Comparison of electronic data capture (EDC) with the standard data capture method for clinical trial data
Traditionally, clinical research studies rely on collecting data with case report forms, which are subsequently entered into a database to create electronic records. Although well established, this method is time-consuming and error-prone. This study compares four electronic data capture (EDC) metho...
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description | Traditionally, clinical research studies rely on collecting data with case report forms, which are subsequently entered into a database to create electronic records. Although well established, this method is time-consuming and error-prone. This study compares four electronic data capture (EDC) methods with the conventional approach with respect to duration of data capture and accuracy. It was performed in a West African setting, where clinical trials involve data collection from urban, rural and often remote locations.
Three types of commonly available EDC tools were assessed in face-to-face interviews; netbook, PDA, and tablet PC. EDC performance during telephone interviews via mobile phone was evaluated as a fourth method. The Graeco Latin square study design allowed comparison of all four methods to standard paper-based recording followed by data double entry while controlling simultaneously for possible confounding factors such as interview order, interviewer and interviewee. Over a study period of three weeks the error rates decreased considerably for all EDC methods. In the last week of the study the data accuracy for the netbook (5.1%, CI95%: 3.5-7.2%) and the tablet PC (5.2%, CI95%: 3.7-7.4%) was not significantly different from the accuracy of the conventional paper-based method (3.6%, CI95%: 2.2-5.5%), but error rates for the PDA (7.9%, CI95%: 6.0-10.5%) and telephone (6.3%, CI95% 4.6-8.6%) remained significantly higher. While EDC-interviews take slightly longer, data become readily available after download, making EDC more time effective. Free text and date fields were associated with higher error rates than numerical, single select and skip fields.
EDC solutions have the potential to produce similar data accuracy compared to paper-based methods. Given the considerable reduction in the time from data collection to database lock, EDC holds the promise to reduce research-associated costs. However, the successful implementation of EDC requires adjustment of work processes and reallocation of resources. |
doi_str_mv | 10.1371/journal.pone.0025348 |
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Three types of commonly available EDC tools were assessed in face-to-face interviews; netbook, PDA, and tablet PC. EDC performance during telephone interviews via mobile phone was evaluated as a fourth method. The Graeco Latin square study design allowed comparison of all four methods to standard paper-based recording followed by data double entry while controlling simultaneously for possible confounding factors such as interview order, interviewer and interviewee. Over a study period of three weeks the error rates decreased considerably for all EDC methods. In the last week of the study the data accuracy for the netbook (5.1%, CI95%: 3.5-7.2%) and the tablet PC (5.2%, CI95%: 3.7-7.4%) was not significantly different from the accuracy of the conventional paper-based method (3.6%, CI95%: 2.2-5.5%), but error rates for the PDA (7.9%, CI95%: 6.0-10.5%) and telephone (6.3%, CI95% 4.6-8.6%) remained significantly higher. While EDC-interviews take slightly longer, data become readily available after download, making EDC more time effective. Free text and date fields were associated with higher error rates than numerical, single select and skip fields.
EDC solutions have the potential to produce similar data accuracy compared to paper-based methods. Given the considerable reduction in the time from data collection to database lock, EDC holds the promise to reduce research-associated costs. However, the successful implementation of EDC requires adjustment of work processes and reallocation of resources.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0025348</identifier><identifier>PMID: 21966505</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Accuracy ; Automatic Data Processing ; Biology ; Cellular telephones ; Clinical trials ; Clinical Trials as Topic ; Computer Science ; Computers ; Councils ; Data capture ; Data collection ; Data Collection - methods ; Data entry ; Design ; Design standards ; Downloading ; Electronic records ; Error analysis ; Global positioning systems ; GPS ; Households ; Humans ; Interviews ; Mathematics ; Medical research ; Medicine ; Methods ; Portable computers ; Product development ; Social and Behavioral Sciences ; Standard data ; Tablet computers ; Wireless telephones</subject><ispartof>PloS one, 2011-09, Vol.6 (9), p.e25348-e25348</ispartof><rights>COPYRIGHT 2011 Public Library of Science</rights><rights>2011 Walther et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>Walther et al. 2011</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c592t-860c6aa8ebeac97a09134a04cc2f71fa0c41f1c4b45afdec46278d8836c6dbfd3</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3179496/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3179496/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79342,79343</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/21966505$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Walther, Brigitte</creatorcontrib><creatorcontrib>Hossin, Safayet</creatorcontrib><creatorcontrib>Townend, John</creatorcontrib><creatorcontrib>Abernethy, Neil</creatorcontrib><creatorcontrib>Parker, David</creatorcontrib><creatorcontrib>Jeffries, David</creatorcontrib><title>Comparison of electronic data capture (EDC) with the standard data capture method for clinical trial data</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Traditionally, clinical research studies rely on collecting data with case report forms, which are subsequently entered into a database to create electronic records. Although well established, this method is time-consuming and error-prone. This study compares four electronic data capture (EDC) methods with the conventional approach with respect to duration of data capture and accuracy. It was performed in a West African setting, where clinical trials involve data collection from urban, rural and often remote locations.
