Electronic data capture, or EDC as it is often referred to, is a generic term but in the field of clinical research, it has become synonymous with a category of information systems that are specifically designed to capture and manage data associated with clinical trials and other research projects. The past decade has seen a significant rise in the use of EDC systems across the board for studies of varying phases, types, and complexity. According to a survey conducted by Tufts in 2017 covering nearly 260 sponsor and CRO companies, it was reported that EDC was utilized universally by all the respondents in some capacity. However, over a quarter of sponsors and over a half of CROs also report that they still make use of paper CRFs. In addition, there is surprising variation in the amount and type of data being captured in the EDC system. For example, while nearly 10% of the organizations collected data on genomics for their studies and over 25% collected data on biomarkers, less than 1% of this information was captured in their primary EDC system. Such variations add to the fragmented approach in data collection for research purposes, creating challenges in data analysis, and significantly limiting the availability of meaningful information for collaborative opportunities downstream.

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The advantage of adopting an EDC system for data capture in clinical research are well known. The benefits are numerous and provide a huge return on investment. These include increased accuracy and completeness of data capture, fewer errors and discrepancies, improved compliance, and quicker access to data for review and analysis, among others. Increasingly EDC systems are also incorporating decision support intelligence e.g. assisting with eligibility determination or providing alerts related to DLTs and dose escalations, etc. Why then, with such significant gains to be achieved – why are EDC systems still limited in their depth and breadth of use?

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The answer lies in the experience that organizations have gone through with their prior or current EDC systems, the limitations they may have encountered along the way, and other challenges related to entire process of database setup and management. Some common concerns are:

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1) Cost: While EDC vendors should be able to provide a secure and high-quality solution at an affordable cost, many organizations question whether there is an overall reduction in costs if an EDC system is utilized. This is usually related to the high cost of setup and management of the database that is a byproduct of the way certain EDC systems are architected and delivered.

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2) Trial Duration: Another point that is debated by organizations considering the use of EDC systems is its impact on the overall duration of the trial. While the duration from the time that all data is entered to database lock is reduced due to less time needed for data cleaning, it has also been observed that the time to set up the database often adds to the overall duration.  Another factor adding to the timeline are the delays incurred in adapting the EDC system to incorporate protocol changes, the top reason cited by 45% of survey respondents as a cause for delays in the process.

 

3) Skilled Staff: Besides cost, a challenge that is especially relevant for smaller and mid-sized organizations is the need for skilled staff to manage the EDC system as well as the need to have staff trained to perform data entry and to be proficient in the use of EDC systems in a compliant manner. 

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4) Type of Research: Adoption of EDC systems often varies by the type of clinical research study and whether the team’s perception of benefits outweighs the challenges they will face. One example is in early phase clinical trials where adoption of EDC systems is highly varied and there is still a wide preference for a paper-based approach. Besides factors noted earlier, other factors contributing to the reluctance in adoption in certain study types are trials of shorter duration, those having fewer number of patients, and those with one or few participating sites.

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5) Integration: High on any data entry team’s wish list is the capability to be able to easily pull data into the EDC system from other institutional systems such as the EHR, LIMS etc. The ability to integrate systems not only ensures accuracy of data but significantly cuts down on time in performing data entry and the time for data to be available for subsequent analysis and critical decisions. However more that 75% of EDC system adopters have faced issues loading data into their system either because the system is unable to do so or due to other technical limitations or compatibility issues.

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The above points are completely understandable when examined in their context. They are valid challenges and yet the advantage of capturing clinical research data in an electronic data capture system is undeniable. So what’s the solution? It’s really a question of choosing your EDC system wisely and making sure that in addition to the required functional capabilities of providing a compliant and high quality data capture process, it is designed to allow easy and fast setup as well as be flexible enough to easily incorporate protocol changes as they arise; should require minimal training for data entry; should have multiple options to facilitate data flow through manual processes as well as automated system integrations; and should provide all of this at an affordable cost. There are a variety of EDC systems on the market, but it is important to be able to discern the one that will be the best fit for your research needs and for your organization. Only then can you put the management of the data capture infrastructure to the back of your mind and focus on the actual data captured and its usage in your research activities. Only then can you truly untap the potential of what an EDC system can do for you.