My prezo at Medinfo 2015 Conference in the workshop: Digital Patient Modeling and Clinical Decision Support by Kerstin Denecke, Stefan Kropf, Claire Chalopin, Mario A, Cypko, Yihan Deng, Jan Gaebel, Koray Atalag

1. Bringing Things Together and
Linking to Health Information
using openEHR
Koray Atalag, MD, PhD, FACHI
Senior Research Fellow (ABI & NIHI)
k.atalag@auckland.ac.nz

2. cell-cell
connections
proteins
genomic
sequence
amino acid
sequence
torso
Example: The Heart Physiome
3D cell
tissue
heart
cellular processes
nm
m
=109nm
Hunter PJ, Pullan AJ, Smaill, BH. Modeling total heart function.
Annual Review of Biomedical Engineering, 5:147-177, 2003
LeGrice IJ, Hunter PJ, Smaill BH. Am.J.Physiol. 272:H2466-H2476, 1997

3. Myocardial activation
Ventricular wall mechanics
Ventricular blood flow
Heart valve mechanics
Coronary blood flow
Neural control
Torso model
Composite
lumped parameter
cell model
Hodgkin-Huxley type
ion channel model
Markov ion channel model
3D protein model
(KCNQ1+KCNE1)
Coarse grained MD model
Quantum mechanics model
Molecular dynamics model
Continuum tissue model
Organ model
Discrete tissue
structure model
Calcium transport models
Myofilament mechanics
Signal pathway models
Metabolic pathway models
Gene regulation models
3D cell model

4. Tissue
Osteon NephronAcinus Liver lobuleLymph nodeCardiac sheets
Organ
Heart Lungs Diaphragm Colon EyeKnee Liver
Environment
Organ system
Organism
Cell
Protein
Gene
Atom
Network
x 1million 20 generations
The challenge: organs to proteins

5. (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: CellML, SBML, FieldML,…

6. Why the need for clinical data?
• Biophysical models (geometric/mathematical)
define real-world biological entities/processes
• Multi-scale biomedical integration requires
understanding of normal and pathological
phenomena
• Clinical records are sinks of valuable
knowledge
– Embody effects of environment/random
phenomena
• Therefore clinical data will allow for
– Better understanding (geno-pheno-enviro)
– Model validation
– Model customisation (e.g. personal parameters)
– Predictive tools & advanced decision support
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7. 7
Patient Avatar:
digital representation
of all health-related data that is
available for the individual,
as the general basis
for the construction of
Virtual Physiological Human workflows

8. VPH-Share Clinical Workflow
• Medical records
• Patient images
• Population data
Images/Data Process
• Segment
• Mesh
• BCs
10%
Surgical planning
etc
Risk of…
Something
Output
• Individualised risk score
• Surgical strategy
• Therapy
Networks
• Multiple sources/types
Cloud
• Scalable
Computing
• Fast processing
Remote Viz
• Efficient graphics
Clinical
ICT
• Simulation
• Visualisation
• Analysis
Analysis

9. Integrating Physiome/Biomedical Informatics
• Current Physiome / VPH data and model
integration work is mostly underpinned by
Semantic Web
• There’s limited uptake of Semantic Web
technologies in healthcare delivery (e.g. EHRs,
HIS, CIS etc.)
• openEHR is a key medical informatics standard to
link the two worlds;
– Models of how to capture/represent clinical information
– Supports data creation, validation, storage etc.
– Supports explicit semantics via terminology bindings to
formal ontologies
– Used by many real-world systems today
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10. The Science Domains
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11. PhD Research (Aleksandar Zivaljevic):
Annotation of clinical datasets using openEHR Archetypes
Extending the RICORDO* Framework
Bono B de, Hoehndorf R, Wimalaratne S, Gkoutos G, Grenon P. The RICORDO approach to semantic interoperability for
biomedical data and models: strategy, standards and solutions. BMC Research Notes. 2011 Aug 30;4(1):313.

12. Conclusion
• Linked Data is a necessity
– Phenotypes (e.g. diseases, findings, behaviour)
– Genotype (e.g. Omics data)
– Environment (e.g. physical, food, psychological)
– Physiological (models, simulations, visualisations)
• Physiome / VPH needs to link to “real world” data
– Shared resources & annotations key to linkage
– TODO: clinical data platform w/ common meta-data
• has been utilised by VPH-Share (Avatars)
• HL7’s is also a key standard for exchange
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