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  • 1.
    Chen, Rong
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Klein, Gunnar O
    Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Solna, Sweden.
    Sundvall, Erik
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Karlsson, Daniel
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Åhlfeldt, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Archetype-based conversion of EHR content models: pilot experience with a regional EHR system2009In: BMC Medical Informatics and Decision Making, ISSN 1472-6947, E-ISSN 1472-6947, Vol. 9, no 33Article in journal (Refereed)
    Abstract [en]

    Background: Exchange of Electronic Health Record (EHR) data between systems from different suppliers is a major challenge. EHR communication based on archetype methodology has been developed by openEHR and CEN/ISO. The experience of using archetypes in deployed EHR systems is quite limited today. Currently deployed EHR systems with large user bases have their own proprietary way of representing clinical content using various models. This study was designed to investigate the feasibility of representing EHR content models from a regional EHR system as openEHR archetypes and inversely to convert archetypes to the proprietary format. Methods: The openEHR EHR Reference Model (RM) and Archetype Model (AM) specifications were used. The template model of the Cambio COSMIC, a regional EHR product from Sweden, was analyzed and compared to the openEHR RM and AM. This study was focused on the convertibility of the EHR semantic models. A semantic mapping between the openEHR RM/AM and the COSMIC template model was produced and used as the basis for developing prototype software that performs automated bidirectional conversion between openEHR archetypes and COSMIC templates. Results: Automated bi-directional conversion between openEHR archetype format and COSMIC template format has been achieved. Several archetypes from the openEHR Clinical Knowledge Repository have been imported into COSMIC, preserving most of the structural and terminology related constraints. COSMIC templates from a large regional installation were successfully converted into the openEHR archetype format. The conversion from the COSMIC templates into archetype format preserves nearly all structural and semantic definitions of the original content models. A strategy of gradually adding archetype support to legacy EHR systems was formulated in order to allow sharing of clinical content models defined using different formats. Conclusion: The openEHR RM and AM are expressive enough to represent the existing clinical content models from the template based EHR system tested and legacy content models can automatically be converted to archetype format for sharing of knowledge. With some limitations, internationally available archetypes could be converted to the legacy EHR models. Archetype support can be added to legacy EHR systems in an incremental way allowing a migration path to interoperability based on standards.

  • 2.
    Freire, Sergio Miranda
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Sundvall, Erik
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Karlsson, Daniel
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Performance of XML Databases for Epidemiological Queries in Archetype-Based EHRs2012In: Proceedings Scandinavian Conference on Health Informatics 2012, Linköping: Linköping University Electronic Press, 2012, p. 51-57Conference paper (Refereed)
    Abstract [en]

    There are very few published studies regarding the performance of persistence mechanisms for systems that use the openEHR multi level modelling approach. This paper addresses the performance and size of XML databases that store openEHR compliant documents. Database size and response times to epidemiological queries are described. An anonymized relational epidemiology database and associated epidemiological queries were used to generate openEHR XML documents that were stored and queried in four opensource XML databases. The XML databases were considerably slower and required much more space than the relational database. For population-wide epidemiological queries the response times scaled in order of magnitude at the same rate as the number of records (total database size) but were orders of magnitude slower than the original relational database. For individual focused clinical queries where patient ID was specified the response times were acceptable. This study suggests that the tested XML database configurations without further optimizations are not suitable as persistence mechanisms for openEHR-based systems in production if population-wide ad hoc querying is needed.

  • 3.
    Freire, Sergio Miranda
    et al.
    Linköping University, Department of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Departamento de Tecnologia da Informação e Educação em Saúde, Universidade do Estado do Rio de Janeiro, Rio de Janeiro, RJ, Brazil.
    Teodoro, Douglas
    Departamento de Tecnologia da Informação e Educação em Saúde, Universidade do Estado do Rio de Janeiro, Rio de Janeiro, RJ, Brazil .
    Wei-Kleiner, Fang
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Sundvall, Erik
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, Faculty of Science & Engineering. Region Östergötland.
    Karlsson, Daniel
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, Faculty of Science & Engineering.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
    Comparing the Performance of NoSQL Approaches for Managing Archetype-Based Electronic Health Record Data2016In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 11, no 3, article id e0150069Article in journal (Refereed)
    Abstract [en]

    This study provides an experimental performance evaluation on population-based queries of NoSQL databases storing archetype-based Electronic Health Record (EHR) data. There are few published studies regarding the performance of persistence mechanisms for systems that use multilevel modelling approaches, especially when the focus is on population-based queries. A healthcare dataset with 4.2 million records stored in a relational database (MySQL) was used to generate XML and JSON documents based on the openEHR reference model. Six datasets with different sizes were created from these documents and imported into three single machine XML databases (BaseX, eXistdb and Berkeley DB XML) and into a distributed NoSQL database system based on the MapReduce approach, Couchbase, deployed in different cluster configurations of 1, 2, 4, 8 and 12 machines. Population-based queries were submitted to those databases and to the original relational database. Database size and query response times are presented. The XML databases were considerably slower and required much more space than Couchbase. Overall, Couchbase had better response times than MySQL, especially for larger datasets. However, Couchbase requires indexing for each differently formulated query and the indexing time increases with the size of the datasets. The performances of the clusters with 2, 4, 8 and 12 nodes were not better than the single node cluster in relation to the query response time, but the indexing time was reduced proportionally to the number of nodes. The tested XML databases had acceptable performance for openEHR-based data in some querying use cases and small datasets, but were generally much slower than Couchbase. Couchbase also outperformed the response times of the relational database, but required more disk space and had a much longer indexing time. Systems like Couchbase are thus interesting research targets for scalable storage and querying of archetype-based EHR data when population-based use cases are of interest.

