Personalized-Detailed Clinical Model for Data Interoperability Among Clinical Standards

Abstract

Objective: Data interoperability among health information exchange (HIE) systems is a major concern for healthcare practitioners to enable provisioning of telemedicine-related services. Heterogeneity exists in these systems not only at the data level but also among different heterogeneous healthcare standards with which these are compliant. The relationship between healthcare organization data and different heterogeneous standards is necessary to achieve the goal of data level interoperability. We propose a personalizeddetailed clinical model (P-DCM) approach for the generation of customized mappings that creates the necessary linkage between organization-conformed healthcare standards concepts and clinical model concepts to ensure data interoperability among HIE systems. Materials and Methods: We consider electronic health record (EHR) standards, openEHR, and HL7 CDA instances transformation using P-DCM. P-DCM concepts associated with openEHR and HL7 CDA help in transformation of instances among these standards. We investigated two datasets: (1) data of 100 diabetic patients, including 50 each of type 1 and type 2, from a local hospital in Korea and (2) data of a single Alzheimer's disease patient. P-DCMs were created for both scenarios, which provided the basis for deriving instances for HL7 CDA and openEHR standards. Results: For proof of concept, we present case studies of encounter information for type 2 diabetes mellitus patients and monitoring of daily routine activities of an Alzheimer's disease patient. These reflect P-DCM-based customized mappings generation with openEHR and HL7 CDA standards. Customized mappings are generated based on the relationship of P-DCM concepts with CDA and openEHR concepts. Conclusions: The objective of this work is to achieve semantic data interoperability among heterogeneous standards. This would lead to effective utilization of resources and allow timely information exchange among healthcare systems.

Towards a Conceptual Framework for Persistent Use: A Technical Plan to Achieve Semantic Interoperability within Electronic Health Record Systems

“…The review of the literature demonstrated that interoperability solutions previously proposed were primarily based on healthcare standards such as openEHR archetypes [6], [21], [23], [42], ISO 13606, semantic ontology using OWL mapping [18], [31], and HL7 standards [18], [33]. RDF, as a standard to achieve interoperability, was not incorporated in any of the proposed solution reviewed in the literature.…”

“…While these solutions facilitated some interoperability functionality, they were proven to be limited and not scalable enough to allow for the application of new scenarios thus hindering the effective achievement of a broader scope of semantic interoperability [6]. Further, many researchers still claim that semantic interoperability within the healthcare sector has yet to be fully accomplished even with the implementation of the existing systems [8], [15], [18], [31], [42].…”

“…As the body of knowledge was examined, it was determined that various researchers have also explored this conceptual basis of the problem of EHR interoperability -the lack of a comprehensive data standards model to promote interoperability [1], [2], [38], [41], [18], [16], [39], [9]. While many researched this problem from the perspective of varied concentrated areas of interest, the general consensus remains the same; there still remains a deficiency in the way health information can be exchanged within multiple healthcare organizations across states or even locally.…”

“…An analysis of the articles compiled for the literature review provides a conclusion that the implementation of a viable EHR interoperability solution would involve significant factors of data standardization and translation which will allow for the exploration of: (a) the current healthcare based standards of EHR interoperability [18], [20], [31], [1], [4]; (b) technical infrastructure which focuses on the back-end infrastructure [2], [19]; (c) modification and optimal changes in process and workflows which consider the current operational practices [7], [14], [22]; and (d) how existing EHR interoperability solutions are implemented [24], [29], [30].…”

Towards a Conceptual Framework for Persistent Use: A Technical Plan to Achieve Semantic Interoperability within Electronic Health Record Systems

“…As the body of knowledge was examined, it was determined that various researchers had also explored this conceptual basis of the problem of EHR interoperability -the lack of a comprehensive data standards model to promote interoperability [1], [2], [43], [46], [22], [18], [44], [10]. While many researched this problem from the perspective of varied concentrated areas of interest, the general consensus remained the same; there still remained a deficiency in the way health information could be exchanged within multiple healthcare organizations across states or even locally.…”