Clinical Data Integration Model : Core Interoperability Ontology for Research Using Primary Care Data

Background

Biomedical research increasingly relies on the integration of information from multiple het- erogeneous data sources [1]. Despite the fact that structural and termino- logical aspects of interoperability are interde- pendent and rely on a common set of require- ments, current e orts typically address them in isolation [2]. We propose a uni ed ontology-based knowl- edge framework to facilitate interoperability between heterogeneous sources [3].

Material and Methods

The modeling infrastructure resides entirely within LexEVS, enabling uni cation of struc- tural and semantic modeling operations. Sev- eral types of models are present:

  1. The general information model (GIM)
  2. Models describing each data source (DSM)
  3. Mapping sets between the sources and the GIM – one set per source (DSmG)
  4. Terminologies (e.g. International Classication of Diseases – ICD – 10 codes…)
  5. Mappings between terminologies (TmT)

Results

The first implementation was realized as part of the EU FP7 TRANSFoRm proj- ect. The General Information Model was successfully instantiated as the clini- cal data integration model (CDIM) and necessary mappings were created to support e ective information retrieval for software tools in the project [4].

The resulting model is imple- mented as an OWL ontology based on the Basic Formal Ontology (BFO) 1.1. It has 549 classes (102 unique to CDIM) and 82 object proper- ties (1 sub-property unique to CDIM). Twenty-one novel CDIM classes had to be intro- duced to represent and manage temporal aspects necessary in TRANSFoRm.

Two clinical data repositories were used to evaluate the suitability of the framework for the project: GPRD from United Kingdom and NPCD from the Netherlands. We evaluated the applicability of the CDIM approach to TRANSFoRm’s clinical trial use cases.

Conclusion

We presented a novel, unifying approach to address interoperability chal- lenges in heterogeneous data sources, by representing structural and seman- tic models in a single framework structured by CDIM. This represents a signi – cant departure from the previous strategies for addressing interoperability in translational research, and it has been successfully demonstrated within the context of the clinical research studies of the EU TRANSFoRm project.

CDIM, terminologies and mappings are all stored in LexEVS and can be ac- cessed using methods implementing the HL7 CTS2 standard. The system is exible, and should reduce the integration e ort required from the data sources, thereby lowering the cost of entry of this type of research.

Acknowledgement and Contact

This work was supported in part by the European Commission – DG INFSO (FP7 247787).
Jean-François Ethier, [email protected], +33 (0)1 44 27 63 93

References

  1. Sujansky W. Heterogeneous Database Integration in Biomedicine. J Biomed Inform 2001;34:285–98.
  2. Rector AL, Qamar R, Marley T. Binding ontologies and coding systems to electronic health records and messages. Appl Ontol 2009;4:51–69.
  3. Ethier JF, Dameron O, Curcin V, et al. A uni ed structural/terminological interoperability framework based on LexEVS: application to TRANSFoRm. J Am Med Inform Assoc 2013; 20:986-994
  4. Ethier JF, Curcin V, Barton A, et al. Clinical Data Integration Model: Core Interoperability Ontology for Research Using Primary Care Data. Methods Inf Med 2014; 53(4). [Epub ahead of print]

Poster

Saint-Malo 2014, France
Poster_St-Malo_2014_CDIM

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