  • 4.
    Hojen, A.R.
    et al.
    Aalborg University, Denmark .
    Sundvall, Erik
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Goeg, K.R.
    Aalborg University, Denmark .
    Methods and applications for visualization of SNOMED CT concept sets2014In: Applied Clinical Informatics, ISSN 1869-0327, Vol. 5, no 1, p. 127-152Article in journal (Refereed)
    Abstract [en]

    Inconsistent use of SNOMED CT concepts may reduce comparability of information in health information systems. Terminology implementation should be approached by common strategies for navigating and selecting proper concepts. This study aims to explore ways of illustrating common pathways and ancestors of particular sets of concepts, to support consistent use of SNOMED CT and also assess potential applications for such visualizations. The open source prototype presented is an interactive web-based re-implementation of the terminology visualization tool TermViz that provides an overview of concepts and their hierarchical relations. It provides terminological features such as interactively rearranging graphs, fetching more concept nodes, highlighting least common parents and shared pathways in merged graphs etc. Four teams of three to four people used the prototype to complete a terminology mapping task and then, in focus group interviews, discussed the user experience and potential future tool usage. Potential purposes discussed included SNOMED CT search and training, consistent selection of concepts and content management. The evaluation indicated that the tool may be useful in many contexts especially if integrated with existing systems, and that the graph layout needs further tuning and development.

  • 5.
    Hägglund, Maria
    et al.
    Karolinska Institutet, Solna, Sverige.
    Karlsson, M. G. Daniel
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Klein, Gunnar
    Örebro Universitet, Örebro, Sverige.
    Koch, Sabine
    Karolinska Institutet, Solna, Sverige.
    Lindgren, Helena
    Umeå Universitet, Umeå, Sverige.
    Nyström, Mikael
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Scandurra, Isabella
    Örebro Universitet, Örebro, Sverige.
    Sundvall, Erik
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Världsbäst på eHälsa kräver internationellt samarbete2017In: Svenska dagbladet, ISSN 1101-2412Article in journal (Other (popular science, discussion, etc.))
    Abstract [sv]

    Det är glädjande att myndigheter nu äntligen tittar mer på internationellt delade detaljerade dokumentationsmodeller för innehåll i journaler. Vi hoppas att de ger tillräckligt kraftfulla och tydliga budskap så att de upphandlande vårdgivarna också ser vikten av detta. Om vi ska bli världsbäst på eHälsa krävs internationellt samarbete, skriver flera forskare i medicinsk informatik.

  • 6.
    Lind, Leili
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Sundvall, Erik
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Karlsson, Daniel
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Shahsavar, Nosrat
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Åhlfeldt, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Requirements and prototyping of a home health care application based on emerging JAVA technology.2002In: International Journal of Medical Informatics, ISSN 1386-5056, Vol. 68, no 1-3, p. 129-139Article in journal (Refereed)
    Abstract [en]

    IT support for home health care is an expanding area within health care IT development. Home health care differs from other in- or outpatient care delivery forms in a number of ways, and thus, the introduction of home health care applications must be based on a rigorous analysis of necessary requirements to secure safe and reliable health care. This article reports early experiences from the development of a home health care application based on emerging technologies. A prototype application for the follow-up of diabetes patients is presented and discussed in relation to a list of general requirements on home health care applications.

  • 7.
    Lind, Leili
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Sundvall, Erik
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Åhlfeldt, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Experiences from development of home health care applications based on emerging Java technology2001In: MEDINFO 2001,2001, Amsterdam: IOS Press , 2001, p. 830-Conference paper (Refereed)
  • 8.
    Nyström, Mikael
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Sundvall, Erik
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Eneling, Martin
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Karlsson, Daniel
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Petersson, Håkan
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Åhlfeldt, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Introduction to openEHR basic principles2008Conference paper (Refereed)
  • 9.
    Nyström, Mikael
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Sundvall, Erik
    Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Örman, Håkan
    Åhlfeldt, Hans
    Data Needs for Patient Overviews: A Literature ReviewCompared with SNOMED CT and openEHRManuscript (preprint) (Other academic)
    Abstract [en]

    Patient overviews automatically generated fromelectronic healthcare data have different data needsdepending on their complexity. A literature reviewbased on a broad MEDLINE search found 16 suchoverviews for which the data needs were analyzedand compared with features provided bySNOMED CT and openEHR. Five systems used onlyinformation type, while five systems also presentedparticular values from its information entities. Sixsystems also aggregated or filtered the information.In addition to that, two systems provided referenceranges and three systems provided more advanceddecision support. The simple data needs can be metusing information entity markups based onSNOMED CT and SNOMED CT relationships. Morecomplex data needs can be satisfied using theopenEHR reference model and archetypes tostructure data and the archetype query language toretrieve individual data values. The most advancedoverviews also need additional methods foraggregation, filtering and connection to knowledgerepresentation.

