“The right tool for the right job” is a saying that applies in many situations across many industries. When it comes to clinical protocol training, research sites and sponsors need to determine what their ultimate goals are to correctly identify the best training tools for the job.
When it comes to training, those goals will revolve around the competency of the staff being trained and can be placed into three broad categories:
- Ticking a box to meet minimum standards under applicable regulations;
- Ensuring staff’s ability to regurgitate information from the training in the short term; and
- Affecting staff’s long-term decision-making behavior.
In the first instance, a read-and-sign procedure, wherein employees are given some form of written instruction to review and a form to sign stating that they have read and understood it, might be the most appropriate training tool. Simple presentation of written information, such as an SOP or slide deck, may be sufficient in cases where the training covers well-known procedures for experienced staff; in such cases, the training may simply be mandated to meet regulatory requirements.
For the second, however, this would be insufficient; an exam following some form of training—which could include reading materials, attending a lecture with slides or participating in a webinar, among other options—would be a typical training tool applied. This is useful when it’s necessary to confirm a level of understanding of the training material beyond ticking off the “training” item on the regulatory checklist. The ability to pass a test after completing the training can serve as an indicator that the employee understands the material presented.
But test-taking doesn’t allow accurate prediction of performance, particularly in complex tasks like talking to patients or identifying inclusion/exclusion criteria from medical charts, tasks that play a key role in driving clinical trial processes. And for training that can be shown to ensure better decision-making by researchers conducting the clinical trial, a training tool that can measure performance on key tasks while it is being applied might be a better choice. Simulation-based training can fill this bill.
There is a saying: “There’s no substitute for on-the-job training.” But this is not 100% accurate. Simulation-based training can, in fact, substitute for on-the-job training, and without risk to patients. It’s well-established that learning by doing is the most effective way of absorbing knowledge in a manner that will ensure appropriate changes in behavior that will yield stronger performance. Pilots, for example, spend many hours in flight simulators before they are allowed to handle planes with passengers on board.
And this simulated learning-by-doing doesn’t require an exam to prove that the information was absorbed. If the staff completes the simulated activities successfully, that proves competency. Performance during simulations can accurately predict job performance, as well as highlight any problem areas. For instance, if 70% of a cohort failed in a first attempt at a simulated procedure, the organization would know that was a problem area in the protocol that needed to be addressed.
So, organizations need to begin by identifying the level of competency they need and evaluating how crucial that competency is to the overall success of the clinical trial, including the decisions that must be made continuously throughout study conduct to sustain the necessary processes.
Another crucial question concerns the skills or concepts that must be taught. Organizations need to consider whether these skills can be modeled or if they are completely abstract. For instance, it would be impossible to create a simulation for things like the company culture, whereas the specific steps of a medical procedure as part of a clinical trial could easily be simulated. With all of this information in place, it’s easy enough for an organization to identify and apply the appropriate tool to ensure the ideal level of training
Dave Hadden is an entrepreneur and technology innovator, founding Pro-ficiency and pioneering the fields of A.I.-based medical decision-support, Training Analytics, and Virtual Patient Simulation (VPS). Dave has focused his passion for technological innovation and learning systems in the field of clinical trials, helping sponsors make their studies more accurate and efficient through finding the right technology mix such as virtualization, performance management and applied behavioral sciences to produce the most effective, lasting, and engaging results for clinical trials.