Focus on critical data and processes by documenting risks, roles, and mitigation strategies.

With the Risk Assessment and Categorization Tool (RACT), you can capture components of a holistic Integrated Quality Risk Management Plan (IQRMP) through centralized documentation of the RACT, key risk indicators, source data review, and source data verification strategies. You don’t need risk assessment spreadsheets that are hard to track and manage. Because RACT is built on the Medidata Rave Clinical Cloud platform, it enables reuse of RACT information any time you need it, streamlining cross-functional collaboration and deployment of RBM strategies.

Identify and analyze known and unknown risks, anomalies, outliers, and patterns using machine learning.

Medidata Detect applies sophisticated machine-learning algorithms to analyze the clinical data in a trial for outliers, data anomalies, and trends. It quickly and accurately identifies risk areas, providing immediate insight into clinical trial performance and data quality. 

Optimize ROI with a site monitoring approach that allows you to redeploy resources to risk or problem areas.

The Medidata Rave Clinical Cloud platform enables Rave CTMS and Rave RBQM to share data elements with each other, facilitating a site monitoring approach that leverages resources efficiently by focusing on sites that have higher workload or monitoring needs. The reduction in redundant data entry saves a tremendous amount of time, both on-site and remotely. This unified functionality results in higher efficiency, increased productivity, and improved risk monitoring

Improve your risk mitigation strategy and resolve issues faster.

With centralized, cross-functional issue management powered by the Medidata Rave Clinical Cloud platform, CRAs can optimize workload efficiencies by documenting issues appropriately and taking timely actions to ensure maximum collaboration across the clinical team.

Refocus CRA priorities with reduced source document verification.

With Rave TSDV, sponsors and CROs can focus on reducing SDV without sacrificing regulatory compliance or data quality strategies. Patients are assigned to pre-configured SDV regimens — focused on critical data — as they are enrolled, enabling study teams to achieve desired coverage levels.