  • 10.
    Nyström, Mikael
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, Faculty of Science & Engineering.
    Örman, Håkan
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, Faculty of Science & Engineering.
    Lind, Leili
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, Faculty of Science & Engineering.
    Sundvall, Erik
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, Faculty of Science & Engineering.
    Shahsavar, Nosrat
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, Faculty of Science & Engineering.
    Karlsson, Daniel
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, Faculty of Science & Engineering.
    Det krävs en riktad satsning på e-hälsa2016In: Dagens medicin, ISSN 1104-7488, no 18, p. 22-Article in journal (Other (popular science, discussion, etc.))
  • 11.
    Pettersson, Mattias
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Wihlborg, Jenny
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Lövström, Rikard
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Sundvall, Erik
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Nyström, Mikael
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Karlsson, Daniel
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Systematizing medical alerts2008In: EHEALTH BEYOND THE HORIZON - GET IT THERE, ISSN 0926-9630, vol 136, 2008, Vol. 136, p. 753-758Conference paper (Refereed)
    Abstract [en]

    The current Swedish regulations for medical alerts in health records were designed for paper records. Suggestions for computerized systems are now being investigated. A proposed model using three alert categories, graphically represented using three directions, probably combined with three severity levels is presented here. Up represents hypersensitivities, left/back represents alerting diagnosis and right/forward represents alerting current and planned treatments. A small qualitative user study of the alert classification model and some graphical representations of it was conducted. One main finding is that most respondents found the use of directions intuitive as a means of presenting categories. Context dependency, information overload, and future possibilities for automated alert-gathering are also discussed in the paper.

  • 12.
    Randorff Højen, Anne
    et al.
    Department of Health Science and Technology, Medical Informatics, Aalborg University, Denmark.
    Sundvall, Erik
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Rosenbeck Gøeg, Kirstine
    Department of Health Science and Technology, Medical Informatics, Aalborg University, Denmark.
    Visualizing sets of SNOMED CT concepts to support consistent terminology implementation and reuse of clinical dataManuscript (preprint) (Other academic)
    Abstract [en]

    Inconsistent use of concepts is an obstacle when implementing SNOMED CT to improve comparability of information. Terminology implementation should be approached by common strategies for navigating and selecting proper concepts. This study aims to explore ways of illustrating common pathways and ancestors of particular sets of concepts, to support consistent use of SNOMED CT in EHR-system implementation processes. The prototype presented here is an interactive web-based reimplementation of the terminology visualization tool TermViz. The open source prototype contains terminological features that are of relevance when exploring and comparing sets of concepts in SNOMED CT. This includes interactively rearranging graphs, fetching more concept nodes, illustrating least common parents and shared pathways in merged graphs etc. Future work should focus on evaluating the developed prototype in order to assess its applicability in EHR-system-implementation contexts.

  • 13.
    Sundvall, Erik
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Scalability and Semantic Sustainability in Electronic Health Record Systems2013Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    This work is a small contribution to the greater goal of making software systems used in healthcare more useful and sustainable. To come closer to that goal, health record data will need to be more computable and easier to exchange between systems.

    Interoperability refers to getting systems to work together and semantics concerns the study of meanings. If Semantic interoperability is achieved then information entered in one information system is usable in other systems and reusable for many purposes. Scalability refers to the extent to which a system can gracefully grow by adding more resources. Sustainability refers more to how to best use available limited resources. Both aspects are important.

    The main focus and aim of the thesis is to increase knowledge about how to support scalability and semantic sustainability. It reports explorations of how to apply aspects of the above to Electronic Health Record (EHR) systems, associated infrastructure, data structures, terminology systems, user interfaces and their mutual boundaries.

    Using terminology systems is one way to improve computability and comparability of data. Modern complex ontologies and terminology systems can contain hundreds of thousands of concepts that can have many kinds of relationships to multiple other concepts. This makes visualization challenging. Many visualization approaches designed to show the local neighbourhood of a single concept node do not scale well to larger sets of nodes. The interactive TermViz approach described in this thesis, is designed to aid users to navigate and comprehend the context of several nodes simultaneously. Two applications are presented where TermViz aids management of the boundary between EHR data structures and the terminology system SNOMED CT.

    The amount of available time from people skilled in health informatics is limited. Adequate methods and tools are required to develop, maintain and reuse health-IT solutions in a sustainable way. Multiple levels of modelling including a fixed reference model and another layer of flexible reusable ‘archetypes’ for domain specific data structures, is an approach with that aim used in openEHR and the ISO 13606 standard. This approach, including learning, implementing and managing it, is explored from different angles in this thesis. An architecture applying Representational State Transfer (REST) to archetype-based EHR systems, in order to address scalability, is presented. Combined with archetyping this architecture also aims at enabling a sustainable way of continuously evolving multi-vendor EHR solutions. An experimental open source implementation of it, aimed for learning and prototyping, is also presented.

    Manually changing database structures used for storage every time new versions of archetypes and associated data structures are needed is likely not a sustainable activity. Thus storage systems that can handle change with minimal manual interventions are desirable. Initial explorations of performance and scalability in such systems are also reported

    Graphical user interfaces focused on EHR navigation, time-perspectives and highlighting of EHR content are also presented – illustrating what can be done with computable health record data and the presented approaches.

