Data Integration for Clinical Decision Support Based on openEHR Archetypes and HL7 Virtual Medical Record

Clinical Decision Support Systems (CDSS) have gained relevance due to their potential to support patient-centric care, but their deployment still has to overcome barriers to become successful. One of these barriers is the integration of patient data with the CDSS engine, a tough challenge given the need to address interoperability with many different existing systems and medical devices. The MobiGuide project aims to build such a CDSS, providing guideline- based clinical decision support through a Personal Health Record (PHR). This PHR is the main component through which the CDSS could access patient data originating from hospital EMRs and wearable sensors, but it also contains the log of the recommendations provided by the CDSS. Using a case study, we compare data-representation standards through which the PHR could be developed, while considering expressiveness and usability requirements. We propose to develop the PHR by combining openEHR archetypes and the HL7 Virtual Medical Record standard, supported by a service oriented framework for data exchange. This proposal aims to close the gap between the HL7 and the ISO/CEN 13606 by using an openEHR-based approach.

[1]  Kensaku Kawamoto,et al.  Standards for Scalable Clinical Decision Support: Need, Current and Emerging Standards, Gaps, and Proposal for Progress , 2010, The open medical informatics journal.

[2]  Samson W. Tu,et al.  A virtual medical record for guideline-based decision support , 2001, AMIA.

[3]  Nicolette de Keizer,et al.  The role of standardized data and terminological systems in computerized clinical decision support systems: Literature review and survey , 2011, Int. J. Medical Informatics.

[4]  Abdul V. Roudsari,et al.  Clinical Decision Support Systems , 2008 .

[5]  Yaron Denekamp,et al.  Mapping computerized clinical guidelines to electronic medical records: Knowledge-data ontological mapper (KDOM) , 2008, J. Biomed. Informatics.

[6]  Silvia Miksch,et al.  Knowledge Representation for Health Care , 2014, Lecture Notes in Computer Science.

[7]  Andrew K. McIntyre,et al.  Multi-National, Multi-Institutional Analysis of Clinical Decision Support Data Needs to Inform Development of the HL7 Virtual Medical Record Standard. , 2010, AMIA ... Annual Symposium proceedings. AMIA Symposium.

[8]  Marco Eichelberg,et al.  A survey and analysis of Electronic Healthcare Record standards , 2005, CSUR.

[9]  Sam Heard,et al.  The Relationship between CEN 13606, HL7, and OpenEHR , 2006 .

[10]  Rong Chen,et al.  Representing a Chemotherapy Guideline Using openEHR and Rules , 2009, MIE.

[11]  Erik Sundvall,et al.  Archetype-based conversion of EHR content models: pilot experience with a regional EHR system , 2009, BMC Medical Informatics Decis. Mak..

[12]  Paul C. Tang,et al.  Integrated Personal Health Records: Transformative Tools for Consumer-Centric Care , 2008, BMC Medical Informatics Decis. Mak..

[13]  Amnon Shabo,et al.  Model Formulation: HL7 Clinical Document Architecture, Release 2 , 2006, J. Am. Medical Informatics Assoc..

[14]  Adolfo Muñoz,et al.  The ISO/EN 13606 Standard for the Interoperable Exchange of Electronic Health Records , 2011 .

[15]  Yuval Shahar.  The "Human Cli-Knowme" Project: Building a Universal, Formal, Procedural and Declarative Clinical Knowledge Base, for the Automation of Therapy and Research , 2011, KR4HC.

[16]  Diego Boscá,et al.  An Archetype-Based Solution for the Interoperability of Computerised Guidelines and Electronic Health Records , 2011, AIME.

[17]  H. Lehmann,et al.  Clinical Decision Support Systems (cdsss) Have Been Hailed for Their Potential to Reduce Medical Errors Clinical Decision Support Systems for the Practice of Evidence-based Medicine , 2022 .

[18]  Sebastian Garde,et al.  Towards Semantic Interoperability for Electronic Health Records , 2007, Methods of Information in Medicine.

[19]  Jesualdo Tomás Fernández-Breis,et al.  LinkEHR-Ed: A multi-reference model archetype editor based on formal semantics , 2009, Int. J. Medical Informatics.