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Mining Electronic Health Records using Linked Data

Meaningful Use guidelines have pushed the United States Healthcare System to adopt electronic health record systems (EHRs) at an unprecedented rate. Hospitals and medical centers are providing access to clinical data via clinical data warehouses such as i2b2, or Stanford’s STRIDE database. In order...

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Detalles Bibliográficos
Autores principales: Odgers, David J., Dumontier, Michel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Informatics Association 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4525267/
https://www.ncbi.nlm.nih.gov/pubmed/26306276
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author Odgers, David J.
Dumontier, Michel
author_facet Odgers, David J.
Dumontier, Michel
author_sort Odgers, David J.
collection PubMed
description Meaningful Use guidelines have pushed the United States Healthcare System to adopt electronic health record systems (EHRs) at an unprecedented rate. Hospitals and medical centers are providing access to clinical data via clinical data warehouses such as i2b2, or Stanford’s STRIDE database. In order to realize the potential of using these data for translational research, clinical data warehouses must be interoperable with standardized health terminologies, biomedical ontologies, and growing networks of Linked Open Data such as Bio2RDF. Applying the principles of Linked Data, we transformed a de-identified version of the STRIDE into a semantic clinical data warehouse containing visits, labs, diagnoses, prescriptions, and annotated clinical notes. We demonstrate the utility of this system though basic cohort selection, phenotypic profiling, and identification of disease genes. This work is significant in that it demonstrates the feasibility of using semantic web technologies to directly exploit existing biomedical ontologies and Linked Open Data.
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spelling pubmed-45252672015-08-24 Mining Electronic Health Records using Linked Data Odgers, David J. Dumontier, Michel AMIA Jt Summits Transl Sci Proc Articles Meaningful Use guidelines have pushed the United States Healthcare System to adopt electronic health record systems (EHRs) at an unprecedented rate. Hospitals and medical centers are providing access to clinical data via clinical data warehouses such as i2b2, or Stanford’s STRIDE database. In order to realize the potential of using these data for translational research, clinical data warehouses must be interoperable with standardized health terminologies, biomedical ontologies, and growing networks of Linked Open Data such as Bio2RDF. Applying the principles of Linked Data, we transformed a de-identified version of the STRIDE into a semantic clinical data warehouse containing visits, labs, diagnoses, prescriptions, and annotated clinical notes. We demonstrate the utility of this system though basic cohort selection, phenotypic profiling, and identification of disease genes. This work is significant in that it demonstrates the feasibility of using semantic web technologies to directly exploit existing biomedical ontologies and Linked Open Data. American Medical Informatics Association 2015-03-23 /pmc/articles/PMC4525267/ /pubmed/26306276 Text en ©2015 AMIA - All rights reserved. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose
spellingShingle Articles
Odgers, David J.
Dumontier, Michel
Mining Electronic Health Records using Linked Data
title Mining Electronic Health Records using Linked Data
title_full Mining Electronic Health Records using Linked Data
title_fullStr Mining Electronic Health Records using Linked Data
title_full_unstemmed Mining Electronic Health Records using Linked Data
title_short Mining Electronic Health Records using Linked Data
title_sort mining electronic health records using linked data
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4525267/
https://www.ncbi.nlm.nih.gov/pubmed/26306276
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