Three types of commonly available EDC tools were assessed in face-to-face interviews; netbook, PDA, and tablet PC. EDC performance during telephone interviews via mobile phone was evaluated as a fourth method. The Graeco Latin square study design allowed comparison of all four methods to standard paper-based recording followed by data double entry while controlling simultaneously for possible confounding factors such as interview order, interviewer and interviewee. Over a study period of three weeks the error rates decreased considerably for all EDC methods. In the last week of the study the data accuracy for the netbook (5.1%, CI95%: 3.5-7.2%) and the tablet PC (5.2%, CI95%: 3.7-7.4%) was not significantly different from the accuracy of the conventional paper-based method (3.6%, CI95%: 2.2-5.5%), but error rates for the PDA (7.9%, CI95%: 6.0-10.5%) and telephone (6.3%, CI95% 4.6-8.6%) remained significantly higher. While EDC-interviews take slightly longer, data become readily available after download, making EDC more time effective. Free text and date fields were associated with higher error rates than numerical, single select and skip fields.
EDC solutions have the potential to produce similar data accuracy compared to paper-based methods. Given the considerable reduction in the time from data collection to database lock, EDC holds the promise to reduce research-associated costs. However, the successful implementation of EDC requires adjustment of work processes and reallocation of resources.</description><subject>Accuracy</subject><subject>Automatic Data Processing</subject><subject>Biology</subject><subject>Cellular telephones</subject><subject>Clinical trials</subject><subject>Clinical Trials as Topic</subject><subject>Computer Science</subject><subject>Computers</subject><subject>Councils</subject><subject>Data capture</subject><subject>Data collection</subject><subject>Data Collection - methods</subject><subject>Data entry</subject><subject>Design</subject><subject>Design standards</subject><subject>Downloading</subject><subject>Electronic records</subject><subject>Error analysis</subject><subject>Global positioning systems</subject><subject>GPS</subject><subject>Households</subject><subject>Humans</subject><subject>Interviews</subject><subject>Mathematics</subject><subject>Medical research</subject><subject>Medicine</subject><subject>Methods</subject><subject>Portable computers</subject><subject>Product development</subject><subject>Social and Behavioral Sciences</subject><subject>Standard data</subject><subject>Tablet computers</subject><subject>Wireless telephones</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><sourceid>DOA</sourceid><recordid>eNptkl1rFDEUhgdRbK3-A9GAF-rFrsnkc26EslYtFLzR63AmH7tZZiZrklX892bdaelKCSQhec57ck7epnlJ8JJQST5s4z5NMCx3cXJLjFtOmXrUnJOOtgvRYvr43v6seZbzFmNOlRBPm7OWdEJwzM-bsIrjDlLIcULRIzc4U1KcgkEWCiADu7JPDr27-rR6j36HskFl41AuMFlI9hQaXdlEi3xMyAyhasCASgp1PmDPmycehuxezOtF8-Pz1ffV18XNty_Xq8ubheFdWxZKYCMAlOsdmE4C7ghlgJkxrZfEAzaMeGJYzzh46wwTrVRWKSqMsL239KJ5fdTdDTHruUtZE4qVkpxjXInrI2EjbPUuhRHSHx0h6H8HMa01pBLM4DT1PWc1HaWcM4xZ3yrhCZNAOimdYlXr45xt34_OGjeVBMOJ6OnNFDZ6HX9pSmTHOlEF3s4CKf7cu1z0GLJxwwCTi_usVSfa9vBtlXzzH_lwcTO1hvr-MPlY05qDpr5kUigpO0IqtXyAqsO6MZjqKB_q-UkAOwaYFHNOzt-VSLA--PH2MfrgRz37sYa9ut-eu6BbA9K_mlzdPw</recordid><startdate>20110923</startdate><enddate>20110923</enddate><creator>Walther, Brigitte</creator><creator>Hossin, Safayet</creator><creator>Townend, John</creator><creator>Abernethy, Neil</creator><creator>Parker, David</creator><creator>Jeffries, David</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</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>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20110923</creationdate><title>Comparison of electronic data capture (EDC) with the standard data capture method for clinical trial data</title><author>Walther, Brigitte ; Hossin, Safayet ; Townend, John ; Abernethy, Neil ; Parker, David ; Jeffries, David</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c592t-860c6aa8ebeac97a09134a04cc2f71fa0c41f1c4b45afdec46278d8836c6dbfd3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Accuracy</topic><topic>Automatic Data Processing</topic><topic>Biology</topic><topic>Cellular telephones</topic><topic>Clinical trials</topic><topic>Clinical Trials as Topic</topic><topic>Computer Science</topic><topic>Computers</topic><topic>Councils</topic><topic>Data capture</topic><topic>Data collection</topic><topic>Data Collection - 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Walther, Brigitte</au><au>Hossin, Safayet</au><au>Townend, John</au><au>Abernethy, Neil</au><au>Parker, David</au><au>Jeffries, David</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Comparison of electronic data capture (EDC) with the standard data capture method for clinical trial data</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2011-09-23</date><risdate>2011</risdate><volume>6</volume><issue>9</issue><spage>e25348</spage><epage>e25348</epage><pages>e25348-e25348</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Traditionally, clinical research studies rely on collecting data with case report forms, which are subsequently entered into a database to create electronic records. Although well established, this method is time-consuming and error-prone. This study compares four electronic data capture (EDC) methods with the conventional approach with respect to duration of data capture and accuracy. It was performed in a West African setting, where clinical trials involve data collection from urban, rural and often remote locations.
Three types of commonly available EDC tools were assessed in face-to-face interviews; netbook, PDA, and tablet PC. EDC performance during telephone interviews via mobile phone was evaluated as a fourth method. The Graeco Latin square study design allowed comparison of all four methods to standard paper-based recording followed by data double entry while controlling simultaneously for possible confounding factors such as interview order, interviewer and interviewee. Over a study period of three weeks the error rates decreased considerably for all EDC methods. In the last week of the study the data accuracy for the netbook (5.1%, CI95%: 3.5-7.2%) and the tablet PC (5.2%, CI95%: 3.7-7.4%) was not significantly different from the accuracy of the conventional paper-based method (3.6%, CI95%: 2.2-5.5%), but error rates for the PDA (7.9%, CI95%: 6.0-10.5%) and telephone (6.3%, CI95% 4.6-8.6%) remained significantly higher. While EDC-interviews take slightly longer, data become readily available after download, making EDC more time effective. Free text and date fields were associated with higher error rates than numerical, single select and skip fields.
EDC solutions have the potential to produce similar data accuracy compared to paper-based methods. Given the considerable reduction in the time from data collection to database lock, EDC holds the promise to reduce research-associated costs. However, the successful implementation of EDC requires adjustment of work processes and reallocation of resources.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>21966505</pmid><doi>10.1371/journal.pone.0025348</doi><oa>free_for_read</oa></addata></record> |
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subjects | Accuracy Automatic Data Processing Biology Cellular telephones Clinical trials Clinical Trials as Topic Computer Science Computers Councils Data capture Data collection Data Collection - methods Data entry Design Design standards Downloading Electronic records Error analysis Global positioning systems GPS Households Humans Interviews Mathematics Medical research Medicine Methods Portable computers Product development Social and Behavioral Sciences Standard data Tablet computers Wireless telephones |
title | Comparison of electronic data capture (EDC) with the standard data capture method for clinical trial data |
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