Evaluation of IC errors.

IntroductionLimited financial and human resources and infrastructure can affect the implementation of Good Clinical Practice (GCP), which can have a detrimental impact on data quality and the robustness and application of clinical trial outcomes. Monitoring frameworks are designed to ensure good data quality and help to guide adaptations of trial procedures over time. However, these frameworks tend to be based on datacentric approaches, which often neglect vital aspects of trials, such as social responsibility, capacity strengthening, and contextual influence. Therefore, this study analyses barriers and facilitators of the implementation of GCP in resource-limited settings to inform the establishment of adapted frameworks for trial management and monitoring.MethodsIn this multi-method analysis of the freeBILy trial, conducted in Madagascar from 2019-2022, a random subset of trial participants (n = 500) and informed consents (n = 500) was analyzed for protocol deviations through descriptive statistics and trend analysis. Framework analysis of focus group discussions and individual semi-structures interviews provided a sociological viewpoint of the study context. Findings were subsequently triangulated, merging the viewpoints on the influences towards GCP in resource-limited settings.ResultsA decreasing trend in incorrect database entries was found (z = -6.968, Mann-Kendall Test, p ConclusionThis study shows the limitations of datacentric clinical trial management to assess GCP performances in the frame of clinical trials in resource-limited settings. We highlight the importance of well-trained and integrated study staff, as well as thorough preparation, budgeting and context appropriate monitoring. This achieves high quality, patient centered and compliant research, implemented through alternative frameworks for monitoring and evaluation.