Immersive learning technologies are growing, and one sector embracing them is healthcare training. Immersive learning tools uniquely engage learning systems in the brain that are highly effective for many forms of training, especially training related to healthcare. These technologies have the potential to improve the quality and quantity of training, reduce training costs, and enhance patient satisfaction through better care from healthcare professionals and a deeper understanding for patients.
These immersive learning technologies are often referred to as extended reality (xR) technologies. They come in two major forms: virtual reality (VR), in which the learner is immersed in a completely virtual environment, and augmented reality (AR), in which the learner is in a combined real and virtual environment where digital information is overlaid onto the learner’s field of view.
In this blog post, I’ll discuss two applications of xR technology in healthcare training. The first is healthcare visualization training, in which a healthcare professional is required to understand and visualize a complex system, such as the human body, or the steps of a specific healthcare procedure. The second is healthcare skills training, in which a healthcare professional must learn some sequence of behaviors, such as how to draw blood, deliver a baby, or perform brain surgery. I take a learning science perspective—the marriage of psychology and brain science—to evaluate the effectiveness of traditional training approaches and compare them with emerging xR training approaches.
Healthcare Visualization TrainingSuppose you’re a healthcare professional learning the anatomy and physiology of the human body. Because the body is a three-dimensional, dynamic structure, your goal is to generate a dynamic, 3-D representation of the body in your brain. Traditional tools for such training are textbooks or slide shows filled with two-dimensional, static images. The student’s task is to take these images and convert them into a mental representation that accurately reflects the human form. This is very challenging, and fraught with potential for error.
The human brain has evolved in such a way that there exist multiple distinct learning systems. Each system is optimally tuned to learn specific types of information. Training works best when the tool applied recruits the appropriate learning system for the task. Unfortunately, traditional approaches to healthcare visualization training that use 2-D images engage a learning system that is not optimally tuned for representing 3-D objects.
Traditional approaches that use static, 2-D images engage the cognitive skills learning system, which recruits the prefrontal cortex and medial temporal lobes in the brain and working memory and attentional resources. Attempting to construct a 3-D, dynamic representation of the human body from a series of images requires substantial cognitive effort. You have to hold a mental representation of a series of 2-D images in short-term (working) memory; you have to combine them on the fly to construct an accurate 3-D, static representation; and you have to apply the dynamic nature of the human form onto this 3-D representation. Each of these steps requires an enormous amount of cognitive capacity (in the form of working memory) and cognitive energy (in the form of executive attention). Any time working memory load and executive attention demands are taxed, you are more likely to make an error and generate an inferior mental representation.
Now consider an xR solution: You place a Microsoft Hololens on your head and a 3-D, dynamic representation of the human body appears in front of you. You can walk around the body and rotate it to see it from all angles. You can select a skeletal view, and touch a bone to see its name. You have a 3-D, dynamic visualization tool that is intuitive and facilitates the development of a highly accurate, 3-D, and dynamic representation in your brain. A tool like this engages the visual representation learning system in the brain, which recruits occipital and temporal lobe structures. By removing the need to construct a 3-D, dynamic mental representation from a series of 2-D, static images, the working memory and executive attention load on the learner has been slashed. Those resources can be used to learn the names of the bones, muscles, arteries, and so on, with a rich visual mental representation upon which to attach them.
Healthcare Skills TrainingAnother important learning task for healthcare professionals is behavioral skills—how to draw blood, insert a catheter, or perform surgery. These skills require learning a set of motor behaviors to be completed in a specific sequence. Although a common approach is to start by reading textbooks, viewing slideshows, or watching someone else complete the task, ultimately the only way to learn a behavioral skill is to do it.
The behavioral skills learning system in the brain evolved to learn behaviors. These skills are learned gradually and incrementally via dopamine-mediated, error-correction learning in the basal ganglia of the brain. When a correct behavior is generated, dopamine is released into the basal ganglia and strengthens the connections between sensory neurons associated with the current environmental situation and motor neurons that initiated the behavior. Thus, that behavior is more likely to be elicited again in the same context. On the other hand, when an incorrect behavior is generated, dopamine is not released into the basal ganglia, those neural connections are weakened, and that behavior is less likely to be elicited again in the same context.
Behavioral skills learning requires extensive practice, and this is one of the biggest obstacles for the healthcare training community. Even when real-world medical training directly targets the behavioral skills learning system, because it is so costly in time and resources, healthcare professionals rarely obtain adequate training—and often receive extensive on-the-job training with actual patients.
This is where xR healthcare skills training technologies could be very useful. A learner could put on a VR headset and have a virtual heart transplant patient on the operating table—a realistic artificial cadaver that provides the appropriate haptic feedback. When implemented correctly, technologies like this will speed the training of healthcare skills and allow learners enough practice to be job-ready before entering a medical facility. The days of on-the-job training with live patients in ERs and training hospitals could be over (or at the very least, dramatically reduced).
xR training also opens up the possibility to train across a broad range of situations. Imagine being able to practice delivering a baby in the back of a taxi with limited medical equipment—a low-probability situation, but one that is life-threatening and for which healthcare personnel would like to be prepared. The broad-based training possible with an xR platform would ready the healthcare professional for any situation.
ConclusionsThe healthcare industry is ripe for the introduction of immersive xR learning technologies. These technologies have the potential to improve all aspects of healthcare training, reduce costs, increase healthcare professionals’ readiness, and most important, instill confidence in patients—thus enhancing patient satisfaction.
To learn more, join me on November 5, 2018, for the webcast, The Learning Science of Extended Reality Technologies and How They Will Accelerate Healthcare Training.