Adaptive Monitoring: Anticipating The Human Factor

Adapt to More than Just Numbers Before the Study Even Begins

In my first two blogs on Adaptive Monitoring (AM) I spoke about how Risk-based Monitoring (RBM) integrates the AM process and risk can be minimized by a tailored monitoring approach. I’d like to continue with how Adaptive Monitoring may be triggered by many other aspects than merely numeric data related issues.     

As illustrated previously, adaptation of the monitoring plan based on mainly numeric data is rather simple and straight forward. Most of today’s RBM applications are predominantly centered around the management of this type of data or are limited to processing numeric data only. These applications typically highlight outliers, display unusual trends and provide graphs with abnormal patterns. While this approach is already moving the risk management process into the right direction, numeric data alone are not truly covering all aspects of Risk-based Monitoring and Adaptive Monitoring.

Let me explain by giving you some real-life use cases:

In some cases, the AM process commences even before any data has been generated. It is not unlikely that a new site, that just became active in the clinical drug development, would require more than just one site initiation visit. The site monitor would have to spend more time with the staff at such a site prior to the first patient being enrolled to ensure; e.g. the right patients get enrolled, any serious adverse events are being reported within the agreed time frames and the staff fully understands the functionality of the EDC system. Time well invested if this effort results in a need for less on-site monitoring visits later in the trial. This scenario should therefore be part of the Risk-based Monitoring plan.

A second resource related risk could be observed in sites where there is a change of personnel during a well running study. Here we are running into the issue of knowledge transfer between the well-trained staff and the newcomers. If the on-site monitor gets to know about such a change to happen, the previously “relaxed” visit pattern will have to be adjusted to a more frequent and intensive one bringing the new staff to the required level of performance.

As a third example, let us look at an acute study with a long term follow up part. In such a type of study, the site staff usually struggles with the documentation of the data required for the transition period from the acute to the chronic follow-up part. Particularly when the acute part of a study must be completed for statistical analysis. It may be worthwhile to have an on-site monitor around when the first two patients move from one part of the study into the following part. Also, here the monitoring frequency will have to be adjusted.

A fit-for-purpose RBM application doesn’t only manage the “numbers”.

What do these use cases illustrate and how do they contribute to conducting sound Risk-based Monitoring? A fit-for-purpose RBM application doesn’t only manage the ‘numbers’, but also accommodates for integrated Adaptive Monitoring features that can deal with for example human factors such as the ones mentioned earlier. The process for those type of risks must follow the same rules and workflow to avoid “afterthoughts” that lead to an additional burden to the monitor. If that can be achieved, then the Adaptive Monitoring process will turn out to be a smooth and straight forward process.

Read also:

If you are interested in getting access to the Adaptive Monitoring process charts, then subscribe to our newsletter “Real RBM for All”. In the coming weeks I will guide you through the process of Adaptive Monitoring by providing you the complete process overview step by step. So stay tuned…

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By |2018-03-21T19:31:12+00:00March 21, 2018|Blog, Case Study|Comments Off on Adaptive Monitoring: Anticipating The Human Factor
Dr Johann Proeve, our Chief Scientific Officer, has over thirty five years of experience working across the Pharma CRO industry, being the former Head of Global Data Management at Bayer AG.

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