Combining Ontologies and Open Standards to Derive a Middle Layer Information Model for Interoperability of Personal and Electronic Health Records
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Objectives: To enable better interoperability between Personal Health Record (PHR) and Electronic Health Record (EHR) systems to allow exchange of data from patients to providers and vice versa in order to encourage PHR use and patient self-management. Methods: A non-binding middleware based on open technologies and standards that resides between a PHR and EHR system has been developed. Specifically, the middleware consists of an ontology-driven information model based on the HL7 Reference Information Model (RIM) and a set of transformation rules that work in conjunction with the information model to process data exported from a PHR or EHR system and prepare it according to constraints imposed by the receiving system. Results: The information model was evaluated by executing a set of use case scenarios containing data exported from a PHR system, transformed according to the transformation rules, transferred to an EHR system and vice versa (EHR to PHR). This allowed various challenges to emerge as well as revealed gaps in current standards in use. Conclusions: The proposed middleware information model offers a number of advantages. When modifications are made to either a PHR or EHR system, they can be incorporated by altering only the instantiation of the information model. The model uses classes and attributes based on HL7 RIM to define how data is captured which allows greater flexibility in how data can be manipulated by receiving systems. The solution is applicable to existing PHR systems, or could be used as a blueprint to develop new PHR applications.
O'Sullivan, D. & Plastiras, P. (2018) Combining Ontologies and Open Standards to Derive a Middle Layer Information Model for Interoperability of Personal and Electronic Health Records, International Journal of Medical Informatics,Vol.120, December 2018, Pages 116-125. DOI:10.1016/j.ijmedinf.2018.10.006
International Journal of Medical InformaticsVolume 120, December 2018, Pages 116-125