    Desirable aspects of semantic sustainability have been discussed, including: sustainable use of limited resources (such as available time of skilled people), and reduction of unnecessary risks. A semantic sustainability perspective should be inspired and informed by research in complex systems theory, and should also include striving to be highly aware of when and where technical debt is being built up. Semantic sustainability is a shared responsibility.

    The combined results presented contribute to increasing knowledge about ways to support scalability and semantic sustainability in the context of electronic health record systems. Supporting tools, architectures and approaches are additional contributions.

    List of papers
    1. Interactive Visualization and Navigation of Complex Terminology Systems, Exemplified by SNOMED CT
    Open this publication in new window or tab >>Interactive Visualization and Navigation of Complex Terminology Systems, Exemplified by SNOMED CT
    2006 (English)In: Ubiquity: Technologies for Better Health in Aging Societies - Proceedings of MIE2006 / [ed] Arie Hasman, Reinhold Haux, Johan van der Lei, Etienne De Clercq, Francis Roger-France, IOS Press , 2006, p. 851-856Conference paper, Published paper (Refereed)
    Abstract [en]

    Free-text queries are natural entries into the exploration of complex terminology systems. The way search results are presented has impact on the users ability to grasp the overall structure of the system. Complex hierarchies like the one used in SNOMED CT, where nodes have multiple parents (IS-A) and several other relationship types, makes visualization challenging. This paper presents a prototype, Term Viz, applying well known methods like "focus+context" and self-organizing layouts from the fields of Information Visualization and Graph Drawing to terminologies like SNOMED CT and ICD-10. The user can simultaneously focus on several nodes in the terminologies and then use interactive animated graph navigation and semantic zooming to further explore the terminology systems without loosing context. The prototype, based on Open Source Java components, demonstrates how a number of Information Visualisation methods can aid the exploration of medical terminologies with millions of elements and can serve as a base for further development.

    Place, publisher, year, edition, pages
    IOS Press, 2006
    Series
    Studies in Health Technology and Informatics, ISSN 0926-9630 ; 124
    Keywords
    Terminology, Information Visualization, SNOMED CT, Medical Informatics
    National Category
    Engineering and Technology
    Identifiers
    urn:nbn:se:liu:diva-38011 (URN)000281143200121 ()17108619 (PubMedID)41106 (Local ID)978-1-58603-647-8 (ISBN)41106 (Archive number)41106 (OAI)
    Conference
    International Congress of the European Federation for Medical Informatics, 27-30 August 2006, Maastricht, The Netherlands
    Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2013-05-15
    2. Visualizing sets of SNOMED CT concepts to support consistent terminology implementation and reuse of clinical data
    Open this publication in new window or tab >>Visualizing sets of SNOMED CT concepts to support consistent terminology implementation and reuse of clinical data
    (English)Manuscript (preprint) (Other academic)
    Abstract [en]

    Inconsistent use of concepts is an obstacle when implementing SNOMED CT to improve comparability of information. Terminology implementation should be approached by common strategies for navigating and selecting proper concepts. This study aims to explore ways of illustrating common pathways and ancestors of particular sets of concepts, to support consistent use of SNOMED CT in EHR-system implementation processes. The prototype presented here is an interactive web-based reimplementation of the terminology visualization tool TermViz. The open source prototype contains terminological features that are of relevance when exploring and comparing sets of concepts in SNOMED CT. This includes interactively rearranging graphs, fetching more concept nodes, illustrating least common parents and shared pathways in merged graphs etc. Future work should focus on evaluating the developed prototype in order to assess its applicability in EHR-system-implementation contexts.

    Keywords
    Clinical terminology, Implementation, SNOMED CT, Information Visualization
    National Category
    Information Systems
    Identifiers
    urn:nbn:se:liu:diva-87693 (URN)
    Available from: 2013-01-22 Created: 2013-01-22 Last updated: 2018-01-11
    3. Integration of Tools for Binding Archetypes to SNOMED CT
    Open this publication in new window or tab >>Integration of Tools for Binding Archetypes to SNOMED CT
    Show others...
    2008 (English)In: BMC Medical Informatics and Decision Making, ISSN 1472-6947, E-ISSN 1472-6947, Vol. 8, no S7Article in journal (Refereed) Published
    Abstract [en]

    Background

    The Archetype formalism and the associated Archetype Definition Language have been proposed as an ISO standard for specifying models of components of electronic healthcare records as a means of achieving interoperability between clinical systems. This paper presents an archetype editor with support for manual or semi-automatic creation of bindings between archetypes and terminology systems.

    Methods

    Lexical and semantic methods are applied in order to obtain automatic mapping suggestions. Information visualisation methods are also used to assist the user in exploration and selection of mappings.

    Results

    An integrated tool for archetype authoring, semi-automatic SNOMED CT terminology binding assistance and terminology visualization was created and released as open source.

    Conclusion

    Finding the right terms to bind is a difficult task but the effort to achieve terminology bindings may be reduced with the help of the described approach. The methods and tools presented are general, but here only bindings between SNOMED CT and archetypes based on the openEHR reference model are presented in detail.

