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How can RBM success be measured?

rbm infancy

As RBM is its infancy, it is vital to understand how to measure its success, so that we all would have a chance to reflect and correct our path if needed. An interest of adding an RBM technology to clinical trials emerges in pharmaceutical companies gradually. Underlying reasons are global trends like, e.g., regulatory changes (FDA & EMA, ICH), cost pressures, and market expectations: e.g., clinical research has to become leaner and personalized in the future.

Skeptics believe that RBM would rather add complexity and costs. When inquired about their method of monitoring, they explain that they do 100% SDV of all their clinical data and are not intending to reduce the level of monitoring.

Thus, “we have done it always this way” is the most common argument, but it is rather a status quo bias, not an argument. (By the way, RBM does not assume that you reduce SDV, this is one of the most common misunderstandings.)

With RBM you just start to think about risks before it happens. E.g., as it is in the Linda Sullivan‘s example illustrated:

Consider the two families driving across the desert. Does each family’s car provide information about whether a potential risk is becoming an issue? If yes, do they know how to interpret the data and when and how to take action?(…) collecting data on the number of fast-food outlets along the route, or ability to receive satellite radio signals, while interesting, is not meaningful for achieving the goal of making it across the desert without mishap.

So what does RBM practically add to a trial and how can its success be measured? Below you find some simple metrics for tracking your achievements:

  1. Improvements in data quality (reduction in query rates, improvement in confidence intervals of primary and secondary end points)
  2. Reduction of frequency of on-site visits (rate of on-site visits per month/quarter/year)
  3. Protocol deviations (rate of protocol deviations per site per month/quarter/year)
  4. Compliance with AE/SAE reporting requirements (more homogeneous AE/SAE reporting rates among sites)
  5. Less site audit findings
  6. Reduction of number of “lost to follow-ups” patients

Does RBM add complexity? Yes, in the beginning! Preventive trial management demands more thinking in the planning phase as reflective. However, your trial becomes more predictable, more professional, less risky and, as nothing “bad” happens, as a result, less expensive during the execution phase. Track your successes and #BeEfficientByNature!

By | 2016-11-16T18:35:29+00:00 September 22, 2016|Blog|0 Comments

About the Author:

Professional in the integration of data-driven Risk-based Monitoring (RbM) process in international clinical trials of pharmacology. Speaker at regional and global conferences such as: DIA, PharmaForum, PharmaDay, DGGF, etc. 10+ years of experience in data quality projects and biostatistics for the pharmaceutical industry. Life passion: improving clinical research with RbM, driving the RbM research to new frontiers for CROs, pharma and biotech companies.

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