My prezo at Medinfo 2017 openEHR Developers Workshop. The aim was to demonstrate how openEHR supports very advanced research and analytics with examples from computational physiology and biosimulation to create patient-specific decision support.

1. Koray Atalag MD, PhD, FACHI
k.atalag@auckland.ac.nz
Senior Research Fellow, ABI
Chief Information Officer, The Clinician
Management Board Member, openEHR Foundation
openEHR in Research
Linking Health Data with Computational Models

3. Human Physiome Project
and
Virtual Physiological Human (VPH)
a methodological and technological framework
that will enable collaborative investigation
of the human body as a single complex system
Descriptive, Integrative And Predictive

4. What’s Computational Physiology
Governing equations
(laws of physics)
Anatomy & structure
High-performance
computing
Software
Material properties
from measurement
Observed function
Validation
Predicted function
Mechanistic insight

5. Tissue
Osteon NephronAcinus Liver lobuleLymph nodeCardiac sheets
Organ
Heart Lungs Diaphragm Colon EyeKnee Liver
Environment
Organ system
Organism
Cell
Protein
Gene
Atom
Network

6. (www.cellml.org)
Cuellar AA, Lloyd CM, Nielsen PF, Halstead MDB, Bullivant DP, Nickerson DP, Hunter PJ. An overview of CellML 1.1, a biological
model description language.SIMULATION: Transactions of the Society for Modeling and Simulation, 79(12):740-747, 2003
Physiome Standards and Tooling

7. Why Linked Health Data?

8. Secondary Use of EHR using openEHR
Single Content Model
CDA
FHIR
HL7 v2/3
EHR Extract
UML
XSD/XMI
PDF
Mindmap
PAYLOAD
System A
Data Source A
Map
To
Content
Model
System B
Data Source B
Native openEHR Repository
Secondary Use
Map
To
Content
Model
Automated Transforms
No Mapping
Atalag K. Using a single content model for eHealth interoperability and secondary use. Stud Health Technol Inform. 2013;193:282–96

9. Realising the Physiome / VPH

11. SNOMED-CT
(Systematized Nomenclature of Medicine)
• >300,000 biomedical concepts
• ~800,000 English language descriptions (terms)
• ~1.4 million semantic relationships (i.e. IS_A)
• Hierarchically organised in multiple axes
• Addressing the whole EHR space
• National licensing (NZ +)
• Mapped to ICD and through UMLS to 100s others
• Aligned/harmonised with LOINC and HL7
 The single most important terminology now

12. Coronary
arteriosclerosis
Structural
disorder of heart
Heart disease
Cardiac finding
Cardiovascular
finding
Finding by site
Clinical finding
SNOMED CT
Concept
Mediastinal
finding
Finding of region
of thorax
Finding of trunk
structure
Finding of body
region
Viscus structure
finding
Disorder of
mediastinum
Disorder of
thorax
Disorder of trunk
Disorder by
body site
Disease
Disorder of body
system
Disorder of body
cavity
Disorder of
cardiovascular
system
Disorder of
coronary artery
Coronary artery
finding
Arterial finding
Blood vessel
finding
General finding
of soft tissue
Disorder of soft
tissue of thoracic
cavity
Disorder of soft
tissue of body
cavity
Disorder of soft
tissue
Disorder of
artery
Vascular
disorder
Arteriosclerotic
vascular disease
Soft tissue
lesion
Degenerative
disorder

13. UMLS: Integrating Biomedicine
Unified Medical Language System
Biomedical
literature
MeSH
Genome
annotations
GO
Model
organisms
NCBI
Taxonomy
Genetic
knowledge bases
OMIM
Clinical
repositories
SNOMED CTOther
subdomains
…
Anatomy
FMA
UMLS
By NLM - UMLS integrates and distributes key terminology and ontology (knowledge sources)

14. Semantics in openEHR
• Whole-of-model meta-data:
– Description, concept references (terminology/ontology), purpose,
use, misuse, provenance, translations
• Item level semantics (Schema level)
– Trees/Clusters (Structure)
– Leaf nodes (Data Elements)
Formally: different types of terminology bindings:
1) linking an item to external terminology/ontology for the
purpose of defining its real-world clinical/biological meaning
2) Linking data element values to external terminology (e.g. a
RefSet or terminology query)
AlsoInstance level semantic annotations – applies to
actual data collected

15. 15

16. mindmap representation of openEHR Archetype
1) Linking items to SNOMED to define clinical meaning

17. 2) Linking data element values to external terminology

18. Bridging Semantics using Archetypes
e.g. Pseudohypoaldosteronism (PHA) as a disease (Diagnosis)
• Has biophysical, genomic and clinical models
• But all encoded using different terminology/ontology

19. NZ Cardiac
Registry
80k Patients
1000+ data points!
100+ terminology
bindings
19Screenshot of openEHR Template

20. Do you think it’s all Star Trek Stuff?

21. 21

23. INNOVATION CONFERENCE
IDEAS TO LIFE 2017
www.uoainnovation.com.cn
WeChat ‘pauxmg’ 梅保
HANGZHOU, CHINA
12-14 December 2017