    Background

    The Archetype formalism and the associated Archetype Definition Language have been proposed as an ISO standard for specifying models of components of electronic healthcare records as a means of achieving interoperability between clinical systems. This paper presents an archetype editor with support for manual or semi-automatic creation of bindings between archetypes and terminology systems.

    Methods

    Lexical and semantic methods are applied in order to obtain automatic mapping suggestions. Information visualisation methods are also used to assist the user in exploration and selection of mappings.

    Results

    An integrated tool for archetype authoring, semi-automatic SNOMED CT terminology binding assistance and terminology visualization was created and released as open source.

    Conclusion

    Finding the right terms to bind is a difficult task but the effort to achieve terminology bindings may be reduced with the help of the described approach. The methods and tools presented are general, but here only bindings between SNOMED CT and archetypes based on the openEHR reference model are presented in detail.

    Place, publisher, year, edition, pages
    Springer, 2008
    National Category
    Medical and Health Sciences
    Identifiers
    urn:nbn:se:liu:diva-43812 (URN)10.1186/1472-6947-8-S1-S7 (DOI)000277030600007 ()74857 (Local ID)74857 (Archive number)74857 (OAI)
    Note

    Original Publication: Erik Sundvall, Rahil Qamar, Mikael Nyström, Mattias Forss, Håkan Petersson, Hans Åhlfeldt and Alan Rector, Integration of Tools for Binding Archetypes to SNOMED CT, 2008, BMC Medical Informatics and Decision Making, (8), S7. http://dx.doi.org/10.1186/1472-6947-8-S1-S7 Licensee: BioMed Central http://www.biomedcentral.com/

    Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2017-12-13
    4. Applying representational state transfer (REST) architecture to archetype-based electronic health record systems
    Open this publication in new window or tab >>Applying representational state transfer (REST) architecture to archetype-based electronic health record systems
    Show others...
    2013 (English)In: BMC Medical Informatics and Decision Making, ISSN 1472-6947, E-ISSN 1472-6947, Vol. 13, no 57Article in journal (Refereed) Published
    Abstract [en]

    Background

    The openEHR project and the closely related ISO 13606 standard have defined structures supporting the content of Electronic Health Records (EHRs). However, there is not yet any finalized openEHR specification of a service interface to aid application developers in creating, accessing, and storing the EHR content.

    The aim of this paper is to explore how the Representational State Transfer (REST) architectural style can be used as a basis for a platform-independent, HTTP-based openEHR service interface. Associated benefits and tradeoffs of such a design are also explored.

    Results

    The main contribution is the formalization of the openEHR storage, retrieval, and version-handling semantics and related services into an implementable HTTP-based service interface. The modular design makes it possible to prototype, test, replicate, distribute, cache, and load-balance the system using ordinary web technology. Other contributions are approaches to query and retrieval of the EHR content that takes caching, logging, and distribution into account. Triggering on EHR change events is also explored.

    A final contribution is an open source openEHR implementation using the above-mentioned approaches to create LiU EEE, an educational EHR environment intended to help newcomers and developers experiment with and learn about the archetype-based EHR approach and enable rapid prototyping.

    Conclusions

    Using REST addressed many architectural concerns in a successful way, but an additional messaging component was needed to address some architectural aspects. Many of our approaches are likely of value to other archetype-based EHR implementations and may contribute to associated service model specifications.

    Place, publisher, year, edition, pages
    BioMed Central, 2013
    National Category
    Information Systems
    Identifiers
    urn:nbn:se:liu:diva-87696 (URN)10.1186/1472-6947-13-57 (DOI)000320998000001 ()
    Available from: 2013-01-22 Created: 2013-01-22 Last updated: 2018-01-11
    5. Performance of XML Databases for Epidemiological Queries in Archetype-Based EHRs
    Open this publication in new window or tab >>Performance of XML Databases for Epidemiological Queries in Archetype-Based EHRs
    2012 (English)In: Proceedings Scandinavian Conference on Health Informatics 2012, Linköping: Linköping University Electronic Press, 2012, p. 51-57Conference paper, Published paper (Refereed)
    Abstract [en]

    There are very few published studies regarding the performance of persistence mechanisms for systems that use the openEHR multi level modelling approach. This paper addresses the performance and size of XML databases that store openEHR compliant documents. Database size and response times to epidemiological queries are described. An anonymized relational epidemiology database and associated epidemiological queries were used to generate openEHR XML documents that were stored and queried in four opensource XML databases. The XML databases were considerably slower and required much more space than the relational database. For population-wide epidemiological queries the response times scaled in order of magnitude at the same rate as the number of records (total database size) but were orders of magnitude slower than the original relational database. For individual focused clinical queries where patient ID was specified the response times were acceptable. This study suggests that the tested XML database configurations without further optimizations are not suitable as persistence mechanisms for openEHR-based systems in production if population-wide ad hoc querying is needed.

