STEP: An ontology-based smart clinical document template editing and production system

Clinical documents are complex in nature and reflective of the knowledge, structured or otherwise, of physicians. A clinical document template (CDT) is that in which this knowledge manifests itself in various relations that exist among clinical concepts or entities. In this work, we present (1) CDT ontology, (2) A web-based knowledge management system called STEP (Smart Template Editing and Production), (3) Web Services Interfaces to STEP, and (4) A GUI-based CDT editor that uses the Web Services. The CDT ontology explicitly specifies clinical document constituents called template description entities (TDE), and their inter-relations in the CDT. STEP stores CDTs and their components in accordance with the CDT ontology. Web Service interfaces were developed for search, retrieval and storage for CDTs and TDEs. STEP holds entities and relations in use, spanning across different functions such as admission and discharge. A GUI-based CDT editor was developed that uses the Web Services to access data stored in STEP.

[1]  Christopher G. Chute,et al.  Implementation Brief: LexGrid: A Framework for Representing, Storing, and Querying Biomedical Terminologies from Simple to Sublime , 2009, J. Am. Medical Informatics Assoc..

[2]  Byung-Hyun Ha,et al.  A multi-layered application for the gross description using Semantic Web technology , 2005, Int. J. Medical Informatics.

[3]  Phillip W. Lord,et al.  Semantic Similarity in Biomedical Ontologies , 2009, PLoS Comput. Biol..

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

[5]  Yan Z. Heras,et al.  Clinical Element Model , 2008 .

[6]  Anneke T. M. Goossen-Baremans,et al.  Detailed Clinical Models: A Review , 2010, Healthcare informatics research.

[7]  Catalina Martínez-Costa,et al.  A model-driven approach for representing clinical archetypes for Semantic Web environments , 2009, J. Biomed. Informatics.

[8]  Stanley M. Huff,et al.  Standards for detailed clinical models as the basis for medical data exchange and decision support , 2003, Int. J. Medical Informatics.

[9]  Miguel-Ángel Sicilia,et al.  Integrating reasoning and clinical archetypes using OWL ontologies and SWRL rules , 2011, J. Biomed. Informatics.

[10]  Christopher G Chute,et al.  An OWL meta-ontology for representing the Clinical Element Model. , 2011, AMIA ... Annual Symposium proceedings. AMIA Symposium.

[11]  David K. Vawdrey Assessing Usage Patterns of Electronic Clinical Documentation Templates , 2008, AMIA.

[12]  Amit P. Sheth,et al.  SPARQL-ST: Extending SPARQL to Support Spatiotemporal Queries , 2011, Geospatial Semantics and the Semantic Web.

[13]  Anna Rumshisky,et al.  Temporal reasoning over clinical text: the state of the art , 2013, J. Am. Medical Informatics Assoc..

[14]  Rong Chen,et al.  Archetype-Based Knowledge Management for Semantic Interoperability of Electronic Health Records , 2009, MIE.

[15]  Thomas Beale Archetypes and the EHR. , 2003, Studies in health technology and informatics.

[16]  Gerhard Weikum,et al.  YAGO2: A Spatially and Temporally Enhanced Knowledge Base from Wikipedia: Extended Abstract , 2013, IJCAI.