Presentation (CTI)

OBJECTIVES: Electronic Clinical Outcome Assessments (eCOAs) have become an integral component of clinical trials, enabling real-time data collection and reducing recall bias. In particular, electronic diaries (eDiaries)—mobile or web-based tools used by patients to report symptoms or health status—play a critical role by capturing patient-reported outcomes with improved accuracy. However, variability in adherence and reporting can compromise data quality. Regulatory agencies increasingly expect that sponsors implement risk-based approaches—including Key Risk Indicators (KRIs)—to monitor eDiary compliance, ensure data reliability, and detect anomalies. This abstract presents key considerations for developing effective KRIs for eDiaries focusing on metric definitions, detection of data inconsistencies, and integration into data monitoring strategies.
METHODS: Illustrative examples of custom metrics recommendations from ulcerative colitis and insomnia disorder trials have been used to explore the development of KRIs before and after First Patient In (FPI). Analysis has included a review of eDiary structure and content, protocol Schedules of Activities, and alignment between eDiary and device data. A structured process—comprising metric selection, threshold determination, feedback loops with clinical and data teams, and corrective action planning—was applied to define KRIs. We intend to explore protocol-specific customization needs and how KRI findings are used in regulatory submissions. (AI was used to support abstract editing.)
RESULTS: Several considerations have been identified as critical—aligned with regulatory expectations—for developing eCOA-specific KRIs:
• KRIs should be timed based on specific study needs.
• Focus areas include underreporting, missing entries, and mismatches between eDiary and connected device data (e.g.:BGM).
• Actionable KRIs must be tied to corrective workflows.
• Thresholds should proactively flag outliers based on clinical guidance.
CONCLUSIONS: The structured implementation of KRIs enhances eDiary data monitoring by supporting regulatory compliance and early detection of assessment inconsistencies at a patient level, excessive completion time, and data plausibility concerns. This enables greater trial efficiency, timely decision-making, and reliable data quality.