    Place, publisher, year, edition, pages
    Linköping: Linköping University Electronic Press, 2012
    Series
    Linköping Electronic Conference Proceedings, ISSN 1650-3686, E-ISSN 1650-3740 ; 70
    Keywords
    Medical Record Systems, Computerized; Database Management Systems, Archetypes, XML Databases, openEHR
    National Category
    Computer and Information Sciences
    Identifiers
    urn:nbn:se:liu:diva-84401 (URN)978-91-7519-758-6 (ISBN)
    Conference
    Scandinavian Conference on Health Informatics 2012, October 2-3, Linköping, Sweden
    Available from: 2012-10-05 Created: 2012-10-05 Last updated: 2018-02-19Bibliographically approved
    6. Approaches to learning openEHR: a qualitative survey, observations, and suggestions
    Open this publication in new window or tab >>Approaches to learning openEHR: a qualitative survey, observations, and suggestions
    2016 (English)In: Proceedings from the 14th Scandinavian Conference on Health Informatics 2016: Gothenburg, Sweden, April 6-7 2016 / [ed] Daniel Karlsson, Andrius Budrionis, Ann Bygholm, Mariann Fossum, Conceicao Granja, Gunnar Hartvigsen, Ole Hejlesen, Maria Hägglund, Monika Alise Johansen, Carl E Moe, Luis Marco-Ruiz, Vivian Vimarlund, Kassaye Y Yigzaw, Linköping: Linköping University Electronic Press, 2016, Vol. 122, p. 29-36Conference paper, Published paper (Refereed)
    Abstract [en]

    Approaches such as ISO 13606 and openEHR aim to address data reusability by defining clinical data structures called archetypes and templates, based on a reference model. A problem with these approaches is that parts of them currently are rather difficult to learn. It can be hard to imagine what an archetype-based clinical system combined with modern terminology systems will look like and what consequences different modeling choices have, without seeing and experimenting with an operational system. This paper reports findings from a survey among openEHR learners and educators combined with observations of related openEHR mailing list discussions. The paper ends with an opinion piece, where we discuss potentially fruitful ways to learn, explore, and extend archetype-based EHR systems using visualization and examples.The findings highlight potential stumble blocks and solutions and should be of interest for both educators and self-learners.

    Place, publisher, year, edition, pages
    Linköping: Linköping University Electronic Press, 2016
    Series
    Linköping Electronic Conference Proceedings, ISSN 1650-3686, E-ISSN 1650-3740 ; 122
    Keywords
    Electronic Health Records; Software; Learning; Standards
    National Category
    Information Systems
    Identifiers
    urn:nbn:se:liu:diva-87701 (URN)9789176857762 (ISBN)
    Conference
    The 14th Scandinavian Conference on Health Informatics 2016, Gothenburg, Sweden, April 6-7 2016
    Available from: 2013-01-22 Created: 2013-01-22 Last updated: 2018-02-05Bibliographically approved
    7. Graphical Overview and Navigation of Electronic Health Records in a prototyping environment using Google Earth and openEHR Archetypes
    Open this publication in new window or tab >>Graphical Overview and Navigation of Electronic Health Records in a prototyping environment using Google Earth and openEHR Archetypes
    Show others...
    2007 (English)In: MEDINFO 2007 - Proceedings of the 12th World Congress on Health (Medical) Informatics – Building Sustainable Health Systems / [ed] Klaus A. Kuhn, James R. Warren, Tze-Yun Leong, IOS Press, 2007, p. 1043-1047Conference paper, Published paper (Refereed)
    Abstract [en]

    This paper describes selected earlier approaches to graphically relating events to each other and to time; some new combinations are also suggested. These are then combined into a unified prototyping environment for visualization and navigation of electronic health records. Google Earth (GE) is used for handling display and interaction of clinical information stored using openEHR data structures and ‘archetypes’. The strength of the approach comes from GE's sophisticated handling of detail levels, from coarse overviews to fine-grained details that has been combined with linear, polar and region-based views of clinical events related to time. The system should be easy to learn since all the visualization styles can use the same navigation.

    The structured and multifaceted approach to handling time that is possible with archetyped openEHR data lends itself well to visualizing and integration with openEHR components is provided in the environment.

    Place, publisher, year, edition, pages
    IOS Press, 2007
    Series
    Studies in Health Technology and Informatics, ISSN 0926-9630 ; 129
    National Category
    Medical and Health Sciences
    Identifiers
    urn:nbn:se:liu:diva-38012 (URN)17911874 (PubMedID)41107 (Local ID)978-1-58603-774-1 (ISBN)41107 (Archive number)41107 (OAI)
    Conference
    12th World Congress on Health (Medical) Informatics – Building Sustainable Health Systems (MEDINFO 2007), 20-24 August 2007, Brisbane, Australia
    Funder
    EU, FP7, Seventh Framework Programme
    Available from: 2012-09-27 Created: 2009-10-10 Last updated: 2015-09-22Bibliographically approved
  • 14.
    Sundvall, Erik
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Nyström, Mikael
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Forss, Mattias
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Chen, Rong
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Petersson, Håkan
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Åhlfeldt, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Graphical Overview and Navigation of Electronic Health Records in a prototyping environment using Google Earth and openEHR Archetypes2007In: MEDINFO 2007 - Proceedings of the 12th World Congress on Health (Medical) Informatics – Building Sustainable Health Systems / [ed] Klaus A. Kuhn, James R. Warren, Tze-Yun Leong, IOS Press, 2007, p. 1043-1047Conference paper (Refereed)
    Abstract [en]

    This paper describes selected earlier approaches to graphically relating events to each other and to time; some new combinations are also suggested. These are then combined into a unified prototyping environment for visualization and navigation of electronic health records. Google Earth (GE) is used for handling display and interaction of clinical information stored using openEHR data structures and ‘archetypes’. The strength of the approach comes from GE's sophisticated handling of detail levels, from coarse overviews to fine-grained details that has been combined with linear, polar and region-based views of clinical events related to time. The system should be easy to learn since all the visualization styles can use the same navigation.

