Comparison of Electronic Data Capture (EDC) with the Standard Data Capture Method for Clinical Trial Data

Background 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. Methodology/Principal Findings 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. Conclusions 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.

[1]  Mark Tomlinson,et al.  The use of mobile phones as a data collection tool: A report from a household survey in South Africa , 2009, BMC Medical Informatics Decis. Mak..

[2]  Christopher J. Seebregts,et al.  Handheld computers for survey and trial data collection in resource-poor settings: Development and evaluation of PDACT, a PalmTM Pilot interviewing system , 2009, Int. J. Medical Informatics.

[3]  T. Salthouse Effects of age and skill in typing. , 1984, Journal of experimental psychology. General.

[4]  Pascal Meunier,et al.  ActiveSync, TCP/IP and 802.11b wireless vulnerabilities of WinCE-based PDAs , 2002, Proceedings. Eleventh IEEE International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises.

[5]  Shannon J. Lane,et al.  Bmc Medical Informatics and Decision Making a Review of Randomized Controlled Trials Comparing the Effectiveness of Hand Held Computers with Paper Methods for Data Collection , 2006 .

[6]  Ben Shneiderman,et al.  Investigating touchscreen typing: the effect of keyboard size on typing speed , 1993, Behav. Inf. Technol..

[7]  S. Becker THE HEALTH INSURANCE PORTABILITY AND ACCOUNTABILITY ACT , 2004 .

[8]  James F. Brinkley,et al.  A partnership approach for Electronic Data Capture in small-scale clinical trials , 2011, J. Biomed. Informatics.

[9]  H Emslie,et al.  Text entry on handheld computers by older users , 2000, Ergonomics.

[10]  Eric Harslem,et al.  Designing the STAR User Interface , 1987, ECICS.

[11]  E. A. Bosman Age-related differences in the motoric aspects of transcription typing skill. , 1993, Psychology and aging.

[12]  A. Blanc Demographic and health surveys , 1991 .

[13]  K. El Emam,et al.  Who’s Using PDAs? Estimates of PDA Use by Health Care Providers: A Systematic Review of Surveys , 2006, Journal of medical Internet research.

[14]  Dianne J Terlouw,et al.  Use of handheld computers with global positioning systems for probability sampling and data entry in household surveys. , 2007, The American journal of tropical medicine and hygiene.

[15]  Amy P Abernethy,et al.  Handheld computers for data entry: high tech has its problems too , 2007, Trials.