eCOA Systems and Intended Use: Key Considerations

Routinely, clinical trials require investigators to interpret data collected through clinical outcomes assessments (COAs) that may impact decisions in relation to the study participant’s treatment or progress through a trial. For example, COA data can be used to support assessment of patient eligibility or efficacy response to a treatment.

In addition, this interpretation may also first require the investigator to perform additional calculations with the collected data. For example, an investigator may need to calculate overall compliance with completion of COAs during a specific time period, calculate the total score associated with an individual COA, calculate the difference between a total score between the same COA collected at different visits, or calculate a composite score based on a combination of COAs.

The electronic collection of COA data (eCOA) is now widely adopted in clinical trials. The intended use of eCOA is to collect COA data in an electronic format as an alternative to paper. The benefits of such electronic collection have been extensively discussed elsewhere.¹ eCOA systems also offer the potential to automate any calculations that previously needed to be performed manually by the investigator.

The potential for eCOA systems to be classified as a medical device has been discussed extensively elsewhere.² The general intent of most eCOA systems is simply to record response data and transmit that data to a database for storage and eventual analysis.

In general, most software driving eCOAs do not have a medical purpose of their own. Thus, most eCOA systems would not qualify as medical device software.

Even if these eCOA systems do not fall under software-as-a-medical device regulation, it is strongly recommended that when developing eCOA systems that use calculations, the intended use does not replace the clinical decision-making process of the investigator.

• The system should present output calculations objectively and not advise the investigator on the result of those calculations (e.g., inform the investigator of the patient’s study eligibility or make a treatment recommendation).
• The eCOA system must be developed according to a robust software development lifecycle.
• Robust user acceptance testing (UAT) should be performed on the system. This should include a test plan with all scenarios and a set of robust test scripts that adequately test these scenarios.³
• Once the system is live, manual calculations of data inputted by the site and/or patient should be made by the sponsor, independent of the system and compared to system output to confirm accuracy.

Authored on behalf of Critical Path Institute’s eCOA Consortium by Brian Lillis, Director, clinical outcomes technology, ICON; Lisa Charlton, vice president, global product development, Science 37; Jamie Hafner, senior scientist, Clinical ink; Bruce Hellman, co-founder and chief patient officer, uMotif; Jan Malecki, associate director, eCOA, WCG Clinical Endpoint Solutions; and Pierre Mermet-Bouvier, senior manager, eCOA, ICON. 

References

1. Dallabrida, SM. Improving Patient Engagement through eCOA. Applied Clinical Trials. 2017. 26 (2), 28-33. https://www.appliedclinicaltrialsonline.com/view/improving-patient-engagement-through-ecoa
2. eCOA Systems and CE Certification. Critical Path Institute’s Electronic Clinical Outcome Assessment Consortium. 2023. https://c-path.org/wp-content/uploads/2023/03/eCOA-Systems-and-CE-Certification.pdf
3. Gordon, S.; Crager, J.; Howry, C.; et al. Best Practice Recommendations: User Acceptance Testing for Systems Designed to Collect Clinical Outcome Assessment Data Electronically. Ther Innov Regul Sci. 2022.56 (3), 442-453. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8964567/