A risk-based monitoring approach to source data monitoring and documenting monitoring findings.

BACKGROUND: Clinical trial monitoring is evolving from labor-intensive to targeted approaches. The traditional 100% Source Data Monitoring (SDM) approach fails to prioritize data by significance, diverting attention from critical elements. Despite regulatory guidance on Risk-Based Monitoring (RBM), its widespread implementation has been slow. METHODS: Our study teams assess the study's overall risk, document heightened and critical risks, and create a study-specific risk-based monitoring plan, integrating SDM and Central Data Monitoring (CDM). SDM combines a fixed list of pre-identified variables and a list of randomly identified variables to monitor. Identifying variables follows a two-step approach: first, a random sample of participants is selected, second, a random set of variables for each participant selected is identified. Sampling weights prioritize critical variables. Regular team meetings are held to discuss and compile significant findings into a Study Monitoring Report. RESULTS: We present a random SDM sample and a Study Monitoring Report. The random SDM output includes a look-up table for selected database elements. The report provides a holistic view of the study issues and overall health. CONCLUSIONS: The proposed random sampling method is used to monitor a representative set of critical variables, while the Study Monitoring Report is written to summarize significant monitoring findings and data trends. The report allows the sponsor to assess the current status of the study and data effectively. Communicating and sharing emerging insights facilitates timely adjustments of future monitoring activities, optimizing efficiencies, and study outcomes.

Development of a risk assessment and risk management tool for an academic research organization.

BACKGROUND: In the past decade, regulatory agencies have released guidance around risk-based management with the goal of focusing on risks to critical aspects of a research study. Several tools have been developed aimed at implementing these guidelines. We designed a risk management tool to meet the demands of our academic data coordinating center. METHODS: We developed the Risk Assessment and Risk Management (RARM) tool on three fundamental criteria of our risk/quality program: (1) Quality by Design concepts applies to all employees, regardless of the employee's role; (2) the RARM process must be economically feasible and dynamically flexible during the study startup and implementation process; and (3) responsibility of the RARM lay with the entire study team as opposed to a single quality expert. RESULTS: The RARM tool has 20 elements for both risk assessment and risk management. The incorporation of both aspects of risk management allow for a seamless transition from identifying risks to actively monitoring risks throughout enrollment. CONCLUSION: The RARM tool achieves a simplified, seamless approach to risk assessment and risk management. The tool incorporates the concept of Quality by Design into daily work by having every team member contribute to the RARM tool. It also combines the risk assessment and risk management processes into a single tool which allows for a seamless transition from identifying risks to managing the risks throughout the life of the study. The instructions facilitate documentation of de-risking protocols early in development and the tool can be implemented in any platform and organization.