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The value of structured data elements from electronic health records for identifying subjects for primary care clinical trials

BACKGROUND: An increasing number of clinical trials are conducted in primary care settings. Making better use of existing data in the electronic health records to identify eligible subjects can improve efficiency of such studies. Our study aims to quantify the proportion of eligibility criteria that...

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Autores principales: Ateya, Mohammad B., Delaney, Brendan C., Speedie, Stuart M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4709934/
https://www.ncbi.nlm.nih.gov/pubmed/26754574
http://dx.doi.org/10.1186/s12911-016-0239-x
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author Ateya, Mohammad B.
Delaney, Brendan C.
Speedie, Stuart M.
author_facet Ateya, Mohammad B.
Delaney, Brendan C.
Speedie, Stuart M.
author_sort Ateya, Mohammad B.
collection PubMed
description BACKGROUND: An increasing number of clinical trials are conducted in primary care settings. Making better use of existing data in the electronic health records to identify eligible subjects can improve efficiency of such studies. Our study aims to quantify the proportion of eligibility criteria that can be addressed with data in electronic health records and to compare the content of eligibility criteria in primary care with previous work. METHODS: Eligibility criteria were extracted from primary care studies downloaded from the UK Clinical Research Network Study Portfolio. Criteria were broken into elemental statements. Two expert independent raters classified each statement based on whether or not structured data items in the electronic health record can be used to determine if the statement was true for a specific patient. Disagreements in classification were discussed until 100 % agreement was reached. Statements were also classified based on content and the percentages of each category were compared to two similar studies reported in the literature. RESULTS: Eligibility criteria were retrieved from 228 studies and decomposed into 2619 criteria elemental statements. 74 % of the criteria elemental statements were considered likely associated with structured data in an electronic health record. 79 % of the studies had at least 60 % of their criteria statements addressable with structured data likely to be present in an electronic health record. Based on clinical content, most frequent categories were: “disease, symptom, and sign”, “therapy or surgery”, and “medication” (36 %, 13 %, and 10 % of total criteria statements respectively). We also identified new criteria categories related to provider and caregiver attributes (2.6 % and 1 % of total criteria statements respectively). CONCLUSIONS: Electronic health records readily contain much of the data needed to assess patients’ eligibility for clinical trials enrollment. Eligibility criteria content categories identified by our study can be incorporated as data elements in electronic health records to facilitate their integration with clinical trial management systems.
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spelling pubmed-47099342016-01-13 The value of structured data elements from electronic health records for identifying subjects for primary care clinical trials Ateya, Mohammad B. Delaney, Brendan C. Speedie, Stuart M. BMC Med Inform Decis Mak Research Article BACKGROUND: An increasing number of clinical trials are conducted in primary care settings. Making better use of existing data in the electronic health records to identify eligible subjects can improve efficiency of such studies. Our study aims to quantify the proportion of eligibility criteria that can be addressed with data in electronic health records and to compare the content of eligibility criteria in primary care with previous work. METHODS: Eligibility criteria were extracted from primary care studies downloaded from the UK Clinical Research Network Study Portfolio. Criteria were broken into elemental statements. Two expert independent raters classified each statement based on whether or not structured data items in the electronic health record can be used to determine if the statement was true for a specific patient. Disagreements in classification were discussed until 100 % agreement was reached. Statements were also classified based on content and the percentages of each category were compared to two similar studies reported in the literature. RESULTS: Eligibility criteria were retrieved from 228 studies and decomposed into 2619 criteria elemental statements. 74 % of the criteria elemental statements were considered likely associated with structured data in an electronic health record. 79 % of the studies had at least 60 % of their criteria statements addressable with structured data likely to be present in an electronic health record. Based on clinical content, most frequent categories were: “disease, symptom, and sign”, “therapy or surgery”, and “medication” (36 %, 13 %, and 10 % of total criteria statements respectively). We also identified new criteria categories related to provider and caregiver attributes (2.6 % and 1 % of total criteria statements respectively). CONCLUSIONS: Electronic health records readily contain much of the data needed to assess patients’ eligibility for clinical trials enrollment. Eligibility criteria content categories identified by our study can be incorporated as data elements in electronic health records to facilitate their integration with clinical trial management systems. BioMed Central 2016-01-11 /pmc/articles/PMC4709934/ /pubmed/26754574 http://dx.doi.org/10.1186/s12911-016-0239-x Text en © Ateya et al. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Ateya, Mohammad B.
Delaney, Brendan C.
Speedie, Stuart M.
The value of structured data elements from electronic health records for identifying subjects for primary care clinical trials
title The value of structured data elements from electronic health records for identifying subjects for primary care clinical trials
title_full The value of structured data elements from electronic health records for identifying subjects for primary care clinical trials
title_fullStr The value of structured data elements from electronic health records for identifying subjects for primary care clinical trials
title_full_unstemmed The value of structured data elements from electronic health records for identifying subjects for primary care clinical trials
title_short The value of structured data elements from electronic health records for identifying subjects for primary care clinical trials
title_sort value of structured data elements from electronic health records for identifying subjects for primary care clinical trials
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4709934/
https://www.ncbi.nlm.nih.gov/pubmed/26754574
http://dx.doi.org/10.1186/s12911-016-0239-x
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