Dr. T. Bedirhan Üstün

World Health Organization

Classifications , Terminologies, Standards

WHO on Health Information

• Views expressed in this presentation are those of B. Üstün

• They do not necessarily represent the policies of

conflict of interests declared:

• Presenter believes in: Scientific Methods, Ontologies,

Caveat

Tower of BabelTower of Babble

History of Disease & Health in the World

• 243 BC: plague in China

• 800 s : smallpox in Japan

• 1090s: dysentery in Palestine

• 1340s: "Black Death" in Europe

• 1830s: cholera worldwide

• 1917–19: influenza worldwide

• …

• …

• 1976-2015 Ebola

William Farr to

• Farr developed the first national vital statistics system as a

instrument for epidemiologic studies.

• to crafted a disease nosology usable by vital statisticians and

epidemiologists led to the creation of the ICD

• The structure of the ICD derives from Farr's 1860 proposal.

150 year later WHO and the FARR Institute

share the vision of Farr to implement it further in the digital health space

Genealogy of ICD 1664

ICD Revisions

139

161

179

189

205

214

200

954

965

1,04

0

1,16

4

8,17

3

1,96

7

14,4

73

1

10

100

1000

10000

100000

Farr/

d'E

spin

e

Berti

llon

ICD

1

ICD

2

ICD

3

ICD

4

ICD

5

ICD

6

ICD

7

ICD

8

ICD

9

ICD

-9-M

ICD

10

ICD

-10-

M

1853 1893 1900 1909 1920 1929 1938 1948 1955 1968 1975 1979 1990 1993

Shepherdingsimple requirements

1. Count your sheep• How many born ?

• How many dead ?

2. Don’t cry wolf !

Reporting of Mortality in the World

Information Paradox

0

100000000

200000000

300000000

400000000

500000000

600000000

700000000

800000000

1 2 3 4

YL

Ls

VR countries vs No VR

Burden of Mortality

Millenium Development Goals

the information YOU -

₋ have is not what you want

₋ want is not what you need

₋ need is not what you can have

Finagle's Law of Information

have

want

need

In other words there is always a gapbetween what you have, need or want

Health Information needs Health Informatics

ComputationalProcessing

Knowledge

INPUTSAnalytical process

OUTPUT

• Mechanisms

• Interventions

• Policies

• Statistics

• Aggregation

• Ontologies

• Data

• Information

GIGO: Garbage In

Out ?

Can we build the Big Intelligence ?

Why is this Sooooo important ?

Sharing Meaning

YOU

• Think

• wish to express

• think you have just expressed

• you expressed

• …

OTHER ONE

• wants to hear

• Actually hears

• wishes to understand

• understands

• …

How do we optimize our health services

E-he@lth Health Information Systems: Analog to Digital

Placing WHO Classifications in HIS & IT

Population Health• Births • Deaths • Diseases• Disability • Risk factors

e-Health RecordSystems

ICD

ICF

ICHI

Classifications

KRs

Terminologies

Clinical• Decision Support• Integration of care• Outcome

Administration• Scheduling• Resources • Billing

Reporting• Cost• Needs• Outcome

ICD-11 Revision Goals1. Evolve a multi-purpose and coherent classification

• Mortality, morbidity, primary care, clinical care, research, public health…• Consistency & interoperability across different uses

2. Serve as an international and multilingual reference standard for scientific comparability and communication purposes

3. Ensure that ICD-11 will function in an electronic environment.• ICD-11 will be a digital product• Support electronic health records and information systems

• Link ICD logically to underpinning terminologies and ontologies (e.g. SNOMED, GO, …)

• ICD Categories “defined” by "logical operational rules" on their associations and details

Ontology (philosophy)

the Organization of Reality !!!

Ontology (computer science) – the explicit – operational description of

the conceptualization of a domain• Entities

• Atributes

• Values

• An ontology defines:– a common vocabulary

– a shared understanding/exchange:• among people

• among software agents

• between people and software– to reuse data - information

– to introduce standards to allow interoperability

What is “NOntology” ?

Knowledge Representationthe triad of things, thoughts and words(Ogden & Richards, 1923 )

APPLETERM

THE CONTENT MODELAny Category in ICD is represented by:

1. ICD Concept Title1.1. Fully Specified Name

2. Classification Properties2.1. Parents2.2 Type2.3. Use and Linearization(s)

3. Textual Definition(s)

4. Terms4.1. Base Index Terms4.2. Inclusion Terms4.3. Exclusions

5. Body Structure Description 5.1. Body System(s) 5.2. Body Part(s) [Anatomical Site(s)]5.3. Morphological Properties

6. Manifestation Properties6.1. Signs & Symptoms 6.2. Investigation findings

7. Causal Properties7.1. Etiology Type7.2. Causal Properties - Agents7.3. Causal Properties - Causal Mechanisms 7.4. Genomic Linkages7.5. Risk Factors

8. Temporal Properties8.1. Age of Occurrence & Occurrence Frequency

8.2. Development Course/Stage

9. Severity of Subtypes Properties

10. Functioning Properties10.1. Impact on Activities and Participation10.2. Contextual factors10.3. Body functions

11. Specific Condition Properties11.1 Biological Sex

11.2. Life-Cycle Properties

12. Treatment Properties

13. Diagnostic Criteria

The ICD Foundation Component

• is a collection of ALL ICD entities like diseases, disorders...

• It represents the whole ICD universe.

• In a simple way, the foundation component is similar to a “store” of books or songs.

