" in SNOMED CT includes:

• A conceptId (25064002), • A set of descriptions

("headache", "pain in head", etc.) • A set of relationships ("is a"="pain",

"finding site"="head structure", etc.).

A concept is described in one or more descriptions

All concepts (except the root) are the source of at least one ‘ISA’(subtype) relationships

Unified Medical Language System

Links the major international terminologies into a common structure, providing a translation mechanism between them.

Designed to aid in the development of systems that – retrieve and integrate electronic biomedical information

from a variety of sources – permit linkage between disparate systems, including

electronic patient records, bibliographic databases and decision support systems.

“UMLS is the Rosetta Stone of international terminologies”

A long term research goal is to enable computer systems to “understand” medical concepts.

UMLS semantic network

• The UMLS Semantic Network allows for the semantic categorization of a wide range of terminologies in multiple domains.

• Major groupings of semantic types include– organisms, – anatomical structures, – biologic function, – chemicals, – events, – physical objects, and – concepts or ideas.

• Links between semantic types represent important relationships in the biomedical domain.

UMLS Meta-thesaurus

• Uniform format for over 100 biomedical vocabularies and classifications

• Organised by concept as a web rather than a tree, linking alternative names and views together and identifying useful relationships.– Components retain original structure.– Each concept has attributes that define its

meaning (e.g. semantic types or categories to which it belongs, a definition).

Clinical concept

UMLS ICD-10 SNOMED SNOMED CT

Chronic ischaemic heart disease

448589 125.9 14020 84537008

UMLS semantic network

Links between semantic types represent important relationships in the biomedical domain. – Primary link: the isa link which establishes the hierarchy of types within the network – Secondary non-hierarchical relationships

grouped into five major categories: physically related to, spatially related to, temporally related to, functionally related to, conceptually related to.

UMLS semantic network

Content– For each semantic type:

a unique identifier, a tree number indicating its position in an isa hierarchy, a definition, and its immediate parent and children. – For each relationship:

a unique identifier, a tree number, a definition, and the set of semantic types that can plausibly be linked by this relationship.

Terms and ontologies

http://bioportal.bioontology.org/

Emulating clinical expertise

• “Expert” systems offer “an engineering discipline that involves integrating [human] knowledge into computer systems to solve complex problems normally requiring a high level of human expertise"

– Successful early demonstrations were developed in chemistry, medicine, various fields of engineering (e.g. Banares-Alcantara’s work on design of chem eng. plant).

• Key features distinguished expert systems from conventional software.

– Explicit, declarative representation of knowledge: capture what an agent needs to know without assuming how that knowledge is to be used in any particular situation.

– Domain-specific heuristics rather than general algorithms; said to resemble human expertise more closely than algorithmic methods.

Formalising medical concepts

Symbols

Concepts

Relationships

Rules

Models

Lump and pre-menopausal implies possible breast cancer

breast cyst breast lump breast cancer

breast cancer is_areproductive system and breast disorder

DF-400DB

CANCER SCENARIOREPRODUCTIVE SYSTEM AND BREAST DISORDERS

IS_AIS-CCC-OF IS_A

WOMAN WITH POSSIBLE BREAST CANCERWOMAN WITH POSSIBLE BREAST CANCER HYPOTHESIS DISEASE OF THORAX

IS_AHAS-HEALTHCARE-PHENOMENON IS_A IS_A

IS_A BREAST FINDING

BREAST CANCER HYPOTHESISBREAST DISEASE

IS-HYPOTHESIS-OF IS_A IS-RANGE-OF-DOMAIN-OF

MALIGNANT NEOPLASM OF BREAST BREAST SPECIALIST

IS_A IS-SPATIAL-PART-OF

WOMAN WITH A REFERABLE BREAST LUMP

MALIGNANT NEOPLASM BREAST STRUCTURE

HAS-WE-STATE IS_A IS-CONSEQUENCE-OF IS_A

MALIGNANT NEOPLASM BREAST CANCER STAGE I

IS_CREATIVE_RESULT_OF IS_A

NEOPLASTIC PROCESS ADVANCED BREAST CANCER ADVANCED

IS_A HAS-WE-STATE

HAS-HEALTHCARE-PHENOMENON IS_A

ADVANCED CANCER

CANCER PATIENT

IS_A IS_A

PATIENT BREAST CANCER PATIENT

Core Ontology

Fragment of breast cancer domain knowledge: M Beveridge CRUK; W Ceusters Language and computing NV

Formalising medical concepts

Symbols

Concepts

Relationships

Rules

Models

pre-menopausal woman has possible breast cancer (scenario)investigation of possible breast cancer (process)

breast cyst breast lump breast cancer

breast cancer is_areproductive system and breast disorder

DF-400DB

Lump and pre-menopausal implies possible breast cancer

February 2010 Centre for Doctoral Training

Clinical research and evidence-based medicine

NIH 1975

February 2010 Centre for Doctoral Training

Levels of evidence

Evidence-based medicine

The practice of EBM has five steps:

1. Convert need for information about prevention, diagnosis, prognosis, therapy, causation etc. into an answerable question

2. Track down the best evidence to answer the question

3. Critically appraise the evidence for validity and applicability

4. Integrate the critical appraisal with our clinical expertise and our patient’s unique biology, values and circumstances

5. Evaluate our performance.

Medical research, clinical practice

Understanding

diseases and their

treatment

Understanding

diseases and their

treatment

Ensure rightPatients receiveright

intervention

Ensure rightPatients receiveright

intervention

Service delivery,

performance

assessment

Service delivery,

performance

assessment

Develop and test

treatments

Develop and test

treatments

HealthRecords

Phase I

The clinical trial is “the most definitive tool for evaluation of the applicability of clinical

research.”

February 2010 Centre for Doctoral Training

Phase IVPhase III

Phase IIAscertain Maximum Tolerated Dose (MTD)

Estimate effect and rate of adverse events

Assess the effectiveness of a new intervention

Long-term studies of licensed interventions

February 2010 Centre for Doctoral Training

IT for evidence-based medicine

Formalising research results

“treatment comparison formulas”

IT for evidence-based medicine

IT for evidence-based medicine

Medical research, clinical practice

Understanding

diseases and their

treatment

Understanding

diseases and their

treatment

Ensure rightPatients receiveright

intervention

Ensure rightPatients receiveright

intervention

Service delivery,

performance

assessment

Service delivery,

performance

assessment

Develop and test

treatments

Develop and test

treatments

HealthRecords

Lecture 3