A Standards-based Semantic Metadata Repository to Support EHR-driven Phenotype Authoring and Execution

This study describes our efforts in developing a standards-based semantic metadata repository for supporting electronic health record (EHR)-driven phenotype authoring and execution. Our system comprises three layers: 1) a semantic data element repository layer; 2) a semantic services layer; and 3) a...

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Autores principales: Jiang, Guoqian, Solbrig, Harold R., Kiefer, Richard, Rasmussen, Luke V., Mo, Huan, Speltz, Peter, Thompson, William K., Denny, Joshua C., Chute, Christopher G., Pathak, Jyotishman
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2015
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4898771/
https://www.ncbi.nlm.nih.gov/pubmed/26262397
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author Jiang, Guoqian
Solbrig, Harold R.
Kiefer, Richard
Rasmussen, Luke V.
Mo, Huan
Speltz, Peter
Thompson, William K.
Denny, Joshua C.
Chute, Christopher G.
Pathak, Jyotishman
author_facet Jiang, Guoqian
Solbrig, Harold R.
Kiefer, Richard
Rasmussen, Luke V.
Mo, Huan
Speltz, Peter
Thompson, William K.
Denny, Joshua C.
Chute, Christopher G.
Pathak, Jyotishman
author_sort Jiang, Guoqian
collection PubMed
description This study describes our efforts in developing a standards-based semantic metadata repository for supporting electronic health record (EHR)-driven phenotype authoring and execution. Our system comprises three layers: 1) a semantic data element repository layer; 2) a semantic services layer; and 3) a phenotype application layer. In a prototype implementation, we developed the repository and services through integrating the data elements from both Quality Data Model (QDM) and HL7 Fast Healthcare Inteoroperability Resources (FHIR) models. We discuss the modeling challenges and the potential of our system to support EHR phenotype authoring and execution applications.
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spelling pubmed-48987712016-06-08 A Standards-based Semantic Metadata Repository to Support EHR-driven Phenotype Authoring and Execution Jiang, Guoqian Solbrig, Harold R. Kiefer, Richard Rasmussen, Luke V. Mo, Huan Speltz, Peter Thompson, William K. Denny, Joshua C. Chute, Christopher G. Pathak, Jyotishman Stud Health Technol Inform Article This study describes our efforts in developing a standards-based semantic metadata repository for supporting electronic health record (EHR)-driven phenotype authoring and execution. Our system comprises three layers: 1) a semantic data element repository layer; 2) a semantic services layer; and 3) a phenotype application layer. In a prototype implementation, we developed the repository and services through integrating the data elements from both Quality Data Model (QDM) and HL7 Fast Healthcare Inteoroperability Resources (FHIR) models. We discuss the modeling challenges and the potential of our system to support EHR phenotype authoring and execution applications. 2015 /pmc/articles/PMC4898771/ /pubmed/26262397 Text en http://creativecommons.org/licenses/by-nc/4.0/ This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License.
spellingShingle Article
Jiang, Guoqian
Solbrig, Harold R.
Kiefer, Richard
Rasmussen, Luke V.
Mo, Huan
Speltz, Peter
Thompson, William K.
Denny, Joshua C.
Chute, Christopher G.
Pathak, Jyotishman
A Standards-based Semantic Metadata Repository to Support EHR-driven Phenotype Authoring and Execution
title A Standards-based Semantic Metadata Repository to Support EHR-driven Phenotype Authoring and Execution
title_full A Standards-based Semantic Metadata Repository to Support EHR-driven Phenotype Authoring and Execution
title_fullStr A Standards-based Semantic Metadata Repository to Support EHR-driven Phenotype Authoring and Execution
title_full_unstemmed A Standards-based Semantic Metadata Repository to Support EHR-driven Phenotype Authoring and Execution
title_short A Standards-based Semantic Metadata Repository to Support EHR-driven Phenotype Authoring and Execution
title_sort standards-based semantic metadata repository to support ehr-driven phenotype authoring and execution
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4898771/
https://www.ncbi.nlm.nih.gov/pubmed/26262397
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