The value of structured data elements from electronic health records for identifying subjects for primary care clinical trials.
File(s)
Author(s)
Delaney, BC
Mohammed, A
Speedie, S
Type
Journal Article
Abstract
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.
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.
Date Issued
2016-01-11
Date Acceptance
2016-01-05
Citation
BMC Medical Informatics and Decision Making, 2016, 16
ISSN
1472-6947
Publisher
BioMed Central
Journal / Book Title
BMC Medical Informatics and Decision Making
Volume
16
Copyright Statement
© 2016 Ateya et al. Open Access This 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.
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.
License URL
Subjects
Medical Informatics
0806 Information Systems
1103 Clinical Sciences
0909 Geomatic Engineering
Publication Status
Published
Article Number
1