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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.
EtherCIS a new Open Source OpenEhr backend server (Christian Chevalley)
EtherCIS is a DB centric OpenEhr compliant SOA platform. It exposes a RESTful API handling OpenEhr entities under three formats (Flat json, AQLPath json and XML). The motivation of EtherCIS has been to provide an open, scalable yet secure clinical data repository that can be queried using different languages (AQL and SQL). SQL querying is performed using standard tools, as recent progresses in DB developments now allow combinations of relational and schema-less data structures. We will discuss our experiences (and failures) with previous persistence approaches, pros and cons of the current one and future perspectives in line with major DB engines developments.
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, Germany
- Ian McNicoll MBChB,MSc, HandiHealth CIC, UK
- Erik Sundvall, MSc, PhD - Linköping University and Region Östergötland, Sweden
- Christian Chevalley, Founder and Technical Director, ADOC Software, Thailand
3 Specific Educational Goals
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