    The structured and multifaceted approach to handling time that is possible with archetyped openEHR data lends itself well to visualizing and integration with openEHR components is provided in the environment.

  • 15.
    Sundvall, Erik
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Nyström, Mikael
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Karlsson, Daniel
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Eneling, Martin
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Chen, Rong
    Cambio Healthcare Systems.
    Örman, Håkan
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Applying representational state transfer (REST) architecture to archetype-based electronic health record systems2013In: BMC Medical Informatics and Decision Making, ISSN 1472-6947, E-ISSN 1472-6947, Vol. 13, no 57Article in journal (Refereed)
    Abstract [en]

    Background

    The openEHR project and the closely related ISO 13606 standard have defined structures supporting the content of Electronic Health Records (EHRs). However, there is not yet any finalized openEHR specification of a service interface to aid application developers in creating, accessing, and storing the EHR content.

    The aim of this paper is to explore how the Representational State Transfer (REST) architectural style can be used as a basis for a platform-independent, HTTP-based openEHR service interface. Associated benefits and tradeoffs of such a design are also explored.

    Results

    The main contribution is the formalization of the openEHR storage, retrieval, and version-handling semantics and related services into an implementable HTTP-based service interface. The modular design makes it possible to prototype, test, replicate, distribute, cache, and load-balance the system using ordinary web technology. Other contributions are approaches to query and retrieval of the EHR content that takes caching, logging, and distribution into account. Triggering on EHR change events is also explored.

    A final contribution is an open source openEHR implementation using the above-mentioned approaches to create LiU EEE, an educational EHR environment intended to help newcomers and developers experiment with and learn about the archetype-based EHR approach and enable rapid prototyping.

    Conclusions

    Using REST addressed many architectural concerns in a successful way, but an additional messaging component was needed to address some architectural aspects. Many of our approaches are likely of value to other archetype-based EHR implementations and may contribute to associated service model specifications.

  • 16.
    Sundvall, Erik
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Nyström, Mikael
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Petersson, Håkan
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Åhlfeldt, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Interactive Visualization and Navigation of Complex Terminology Systems, Exemplified by SNOMED CT2006In: Ubiquity: Technologies for Better Health in Aging Societies - Proceedings of MIE2006 / [ed] Arie Hasman, Reinhold Haux, Johan van der Lei, Etienne De Clercq, Francis Roger-France, IOS Press , 2006, p. 851-856Conference paper (Refereed)
    Abstract [en]

    Free-text queries are natural entries into the exploration of complex terminology systems. The way search results are presented has impact on the users ability to grasp the overall structure of the system. Complex hierarchies like the one used in SNOMED CT, where nodes have multiple parents (IS-A) and several other relationship types, makes visualization challenging. This paper presents a prototype, Term Viz, applying well known methods like "focus+context" and self-organizing layouts from the fields of Information Visualization and Graph Drawing to terminologies like SNOMED CT and ICD-10. The user can simultaneously focus on several nodes in the terminologies and then use interactive animated graph navigation and semantic zooming to further explore the terminology systems without loosing context. The prototype, based on Open Source Java components, demonstrates how a number of Information Visualisation methods can aid the exploration of medical terminologies with millions of elements and can serve as a base for further development.

  • 17.
    Sundvall, Erik
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Qamar, Rahil
    Dep of Computer Science University of Manchester, UK.
    Nyström, Mikael
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Forss, Mattias
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Petersson, Håkan
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Åhlfeldt, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Rector, Alan
    Dep of Computer Science University of Manchester, UK.
    Integration of Tools for Binding Archetypes to SNOMED CT2006Conference paper (Other academic)
    Abstract [en]

    The Archetype formalism and the associated Archetype Definition Language have been proposed as standard for specifying models of components of Electronic Healthcare Records as a means of achieving interoperability between clinical systems. This paper presents an archetype editor with support for manual or semi-automatic creation of bindings between archetypes and terminology systems. Lexical and semantic methods are applied in order to obtain automatic mapping suggestions. Information visualisation methods are also used to assist the user in exploration and selection of mappings.

    The methods and tools presented are general, but here only bindings between SNOMED CT and archetypes based on the openEHR reference model are presented in detail.

  • 18.
    Sundvall, Erik
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Qamar, Rahil
    Department of Computer Science University of Manchester, UK.
    Nyström, Mikael
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Forss, Mattias
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Petersson, Håkan
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Åhlfeldt, Hans
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Rector, Alan
    Department of Computer Science University of Manchester, UK.
    Integration of Tools for Binding Archetypes to SNOMED CT2008In: BMC Medical Informatics and Decision Making, ISSN 1472-6947, E-ISSN 1472-6947, Vol. 8, no S7Article in journal (Refereed)
    Abstract [en]

    Background

    The Archetype formalism and the associated Archetype Definition Language have been proposed as an ISO standard for specifying models of components of electronic healthcare records as a means of achieving interoperability between clinical systems. This paper presents an archetype editor with support for manual or semi-automatic creation of bindings between archetypes and terminology systems.

