Problem: A trial includes more than 10 different data collection tools. How do you monitor the data from so many systems to find errors in how the study is being conducted? Solution: REACHER analyzes the data across all different data sources and finds errors immediately.  No need to spend the resources to build a “data…

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Problem: How do you monitor trials in a remote world, when there are no “sites” for all or some of the data? Solution: REACHER analyzes the data for errors, regardless of where the data were entered, or by whom. REACHER is not dependent on traditional trial models. This groundbreaking approach assures sponsors and CROs that…

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Problem: Disrupting the entire clinical trial process is a big concern for most organizations.  How to implement RBQM without making major changes to current processes is a question that challenges most Sponsors and CROs. Solution: REACHER delivers answers directly to study team management or to team members. No changes in workflow are required to enhance…

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Problem: Clinical staff may not be experts in data analytics, and often don’t have tools they need to make an assessment. Monitors wanted a tool that showed them exactly where the error occurred — the subject, the visit, the form, and the item. They were tired of spending hours tracking down non-specific “indicators” that were…

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Problem: For a large oncology trial with extremely complex inclusion/exclusion (I/E) criteria, finding a subject that didn’t meet criteria was very difficult to do manually. There was a high risk of enrolling a subject that did not meet all the I/E criteria. Solution: REACHER performed over 200 checks of data combinations and provided the site…

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Problem: While RBQM approaches such as targeted SDV may find errors, they do not recognize when an error is a systematic problem. If you don’t recognize a systematic error, you don’t find the cause, and the error is perpetuated. Government inspectors ask, “When did you recognize the error as systematic?” Solution: REACHER identifies systematic errors—whether at…

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Problem: RBQM approaches like Key Risk Indicators and Statistical Outliers require that a large number of subjects are enrolled first. False positive (system signals an error but no error exists) results are frequent.  Solution: REACHER finds the errors from the very first subject and tells the monitor exactly what the error is, and how to…

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Problem: A sponsor needed to find errors that affect whether the efficacy endpoint was collected according to the protocol. This included checking the clinical database over time, the audit trail, the training database and the delegation of authority and comparing the results. Solution: REACHER compared the data from all of the different sources and immediately identified…

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Case Studies on REACHER Technology REACHER is theBEST RBQM solution Identify Protocol-Specific Errors that Matter Problem: A sponsor needed to find errors that affect whether the efficacy endpoint was collected according to the protocol. This included checking the clinical database over time, the audit trail, the training database and the delegation of authority and comparing the……

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Resources MANA RBM is committed to sharing knowledge gained over nearly a decade of developing risk-based monitoring and risk-based quality management solutions. In the exclusive Educational Content area, view SOPs, Work Instructions, Templates, and Training Videos for non-commercial use. Resources Risk-Based Monitoring Versus Source Data Verification The Risks of KRI in RBM RBM Barriers to Adoption…

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