María del Carmen Legaz-García1, Marcos Menárguez-Tortosa2, Jesualdo Tomás Fernández-Breis2, Christopher G Chute3, Cui Tao4. 1. Departamento de Informática y Sistemas, Universidad de Murcia, IMIB-Arrixaca, 30100 Spain mdclg3@um.es. 2. Departamento de Informática y Sistemas, Universidad de Murcia, IMIB-Arrixaca, 30100 Spain. 3. Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA. 4. School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX, USA.
Abstract
INTRODUCTION: The semantic interoperability of electronic healthcare records (EHRs) systems is a major challenge in the medical informatics area. International initiatives pursue the use of semantically interoperable clinical models, and ontologies have frequently been used in semantic interoperability efforts. The objective of this paper is to propose a generic, ontology-based, flexible approach for supporting the automatic transformation of clinical models, which is illustrated for the transformation of Clinical Element Models (CEMs) into openEHR archetypes. METHODS: Our transformation method exploits the fact that the information models of the most relevant EHR specifications are available in the Web Ontology Language (OWL). The transformation approach is based on defining mappings between those ontological structures. We propose a way in which CEM entities can be transformed into openEHR by using transformation templates and OWL as common representation formalism. The transformation architecture exploits the reasoning and inferencing capabilities of OWL technologies. RESULTS: We have devised a generic, flexible approach for the transformation of clinical models, implemented for the unidirectional transformation from CEM to openEHR, a series of reusable transformation templates, a proof-of-concept implementation, and a set of openEHR archetypes that validate the methodological approach. CONCLUSIONS: We have been able to transform CEM into archetypes in an automatic, flexible, reusable transformation approach that could be extended to other clinical model specifications. We exploit the potential of OWL technologies for supporting the transformation process. We believe that our approach could be useful for international efforts in the area of semantic interoperability of EHR systems.
INTRODUCTION: The semantic interoperability of electronic healthcare records (EHRs) systems is a major challenge in the medical informatics area. International initiatives pursue the use of semantically interoperable clinical models, and ontologies have frequently been used in semantic interoperability efforts. The objective of this paper is to propose a generic, ontology-based, flexible approach for supporting the automatic transformation of clinical models, which is illustrated for the transformation of Clinical Element Models (CEMs) into openEHR archetypes. METHODS: Our transformation method exploits the fact that the information models of the most relevant EHR specifications are available in the Web Ontology Language (OWL). The transformation approach is based on defining mappings between those ontological structures. We propose a way in which CEM entities can be transformed into openEHR by using transformation templates and OWL as common representation formalism. The transformation architecture exploits the reasoning and inferencing capabilities of OWL technologies. RESULTS: We have devised a generic, flexible approach for the transformation of clinical models, implemented for the unidirectional transformation from CEM to openEHR, a series of reusable transformation templates, a proof-of-concept implementation, and a set of openEHR archetypes that validate the methodological approach. CONCLUSIONS: We have been able to transform CEM into archetypes in an automatic, flexible, reusable transformation approach that could be extended to other clinical model specifications. We exploit the potential of OWL technologies for supporting the transformation process. We believe that our approach could be useful for international efforts in the area of semantic interoperability of EHR systems.
Authors: Cui Tao; Guoqian Jiang; Thomas A Oniki; Robert R Freimuth; Qian Zhu; Deepak Sharma; Jyotishman Pathak; Stanley M Huff; Christopher G Chute Journal: J Am Med Inform Assoc Date: 2012-12-25 Impact factor: 4.497
Authors: Jason J Saleem; Mindy E Flanagan; Nancy R Wilck; Jim Demetriades; Bradley N Doebbeling Journal: J Am Med Inform Assoc Date: 2013-04-18 Impact factor: 4.497
Authors: Susan Rea; Jyotishman Pathak; Guergana Savova; Thomas A Oniki; Les Westberg; Calvin E Beebe; Cui Tao; Craig G Parker; Peter J Haug; Stanley M Huff; Christopher G Chute Journal: J Biomed Inform Date: 2012-02-04 Impact factor: 6.317
Authors: Jesualdo Tomás Fernández-Breis; José Alberto Maldonado; Mar Marcos; María del Carmen Legaz-García; David Moner; Joaquín Torres-Sospedra; Angel Esteban-Gil; Begoña Martínez-Salvador; Montserrat Robles Journal: J Am Med Inform Assoc Date: 2013-08-09 Impact factor: 4.497
Authors: José Alberto Maldonado; Mar Marcos; Jesualdo Tomás Fernández-Breis; Estíbaliz Parcero; Diego Boscá; María Del Carmen Legaz-García; Begoña Martínez-Salvador; Montserrat Robles Journal: AMIA Annu Symp Proc Date: 2017-02-10
Authors: María Del Carmen Legaz-García; José Antonio Miñarro-Giménez; Marcos Menárguez-Tortosa; Jesualdo Tomás Fernández-Breis Journal: J Biomed Semantics Date: 2016-06-03
Authors: Blanda Helena de Mello; Sandro José Rigo; Cristiano André da Costa; Rodrigo da Rosa Righi; Bruna Donida; Marta Rosecler Bez; Luana Carina Schunke Journal: Health Technol (Berl) Date: 2022-01-26