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Electronic Data Capture (edc) Improves Data Quality In Clinical Studies

Electronic data capture (EDC) software is a web-based system designed to collect clinical trial data in electronic format. It runs solely on a web server and the only tool required to access and operate it is a regular web browser (with no plug-ins) with internet connection. Check out the video below to learn more about electronic data capture software:

EDC is used in place of the conventional paper-based data collection method in an attempt to speed up the entire process. The data may be captured either electronically at the source, or in paper format which is then transcribed to the EDC system. These eClinical solutions are largely adopted by clinical research organizations and pharmaceutical companies.

EDC systems typically provide:

- a tool for reporting data analysis

- a validation tool to verify user data

- a graphic user interface for data entry

Users of Clinical Data Solutions

There are 3 main classes of EDC software users: sponsors, CROs, and sites.

- Sponsor: The sponsor is the organization or group that owns the clinical trial being initiated. Life science companies must sponsor a clinical trial as this is necessary in order to have their medical advances approved by the regulatory authority and sold on the market.

- CRO: A contract research organization (CRO) is the entity that plans and conducts the clinical trial, as commissioned by the sponsor. The CRO may effectively manage the trial on the sponsors behalf or handle only some of the major roles (analysis, monitoring, data management, etc.). In the academic world, CROs are referred to as AROs or Academic Research Organizations.

- Site: A site is the entity that organizes and collects data from the subjects of the clinical trial; it is often a clinic or hospital. The site employs study coordinators (usually nurses) and gives them tasks, such as entering clinical data into the electronic data capture system. The physician responsible for the patients care and dataoften called the sites investigatorreviews and electronically signs the data.

In addition to these types of EDC users, the patients involved in the study may also contribute some data to the system, either via another application and/or device that conveys data to the EDC software, or through a specified component in the software. This practice is known as electronic patient-reported outcomes or ePRO.

Advantages of EDC for Clinical Data Management

The majority of recent clinical trials use the EDC system. This type of clinical trial management software improves data accuracy and expedites data collection for studies of medical devices and pharmaceutical drugs. Other advantages of EDC include:

- Cleaner Data: The EDC system is particularly useful at administering key aspects of clinical data quality. The software has built-in programs that ensure all data meets the requirements (ranges, formats, etc.) before transferring the data to the database.

- More Efficient Procedures: EDC software can lead the site through a sequence of study events, asking only for specific data required for the patients situation at a certain time. It simplifies data rectification using tools that can identify and resolve data issues involving sites.

- Faster Data Access: Since they are web-based, EDC systems are able to provide virtually real-time access to clinical data during a clinical trial. This allows for faster decision-making and trial design adjustments.

History of EDC

Electronic data capture is often linked to another type of software that came out in the early 90s, called Remote Data Entry (RDE). However, the origins of EDC actually started in the mid-70s with a CRO named Institute for Biological Research and Development (IBRD).

The officials of the said institute signed with Abbott Pharmaceuticals in order to have a computer that can directly enter clinical data for each of their network of clinical investigators. IBRD later cleaned the collected data and submitted reports to Abbott.

Clinical research data, or the patients data collected in a study of a new medical device or drug, is collected by study coordinators, nurse and physicians in medical sites (universities, hospitals or offices) across the globe.

Historically, such information was gathered in paper form which was then submitted to the sponsor for data entry and statistical analysis. In an effort to improve several aspects of data collection, including speed and accuracy, EDC was developed and is continuously being upgraded.

Conclusion

As EDC systems continue to progress, vendors are starting to include capabilities that would have been developed and marketed as separate clinical trial software solutions: clinical trial management system (CTMS), clinical data management system (CDMS), and business intelligence, among others.

Further, there are efforts being made to incorporate payment execution into the EDC data systema convergence that is expected to persist until electronic medical accounts will become more prevalent within the wider healthcare ecosystem.

References

Anaïs Le Jeannic,1 Céline Quelen,1 Corinne Alberti, corresponding author2,3 and Isabelle Durand-Zaleski1,4, on behalf of the CompaRec Investigators. Comparison of two data collection processes in clinical studies: electronic and paper case report forms. BMC Med Res Methodol. 2014; 14: 7. Published online 2014 Jan 17. doi: 10.1186/1471-2288-14-7.

El Emam K, Jonker E, Sampson M, Krlea-Jeric K, Neisa A. The Use of Electronic Data Capture Tools in Clinical Trials: Web-Survey of 259

Canadian Trials. J Med Internet Res 2009;11(1):e8. DOI: 10.2196/jmir.1120. PMID: 19275984. PMCID: PMC2762772.

Laird-Maddox, Marsha; Mitchell, Susan B; Hoffman, Mark. "Integrating Research Data Capture into the Electronic Health Record

Workflow: Real-World Experience to Advance Innovation" Perspectives in Health Information Management (Fall, October 2014).

Meredith L. Nahm,1,* Carl F. Pieper,2 and Maureen M. Cunningham3. Roberta W. Scherer, Editor. Quantifying Data Quality for Clinical Trials Using Electronic Data Capture. PLoS ONE. 2008; 3(8): e3049. Published online 2008 Aug 25. doi: 10.1371/journal.pone.0003049. PMCID: PMC2516178.

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