Paper-Based COA? Nobody Wants This. 

A Note From the Author, Donna M. Mongiello, RN, BSN:  

Innovation is the lifeline of progress. Across the industry, I’m hearing more about the cost pressures that so many clinical trial teams face. With increasing pressure comes tough decisions—decisions that could slow down clinical trial progress.

I recently spoke with a team considering a paper-based clinical outcome assessment (COA) solution for the sake of cost savings. I couldn’t help but question the impact on both data integrity and the patient experience. 

Abandoning technological advancements in favor of outdated methods not only undermines the hard-earned progress we’ve made but also risks compromising the quality of data—essential to critical decision-making.

Paper-based COA, despite its seemingly lower upfront costs, comes with myriads of issues. Hidden expenses and data quality concerns, including the inability to ensure attributability or contemporaneous reporting, and incomplete or illegible entries, not to mention potential transcription errors, inevitably inflate the overall cost and delay the delivery of life-saving treatments. 

Our commitment to patients, sites, and scientific advancement must remain unwavering. We cannot afford to step backward.

Download our latest white paper, where I explore why eCOA is a must for clinical research.

Key Takeaways:

Superior Data Quality — eCOA significantly reduces data entry errors compared to manual methods, ensuring higher accuracy and reliability in clinical trials.

Patient Preference — The majority of clinical trial participants strongly prefer electronic processes over paper-based methods.

Regulatory Alignment — FDA and EMA guidelines actively encourage eCOA adoption, recognizing its role in improving data quality and trial efficiency.

Hidden Cost Savings — BYOD strategies deliver substantial cost savings while eliminating hidden paper-based expenses in data management and storage.

Compliance Excellence — eCOA dramatically improves participant compliance rates compared to paper-based methods, significantly enhancing data reliability.