Training healthcare professionals comes with unique challenges. How do you ensure that medics are up-to-speed with the latest technology and techniques when there’s often limited access to new equipment, and it’s not possible to practise on real-life patients? Virtual Reality (VR) could provide the answer. The VR experts at Immerse are creating detailed simulations to upskill healthcare professionals. And immersive, effective training doesn’t just mean better-trained employees, it also means increased engagement, improving staff retention in a sector that’s struggling with understaffing.
How tech is reshaping healthcare
There’s a technology revolution underway in healthcare training. Cutting-edge tools and techniques are changing the way training is delivered, from students watching live-streamed operations by experienced surgeons, to nurses learning how to deal with aggressive patients through VR simulations. And VR is being used in other healthcare contexts too; it’s been shown to be effective as pain relief, redirecting a patient’s attention away from treatment by engrossing them in an alternative experience or game.
The possibilities of VR for healthcare are exciting and far-reaching. And this technology couldn’t come at a better time: the NHS is the UK’s biggest employer, but with A&E admissions continuing to rise and Brexit putting pressure on staffing, cost-effective training and staff engagement and retention are critical.
X-ray training
Consistency is key when it comes to training medics, but ensuring that all staff are getting the same experience and reaching the same standard when the workforce is huge and dispersed is a challenge. Plus, access to state-of-the-art equipment is often limited, making hands-on training difficult. The right use of VR can mean that healthcare employees are trained on new techniques and technologies in an efficient, cost-effective way.
The VR training developed by Immerse for GE Healthcare is a great example of this. CTCA scanning is a non-invasive, x-ray based technique for detecting patients

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