The openEHR Developers' workshop
Shinji KOBAYASHIKobayashia, Pablo Pazos Gutierrezb, Koray Atalag (Deactivated)c, Sebastian Garded, Ian McNicolle, Erik Sundvall f,g
aThe EHR Research Unit, Kyoto University, Japan, bCaboLabs, cUniversity of Auckland, dOcean Informatics, eHandiHealth, fLinköping University, gRegion Östergötland
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2.2 Overview of each implementation project
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We have employed the openEHR standard which underpins our national interoperability reference architecture to represent the dataset and also to build the web-based registry system. Use of this rigorous methodology to tackle health information is expected to ensure semantic consistency of Registry data and maximise interoperability with other Sector projects. The development work has been facilitated by the ability to transform the dataset automatically into software code – ensuring clinical requirements accurately translated into technical terms.
Clinical Knowledge Manager (Sebastian Garde)
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Since 2009 we have developed several Clinical Information System projects based on openEHR. We started focusing on R&D, and now reusing that experience (and code) to build a service oriented (REST and SOAP), open source, and general purpose EHR platform to help developers to create shared EHRs that will be standard-compliant from scratch. That platform will support many EMR applications and devices. We are also creating tools to help on the application development itself, providing frameworks, libraries and tools.
Working with openEHR Semantically (Koray Atalag)
We have used openEHR to model and persist experimental data that underpins computational physiology models (e.g. VPH, Human Physiome). The idea is then to link both experimental and real-world clinical information to these quantitative and predictive models to create a new breed of decision support tools that can deliver highly personalised and precision medicine. We have had some key important learnings while representing such models and especially when semantically annotating them - which in openEHR world corresponds to term and constraint bindings and data instance level term mappings. We will explain our methodology and discuss lessons learned which we hope will facilitate the use of openEHR in Semantic Web environments.
2.3 Workshop speakers
- Shinji Kobayashi, MD, PhD - Kyoto University, Japan
- Pablo Pazos, Ingeniero en Computación, openEHR en español, CaboLabs, ACHISA
- Koray Atalag (Deactivated), MD, PhD, FACHI - University of Auckland, New Zealand
- Sebastian Garde, Dr. sc. hum., Dipl.-Inform. Med., FACHI - Ocean Informatics
- Ian McNicoll MBChB,MSc, HandiHealth CIC, UK
- Erik Sundvall, MSc, PhD - Linköping University and Region Östergötland, Sweden
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