• From these elements we build a selection as a linearization.

• This analogy may however be misleading because there are many links between the ICD entities (like parent-child relations and other).

• The ICD entities in the Foundation Component:

• are not necessarily mutually exclusive

• allow multiple parenting ( i. e. an entity may be in more than one branch, for example tuberculosis meningitis is both an infection and a brain disease)

The ICD Linearizations• A linearization is a subset of the

foundation component, that is:• Fit for a particular purpose: reporting mortality,

morbidity, or other uses

• Jointly Exhaustive of ICD Universe (Foundation Component)

• Composed of entities that are Mutually Exclusive of each other

• Each entity is given a single parent

30

Foundation: ICD categories with

- Definitions, synonyms- Clinical descriptions- Diagnostic criteria- Causal mechanism- Functional Properties

Find Term

SNOMED-CT, International Classification of Functioning, Disability and Health (ICF)…

Linearizations

Mortality

Morbidity

Primary Care

• Open and Collaborative Platform

• Web based

• Like WIKIPEDIA• But

• by the Content Model

• with• by the TAGs , and scientific peers

ICD11 βeta• http://www.who.int/classifications/icd/revision

• Beta – Browser & Print

10 look & feel + descriptions – code structure !

• ICD-11 Beta draft is NOT FINAL

• updated on a daily basis

•NOT TO BE USED for CODING except for agreed FIELD TRIALS

βeta

ICD-11 Features

Internet Based

Platform

Content Model

Multi Lingual Representations

Definitions

Input from

all Stakeholders

لعربية Arabic

官话 Chinese

English English

Français French

Русский язык Russian

Español Spanish

Deutsch German

Português Portuguese

Field Trials for

Use Cases

Electronic Health Record

Ready

Beta

• Comments

• Proposals

• Field Trials

• Review Mechanism

Incentives for Participants

ICD-11 Timeline

• 2014 : Beta : Field Trials Version• Systematic/scientific reviews• Vigorous crowdsourcing• Field Trials

• 2017 : Final version for WHA Approval• 2018+ implementation Perpetual DIGITAL editing – review cycles

• Essential for EHR

• Enhance Care

• Decision Support

• Safety & Quality

• Better Collaboration

• Monitoring & Evaluation

• Better Health Information

• Less Administration

SNOMED : Old and Current

FormerSNOMED

Enterprise

College

American

Pathologists

Global

Network

Overall Health Care

Why work together?– WHO & IHTSDO

– Coverage & Adequacy

– Quality – Reliability - Utility

– MultiLingual Applicability

– Interoperability

– Sustainability

– Member States: Enable health care delivery and

compile health information

SNOMED & WHO Classifications are synergistic and not antagonistic

The «Common Ontology» Purpose• To provide a common formal knowledge representation structure to

enable interoperability between:• ICD-11 and SNOMED CT.

• a shared semantics

Ultimate “Turing-like” Test

If common ontology achieved

Grade 3 hypertension

Grade 2 hypertension

Grade 1 hypertension

High normal

normal

optimal

120 130 140 150 160 170 180

Systolic pressure

Dia

sto

lic p

ress

ure

172

102

110

105

100

95

90

85

80

Knowledge Representation

43

Rewriting ICD Using SNOMEDexample of Depressive Disorder F32.0

A. Low mood {41006004}

Loss of interest {417523004 }

Low energy {248274002}

1. Appetite (decrease, increase) {64379006, 72405004}

2. Body weight (decrease, increase) {89362005, 8943002}

3. Sleep (decrease, increase) {59050008, 77692006}

4. Psychomotor (decrease, increase) {398991009, 47295007}

5. Libido loss {8357008}

6. Low self esteem {286647002, 162220005}

7. Guilt, self blame {7571003}

8. Thoughts of death …

9. Suicide Ideation {102911000, 6471006}

B.

Beyond GoogleTM

Semantic Interoperability for HIS

• Search using Concepts above Words• How many patients do have diabetes mellitus type II?

• Extraction of Concepts from Health Records• Automated extraction of Hb1Ac results of selected patients with DM type II from lab

reports within last year

• Statistical Index on Community Collections• Calculation of coverage gap for treatment need for diabetes mellitus

• Concept Navigation across Collections• Comparison of region A with region B etc

45

Real Time Public HealthRule-based Aggregation @ Individual, Facility, Population levels

Public Health, Epi & Surveillance

Findings InterventionsEvents

Clinical Information

ReimbursementResource Management

Clinical Use Case: Exploration of Cough

Fever

386661006

COUGH

49727002

WET COUGH

sputum

28743005

Hemoptisia

Blood in Sputum

207069003

• X-ray : Tbc?

• Culture

399208008

104184002

• Diagnosis: Tuberculosis 154283005

A 15.0

• Treatment: DOTs { 324453004 }

Interoperability

Future Steps

1. Linking individual data to public health indicators

2. Standards for public health indicators• Entities – relations ( n-ontology?: scientific compilation)

• Architecture

• Flow

• Aggregation process

Uniform Resource Identifiers

URI: //id.who.int/….

• enable links to other established terminology, ontologies

• allow impact analysis possible via W3C• e.g. where on the world these are used or not used

• Useful for translations: • the concepts will indicate a language-independent construct

and translations will refer to the unique source concept.

… BUILDING BLOCKS OF HEALTH INFORMATION …

Avoiding an e-tower of Babel

Questions & Answers

ustunb@who.int

@ustunb

bedirhan-ustun