There are more than 270,000 clinical studies underway in all 50 states of the U.S. and in 203 countries, according to the U.S. National Library of Medicine (ClinicalTrials.gov).
Given the sheer volume of data and design complexity that often accompany clinical trial data capture, misconceptions frequently surround the processes and personnel required for study building. Let’s explore three common myths surrounding EDC study building.
Building EDC databases requires an advanced team of experienced EDC study builders.
It is a misconception that building EDC studies requires staff expansion to include highly skilled clinical developers.
The Reality: EDC studies should not be too challenging for an organization to adopt. The focus should be on the proper evaluation of the business needs to determine the appropriate resources required to manage the work.
Evaluation of business needs as the primary focus may reveal that data managers are equipped to handle the study build and there is no need for clinical developers.
For example, CROs specializing in Phase I research may only require EDC study designs with low complexity and minimal — or even no — data integration. A team of technical data managers may be sufficient to handle these study build activities. Using template studies and standards, the process can be streamlined to rapidly build studies with a fairly small team of individuals.
A large CRO already managing a wide range of studies is likely to have an existing team of adequately skilled individuals in place to manage study builds within a new system. The evaluation of business needs in this case should consist of retraining needed to prepare these individuals to work with several EDC solutions.
Bottom line: Focus on business needs will provide proper business evaluation and skill analysis to clearly understand the makeup and size of the team that will be required.
Training is enough.
Training alone is not always adequate to begin activities within a new system.
The Reality: Granted, there’s a large resource pool of qualified EDC-experienced individuals in the industry with strong CDM and clinical programming skills, and those teams can certainly be taught the skills required to work with a new solution. But, a startup approach that is based only on training misses critical components of adoption and change management. This approach bypasses other important factors, including learning and understanding of best practices, and the applicability of functionality the new solution may offer. Organizations must also focus on proficiency of these newly learned skills to take full advantage of a system’s capabilities.
Bottom line: Training is necessary, but it is only part of a complete system adoption process.
Technology solves everything.
Choosing better technology equates to successful adoption is a misconception.
The Reality: Going into a large technology adoption with this mindset is risky. Adoption of new technologies entails a comprehensive change-management process that includes multiple layers of activity. Your organization’s appetite and attitude for change will ultimately determine the level of success that will be achieved.
Organizations moving through a technology adoption should have well-developed plans in place that cover all aspects of the process, including vendor selection, organizational impact, training, proficiency and process improvement.
Bottom line: Choosing a great solution is important, but the solution alone will not dictate success. Choosing a solution partner who understands your needs and will assist your team through the adoption process is key.
Learn more about OmniComm’s Professional Services team and EDC CARE™ Qualification, our comprehensive software qualification program that goes beyond the classroom to help ensure your organization has the expertise and resources necessary for a successful EDC implementation.
About the Author
John Fontenault, chief operating officer, brings more than 25 years of pharma industry experience to his role at OmniComm Systems. He was vice president, Operations at ER Squared, providing strategic eClinical business process and change management/adoption services. Prior to ER Squared, he was executive director and global head of Clinical Data Management and Technology at Kendle International (INC Research). Previously, he held positions of increasing responsibility at Bayer Healthcare and Purdue Pharma.