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An OMOP CDM-Based Relational Database of Clinical Research Eligibility Criteria

Eligibility criteria are important for clinical research protocols or clinical practice guidelines for determining who qualify for studies and to whom clinical evidence is applicable, but the free-text format is not amenable for computational processing. In this paper, we described a practical metho...

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Detalles Bibliográficos
Autores principales: Si, Yuqi, Weng, Chunhua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5893219/
https://www.ncbi.nlm.nih.gov/pubmed/29295240
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author Si, Yuqi
Weng, Chunhua
author_facet Si, Yuqi
Weng, Chunhua
author_sort Si, Yuqi
collection PubMed
description Eligibility criteria are important for clinical research protocols or clinical practice guidelines for determining who qualify for studies and to whom clinical evidence is applicable, but the free-text format is not amenable for computational processing. In this paper, we described a practical method for transforming free-text clinical research eligibility criteria of Alzheimer’s clinical trials into a structured relational database compliant with standards for medical terminologies and clinical data models. We utilized a hybrid natural language processing system and a concept normalization tool to extract medical terms in clinical research eligibility criteria and represent them using the OMOP Common Data Model (CDM) v5. We created a database schema design to store syntactic relations to facilitate efficient cohort queries. We further discussed the potential of applying this method to trials on other diseases and the promise of using it to accelerate clinical research with electronic health records.
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spelling pubmed-58932192018-04-10 An OMOP CDM-Based Relational Database of Clinical Research Eligibility Criteria Si, Yuqi Weng, Chunhua Stud Health Technol Inform Article Eligibility criteria are important for clinical research protocols or clinical practice guidelines for determining who qualify for studies and to whom clinical evidence is applicable, but the free-text format is not amenable for computational processing. In this paper, we described a practical method for transforming free-text clinical research eligibility criteria of Alzheimer’s clinical trials into a structured relational database compliant with standards for medical terminologies and clinical data models. We utilized a hybrid natural language processing system and a concept normalization tool to extract medical terms in clinical research eligibility criteria and represent them using the OMOP Common Data Model (CDM) v5. We created a database schema design to store syntactic relations to facilitate efficient cohort queries. We further discussed the potential of applying this method to trials on other diseases and the promise of using it to accelerate clinical research with electronic health records. 2017 /pmc/articles/PMC5893219/ /pubmed/29295240 Text en This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0) (http://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Article
Si, Yuqi
Weng, Chunhua
An OMOP CDM-Based Relational Database of Clinical Research Eligibility Criteria
title An OMOP CDM-Based Relational Database of Clinical Research Eligibility Criteria
title_full An OMOP CDM-Based Relational Database of Clinical Research Eligibility Criteria
title_fullStr An OMOP CDM-Based Relational Database of Clinical Research Eligibility Criteria
title_full_unstemmed An OMOP CDM-Based Relational Database of Clinical Research Eligibility Criteria
title_short An OMOP CDM-Based Relational Database of Clinical Research Eligibility Criteria
title_sort omop cdm-based relational database of clinical research eligibility criteria
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5893219/
https://www.ncbi.nlm.nih.gov/pubmed/29295240
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