Detailed Clinical Models: Representing Knowledge, Data and Semantics in Healthcare Information Technology

Abstract

ObjectivesThis paper will present an overview of the developmental effort in harmonizing clinical knowledge modeling using the Detailed Clinical Models (DCMs), and will explain how it can contribute to the preservation of Electronic Health Records (EHR) data.MethodsClinical knowledge modeling is vital for the management and preservation of EHR and data. Such modeling provides common data elements and terminology binding with the intention of capturing and managing clinical information over time and location independent from technology. Any EHR data exchange without an agreed clinical knowledge modeling will potentially result in loss of information.ResultsMany attempts exist from the past to model clinical knowledge for the benefits of semantic interoperability using standardized data representation and common terminologies. The objective of each project is similar with respect to consistent representation of clinical data, using standardized terminologies, and an overall logical approach. However, the conceptual, logical, and the technical expressions are quite different in one clinical knowledge modeling approach versus another. There currently are synergies under the Clinical Information Modeling Initiative (CIMI) in order to create a harmonized reference model for clinical knowledge models.ConclusionsThe goal for the CIMI is to create a reference model and formalisms based on for instance the DCM (ISO/TS 13972), among other work. A global repository of DCMs may potentially be established in the future.

Solving the Modeling Dilemma as a Foundation for Interoperability

“…This does not just apply to the aforementioned specifications such as the RIM-based solutions, but is also a concern in managing clinical models such as the HL7 CIMI approach [38]. For more information, see, e.g., [23,24]. Not just the presented classification systems, but also standard modeling conventions and data modeling best practices advise in overcoming the problems in data modeling and data governance management.…”

“…To get there, intra-domain specializations/ generalizations have to be performed. In summary, the Interoperability Reference Architecture Model supports EJBI -Volume 14 (2018), Issue 3 Examples for re-engineering existing standards to provide cross-specification or even inter-disciplinary interoperability can be found in [21,22] regarding interoperability between HL7v2 and HL7v3 or in [23,24] enabling use case and domaincrossing interoperability in the context of ISO 13972 Health informatics -Detailed clinical models [25]. The approach has also been adopted for ISO and CEN standards such as ISO 13606-1 Health informatics -EHR communication -Reference Model [14], where the reference model used for all parts has been re-engineered.…”

Standardization on for Mastering Healthcare Transformation on - Challenges and Solutions

“…Th e presented approach has been successfully deployed in several cross-domain ISO specifi cations, such as ISO 22600, ISO 21298, HL7 Composite Security and Privacy Domain Analysis Model [21]. Its feasibility has been practically demonstrated for automatically harmonizing HL7 v2.x and HL7 v3 specifi cations [16,22], for enabling use case and domain crossing interoperability in the context of ISO 13972 Health informatics -Detailed clinical models [23,24], or for automatically designing inter-domain Web services to facilitate multi-disciplinary approaches to Type 2 Diabetes Care management [25,26]. Th e approach also allows a comparative analysis and evaluation of ICT Enterprise Architectures [6].…”

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

“…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].…”