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The value of structured data elements from electronic health records for identifying subjects for primary care clinical trials
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 addr...
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Published in: | BMC medical informatics and decision making 2016-01, Vol.16 (1), p.1-1, Article 1 |
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description | 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.
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.
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).
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. |
doi_str_mv | 10.1186/s12911-016-0239-x |
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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.
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).
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.</description><identifier>ISSN: 1472-6947</identifier><identifier>EISSN: 1472-6947</identifier><identifier>DOI: 10.1186/s12911-016-0239-x</identifier><identifier>PMID: 26754574</identifier><language>eng</language><publisher>England: BioMed Central Ltd</publisher><subject>Ambulatory care ; Analysis ; Automation ; Clinical trials ; Clinical Trials as Topic - standards ; Electronic health records ; Electronic Health Records - standards ; Electronic records ; Eligibility Determination - standards ; Health Services Research - standards ; Humans ; Medical practices ; Medical records ; Ontology ; Patient Selection ; Patients ; Primary care ; Primary Health Care ; Semantics ; Standardization</subject><ispartof>BMC medical informatics and decision making, 2016-01, Vol.16 (1), p.1-1, Article 1</ispartof><rights>COPYRIGHT 2016 BioMed Central Ltd.</rights><rights>Copyright BioMed Central 2016</rights><rights>Ateya et al. 2016</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c424t-8da3fad032df479017a3960d26f9592cf7920c90d44f694e63e20c4fed6afbe93</citedby><cites>FETCH-LOGICAL-c424t-8da3fad032df479017a3960d26f9592cf7920c90d44f694e63e20c4fed6afbe93</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4709934/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/1773769985?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25753,27924,27925,37012,37013,44590,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26754574$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Ateya, Mohammad B</creatorcontrib><creatorcontrib>Delaney, Brendan C</creatorcontrib><creatorcontrib>Speedie, Stuart M</creatorcontrib><title>The value of structured data elements from electronic health records for identifying subjects for primary care clinical trials</title><title>BMC medical informatics and decision making</title><addtitle>BMC Med Inform Decis Mak</addtitle><description>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.
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.
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).
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.</description><subject>Ambulatory care</subject><subject>Analysis</subject><subject>Automation</subject><subject>Clinical trials</subject><subject>Clinical Trials as Topic - standards</subject><subject>Electronic health records</subject><subject>Electronic Health Records - standards</subject><subject>Electronic records</subject><subject>Eligibility Determination - standards</subject><subject>Health Services Research - standards</subject><subject>Humans</subject><subject>Medical practices</subject><subject>Medical records</subject><subject>Ontology</subject><subject>Patient Selection</subject><subject>Patients</subject><subject>Primary care</subject><subject>Primary Health Care</subject><subject>Semantics</subject><subject>Standardization</subject><issn>1472-6947</issn><issn>1472-6947</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><recordid>eNptUk1rHSEUHUpD89H-gG6K0E03k_o1Om4KIbRpIZBNshafXt_z4YypzoRkk99eh_eaJiW4uF7vOUePnKb5SPApIb34WghVhLSYiBZTptr7N80R4ZK2QnH59tn-sDkuZYsxkT3r3jWHVMiOd5IfNY_XG0B3Js6AkkdlyrOd5gwOOTMZBBEGGKeCfE7D0tkppzFYtAETpw3KYFN2dZwyCq4ig38I4xqVebWt2N3gNofB5AdkTQZkY6h8E9GUg4nlfXPga4EP-3rS3Pz4fn3-s728uvh1fnbZWk751PbOMG8cZtR5LlX1YZgS2FHhVaeo9VJRbBV2nPvqFwSD2nMPThi_AsVOmm873dt5NYCz9anZRL1_mk4m6JeTMWz0Ot1pLrFSjFeBL3uBnH7PUCY9hGIhRjNCmosmUuC-E5SKCv38H3Sb5jxWexUlmRRK9d0_1NpE0GH0qd5rF1F9xjnpaYfJgjp9BVWXgyHYNIIP9fwFgewINqdSMvgnjwTrJTR6FxpdQ6OX0Oj7yvn0_HOeGH9Twv4AyEK_VQ</recordid><startdate>20160111</startdate><enddate>20160111</enddate><creator>Ateya, Mohammad B</creator><creator>Delaney, Brendan C</creator><creator>Speedie, Stuart M</creator><general>BioMed Central Ltd</general><general>BioMed Central</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QO</scope><scope>7SC</scope><scope>7X7</scope><scope>7XB</scope><scope>88C</scope><scope>88E</scope><scope>8AL</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>K9.</scope><scope>L7M</scope><scope>LK8</scope><scope>L~C</scope><scope>L~D</scope><scope>M0N</scope><scope>M0S</scope><scope>M0T</scope><scope>M1P</scope><scope>M7P</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20160111</creationdate><title>The value of structured data elements from electronic health records for identifying subjects for primary care clinical trials</title><author>Ateya, Mohammad B ; Delaney, Brendan C ; Speedie, Stuart M</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c424t-8da3fad032df479017a3960d26f9592cf7920c90d44f694e63e20c4fed6afbe93</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Ambulatory care</topic><topic>Analysis</topic><topic>Automation</topic><topic>Clinical trials</topic><topic>Clinical Trials as Topic - 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>BMC medical informatics and decision making</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ateya, Mohammad B</au><au>Delaney, Brendan C</au><au>Speedie, Stuart M</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The value of structured data elements from electronic health records for identifying subjects for primary care clinical trials</atitle><jtitle>BMC medical informatics and decision making</jtitle><addtitle>BMC Med Inform Decis Mak</addtitle><date>2016-01-11</date><risdate>2016</risdate><volume>16</volume><issue>1</issue><spage>1</spage><epage>1</epage><pages>1-1</pages><artnum>1</artnum><issn>1472-6947</issn><eissn>1472-6947</eissn><abstract>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.
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.
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).
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.</abstract><cop>England</cop><pub>BioMed Central Ltd</pub><pmid>26754574</pmid><doi>10.1186/s12911-016-0239-x</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Ambulatory care Analysis Automation Clinical trials Clinical Trials as Topic - standards Electronic health records Electronic Health Records - standards Electronic records Eligibility Determination - standards Health Services Research - standards Humans Medical practices Medical records Ontology Patient Selection Patients Primary care Primary Health Care Semantics Standardization |
title | The value of structured data elements from electronic health records for identifying subjects for primary care clinical trials |
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