    Methods

    Lexical and semantic methods are applied in order to obtain automatic mapping suggestions. Information visualisation methods are also used to assist the user in exploration and selection of mappings.

    Results

    An integrated tool for archetype authoring, semi-automatic SNOMED CT terminology binding assistance and terminology visualization was created and released as open source.

    Conclusion

    Finding the right terms to bind is a difficult task but the effort to achieve terminology bindings may be reduced with the help of the described approach. The methods and tools presented are general, but here only bindings between SNOMED CT and archetypes based on the openEHR reference model are presented in detail.

    Background

    The Archetype formalism and the associated Archetype Definition Language have been proposed as an ISO standard for specifying models of components of electronic healthcare records as a means of achieving interoperability between clinical systems. This paper presents an archetype editor with support for manual or semi-automatic creation of bindings between archetypes and terminology systems.

    Methods

    Lexical and semantic methods are applied in order to obtain automatic mapping suggestions. Information visualisation methods are also used to assist the user in exploration and selection of mappings.

    Results

    An integrated tool for archetype authoring, semi-automatic SNOMED CT terminology binding assistance and terminology visualization was created and released as open source.

    Conclusion

    Finding the right terms to bind is a difficult task but the effort to achieve terminology bindings may be reduced with the help of the described approach. The methods and tools presented are general, but here only bindings between SNOMED CT and archetypes based on the openEHR reference model are presented in detail.

  • 19.
    Sundvall, Erik
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, Faculty of Science & Engineering.
    Siivonen, Dominique
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
    Örman, Håkan
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, Faculty of Science & Engineering.
    Approaches to learning openEHR: a qualitative survey, observations, and suggestions2016In: Proceedings from the 14th Scandinavian Conference on Health Informatics 2016: Gothenburg, Sweden, April 6-7 2016 / [ed] Daniel Karlsson, Andrius Budrionis, Ann Bygholm, Mariann Fossum, Conceicao Granja, Gunnar Hartvigsen, Ole Hejlesen, Maria Hägglund, Monika Alise Johansen, Carl E Moe, Luis Marco-Ruiz, Vivian Vimarlund, Kassaye Y Yigzaw, Linköping: Linköping University Electronic Press, 2016, Vol. 122, p. 29-36Conference paper (Refereed)
    Abstract [en]

    Approaches such as ISO 13606 and openEHR aim to address data reusability by defining clinical data structures called archetypes and templates, based on a reference model. A problem with these approaches is that parts of them currently are rather difficult to learn. It can be hard to imagine what an archetype-based clinical system combined with modern terminology systems will look like and what consequences different modeling choices have, without seeing and experimenting with an operational system. This paper reports findings from a survey among openEHR learners and educators combined with observations of related openEHR mailing list discussions. The paper ends with an opinion piece, where we discuss potentially fruitful ways to learn, explore, and extend archetype-based EHR systems using visualization and examples.The findings highlight potential stumble blocks and solutions and should be of interest for both educators and self-learners.

  • 20.
    Sundvall, Erik
    et al.
    Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering.
    Wei-Kleiner, Fang
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Freire, Sergio Miranda
    Universidade do Estado do Rio de Janeiro, Brazil.
    Lambrix, Patrick
    Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
    Querying archetype-based Electronic Health Records using Hadoop and Dewey encoding of openEHR models2017In: Informatics for Health: Connected Citizen-Led Wellness and Population Health / [ed] Rebecca Randell; Ronald Cornet; Colin McCowan; Niels Peek; Philip J. Scott, Amsterdam, The Netherlands: IOS Press, 2017, p. 406-410Conference paper (Refereed)
    Abstract [en]

    Archetype-based Electronic Health Record (EHR) systems using generic reference models from e.g. openEHR, ISO 13606 or CIMI should be easy to update and reconfigure with new types (or versions) of data models or entries, ideally with very limited programming or manual database tweaking. Exploratory research (e.g. epidemiology) leading to ad-hoc querying on a population-wide scale can be a challenge in such environments. This publication describes implementation and test of an archetype-aware Dewey encoding optimization that can be used to produce such systems in environments supporting relational operations, e.g. RDBMs and distributed map-reduce frameworks like Hadoop. Initial testing was done using a nine-node 2.2 GHz quad-core Hadoop cluster querying a dataset consisting of targeted extracts from 4+ million real patient EHRs, query results with sub-minute response time were obtained.

  • 21.
    Åhlfeldt, Hans
    et al.
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Karlsson, Daniel
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Petersson, Håkan
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Chen, Rong
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Nyström, Mikael
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Sundvall, Erik
    Linköping University, The Institute of Technology. Linköping University, Department of Biomedical Engineering, Medical Informatics.
    Advancement in the standardisation of the EHR2007In: 5th Scandinavian Conference on Health Informatics 2007, 2007Conference paper (Refereed)
1 - 21 of 21
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