Time-consuming and Expensive Data Quality Monitoring Procedures Persist in Clinical Trials: A National Survey.

Introduction: The Good Clinical Practice guideline identifies that data monitoring is an essential research activity. However, limited evidence exists on how to perform monitoring including the amount or frequency that is needed to ensure data quality. This study aims to explore the monitoring procedures that are implemented to ensure data quality in Australian clinical research studies.& nbsp; Material and methods: Clinical studies listed on the Australian and New Zealand Clinical Trials Registry were invited to participate in a national cross-sectional, mixed-mode, multi-contact (postal letter and e-mail) webbased survey. Information was gathered about the types of data quality monitoring procedures being implemented.& nbsp; Results: Of the 3689 clinical studies contacted, 589 (16.0%) responded, of which 441 (77.4%) completed the survey. Over half (55%) of the studies applied source data verification (SDV) compared to risk-based targeted and triggered monitoring (10?11%). Conducting 100% on-site monitoring was most common for those who implemented the traditional approach. Respondents who did not conduct 100% monitoring, included 1?25% of data points for SDV, centralized or on-site monitoring. The incidence of adverse events and protocol deviations were the most likely factors to trigger a site visit for risk-based triggered (63% and 44%) and centralized monitoring (48% and 44%), respectively.& nbsp; Conclusion: Instead of using more optimal risk-based approaches, small single-site clinical studies are conducting traditional monitoring procedures which are time consuming and expensive. Formal guidelines need to be improved and provided to all researchers for ?new? risk-based monitoring approaches.