Ontology Content Patterns as Bridge for the Semantic Representation of Clinical Information

Summary

Objective: Semantic interoperability of the Electronic Health Record (EHR) requires a rigorous and precise modelling of clinical information. Our objective is to facilitate the representation of clinical facts based on formal principles.

Methods: We here explore the potential of ontology content patterns, which are grounded on a formal and semantically rich ontology model and can be specialised and composed.

Results: We describe and apply two content patterns for the representation of data on tobacco use, rendered according to two heterogeneous models, represented in openEHR and in HL7 CDA. Finally, we provide some query exemplars that demonstrate a data interoperability use case.

Conclusion: The use of ontology content patterns facilitate the semantic representation of clinical information and therefore improve their semantic interoperability. There are open issues such as the scalability and performance of the approach if a logic-based language is used. Implementation decisions might determine the final degree of semantic interoperability, influenced by the state of the art of the semantic technologies.

Citation: Martínez-Costa C, Schulz S. Ontology content patterns as bridge for the semantic rRepresentation of clinical information Appl Clin Inf 2014; 5: 660–669

http://dx.doi.org/10.4338/ACI-2014-04-RA-0031

Keywords

Electronic Health Records - Semantics - SNOMED CT - Knowledge Representation - HL7 CDA - OpenEHR

 

Conflicts of interest

The authors declare that they have no conflicts of interest in the research

• References

• 1 Heard S, Beale T, Freriks G, Mori AR, Pishec O. Templates and archetypes: How do we know what we are talking about, Version 1.2. 2003
• 2 CIMI Patterns. http://informatics.mayo.edu/CIMI/index.php (Last accessed: March 2014).
• 3 Rector A, Qamar R, Marley T. Binding Ontologies & Coding systems to Electronic Health Records and Messages. Applied Ontology 2009; 4: 51-51.
• 4 emanticHealthNet Network of Excellence.. http://www.semantichealthnet.eu (Last accessed March 2014)
• 5 Schulz S, Martinez-Costa C. How ontologies can improve semantic interoperability in health care. Lecture Notes in Computer Science 2013; 8268: 1-10.
• 6 Gangemi A, Presutti V. Content ontology design patterns as practical building blocks for web ontologies. In: Proc of the 27th International Conference on Conceptual Modeling. 2008: 128-141.
• 7 W3C OWL working group.. OWL 2 Web Ontology Language, document overview. W3C Recommendation 11 December 2012. www.w3.org/TR/owl2-overview (Last accessed March 2014)
• 8 OpenEHR.. An open domain-driven platform for developing flexible e-health systems. http://www.ope nehr.org (Last accessed March 2014)
• 9 Dolin RH, Alschuler L, Boyer S, Beebe C, Behlen FM, Biron PV, Shvo AS. The HL7 clinical document architecture, release 2. JAMIA 2006; 13: 30-39.
• 10 BioTopLite. http://purl.org/biotop/biotoplite.owl. (Last accessed March 2014)
• 11 Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT), 2008.. http://www.ihtsdo.org snomed-ct (Last accessed March 2014)
• 12 Schulz S, Rector A, Rodrigues J, Chute C, Üstün B, Spackman K. Ontology-based convergence of medical terminologies. SNOMED CT and ICD-11. Proc of eHealth2012. Vienna, Austria: OCG; 2012
• 13 Blomqvist E, Daga E, Gangemi A, Presutti V. Modelling and using ontology design patterns. [http://www. neon-project.org/web-content/media/book-chapters/Chapter-12.pdf ]. (Last accessed March. 2014)
• 14 Gangemi A. Ontology design patterns for semantic web content. In: Proceedings of the Fourth International Semantic Web Conference. 2005: 262-276.
• 15 SemanticHealthNet deliverable 4.2: Ontology/Information models covering the HF use case, 2013.( http://www.semantichealthnet.eu/index.cfm/deliverables )
• 16 Martínez Costa C, Boscá D. Legaz-García MC, Tao C, Fernández-Breis JT, Schulz S, Chute CG, Isosem-antic rendering of clinical information using formal ontologies and RDF.. In: Proc MEDINFO 2013. Stud Health Technol Inform 2013; 192: 1085.
• 17 Clinical Knowledge Manager.. http://www.openehr.org/ckm (Last accessed March 2014)
• 18 HL7 IG for CDAR2: IHE Health Story Consolidation, R1“, Consolidated CDA, C-CDA:. www.hl7.org/implement/standards (Last accessed March 2014)
• 19 US Meaningful Use Stage 2. http://www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentive Programs/Downloads/Stage2_Guide_EPs_9_23_13.pdf (Last accessed March 2014)