World Health Organization on Health Information
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Transcript of World Health Organization on Health Information
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