Virtual Reality for Medical Training: Overview
ScienceSoft leverages its 34 year-long practice in IT and 18 year-long expertise in healthcare to deliver top-class VR software products and solutions.
Overview of VR Technology for Medical Training
When used for medical training, virtual reality solutions help prepare surgeons, physicians, and nurses for high-stress situations (e.g., emergencies, complex surgeries) and provide them with concise feedback. After passing the VR training, the healthcare professionals report improved accuracy and confidence when dealing with high-risk conditions.
VR for Medical Training: Market Overview
The Virtual Reality (VR) training market generated $204 billion in 2019 and is expected to reach $601 billion in 2027 growing at a CAGR of 13.7%. Today, healthcare is one of the top VR technology adopters, using it for risk-free, realistic, and highly effective training of new medical experts.
Use Cases of VR for Medical Training
1
Surgery simulation
Simulation of an operating room environment. Helps surgeons gain practical skills and raise competence levels in safe environment.
2
Crisis simulation
Simulation of rare emergencies, accidents with multiple casualties, or disease outbreaks. Allows medical experts to develop automatic response behavior to low-frequency situations.
3
Onboarding
Simulation of typical work environment for starting-out medical professionals. Helps to faster adjust to real job specifics and eliminates skill deficiency in risk-free conditions.
4
Use of medical equipment
Simulation of operating professional medical equipment. Minimizes training costs due to trainer-less guidance and lowers the learning curve.
VR Medical Training Solution Architecture
The architecture of a VR solution for medical training usually comprises three main elements: a client VR application, which loads necessary data from the database web server, and a web administration panel for managing the two.
The key modules of the Client VR application are:
- VR visualization module – defines the logics of the VR world-building by defining physics (usually with the help of NVidea Flex) and storing AI data for non-controllable VR characters. Patient AI is critical for onboarding and crisis simulations, as it helps to recreate real communication. Instructor AI is vital for guiding a surgery or assisting in medical equipment use training.
- Replay and training analytics module – automatically records the simulation and assesses a trainee’s performance based on numerous metrics. It’s possible to create a database for storing multiple recordings for future replay or only make the last simulation available for a replay.
- Scenario editing module – allows editing existing scenarios, stored in the database.
- Supplementary data load – optional load of additional data that can be useful for a trainee during the simulation (for instance MRI or CT 3D models, equipment operation tips or steps, etc).
- Scenario simulation system – allows a user to interact with the scenario and its content.
3D modeling
VR engine
Cloud databases, warehouses and storage
AWS
We use Amazon Redshift to build cost-effective data warehouses that easily handle complex queries and large amounts of data.
We use Amazon DynamoDB as a NoSQL database service for solutions that require low latency, high scalability and always available data.
Azure
We leverage Azure Cosmos DB to implement a multi-model, globally distributed, elastic NoSQL database on the cloud. Our team used Cosmos DB in a connected car solution for one of the world’s technology leaders.
Azure SQL Database is great for handling large volumes of data and varying database traffic: it easily scales up and down without any downtime or disruption to the applications. It also offers automatic backups and point-in-time recoveries to protect databases from accidental corruption or deletion.
Google Cloud Platform
We use Google Cloud Datastore to set up a highly scalable and cost-effective solution for storing and managing NoSQL data structures. This database can be easily integrated with other Google Cloud services (BigQuery, Kubernetes, and many more).
Clouds
Johnson and Johnson Medical Devices Companies
developed a VR training system for practicing Anterior approach in hip surgery. The Imperial College London’s later study showed that 83% of the surgeons, who completed this VR training, could successfully perform the real surgery with minimal guidance, whereas those, who didn’t complete the training, required assistance.
Children’s Hospital Los Angeles (CHLA)
partnered with Oculus to create a VR simulation of emergency scenarios in pediatric care. The solution helps minimize the gap between medical school and real practice by repeatedly performing rare scenarios that have high stakes. The positive results drove further extension of the VR training to other 11 healthcare institutions.
Limitations of VR’s applicability in medical training
Despite the development of haptic technology, it’s not recommended to use VR for practicing procedures that rely on thorough palpation or involve surgical drilling, since highly-detailed surfaces and vibration feedback are hard to simulate. However, even with the limitations, the range of areas where VR training proves to be very effective is immense.
Possibilities of the solution’s growth
Scalable VR solution architectures allow for cheaper and faster evolution of the VR software. With all the asset data stored independently from the client, in the database, it is simple to expand scenarios: you can, say, add an “Instructor” user role and modify an existing simulation so that not only a trainee, but also a trainer could enter the VR world.
VR simulation vs. Real-life training
Ideally, VR-based and real-life training should be combined. Yet, it’s hard to overestimate the importance of risk-free environment that defines VR training as well as its key possibility of infinite task repetition.
So far, practical studies show that high-quality VR software can bring the same qualitative results as real-life simulation and – in addition – help reduce the training costs. Replacing mannequin-based practice with VR training in learning to treat pulmonary disease, for example, has brought successful performance results and allowed for a 3x cost reduction.
Costs of Implementing VR Medical Training Solution
At ScienceSoft, we define the price of VR software development by analyzing the following:
- Method of acquiring/creating key art assets (Photoshoot, 3D CAD rendering, Video shoot)
- Number of 3D models (in case of 3D CAD rendering).
- Number of user roles.
- Number and complexity of training scenarios.
Additional costs of the entire solution may be related to:
- VR hardware (with or without haptics)
- Development of a training analytics module
- Possible integrations with:
- Learning Management System (LMS)
- Content Management System (CMS)
Operational costs include:
- Cloud services (price depends on stored data volume and bandwidth)
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According to ScienceSoft’s experience, the average cost of a full-fledged medical training VR application ranges from $120,000 to $360,000. |
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VR for Medical Training: Consulting and Development by ScienceSoft
Being ISO 13485-certified to design and develop medical software according to the requirements of the FDA and the Council of the European Union, ScienceSoft delivers high-end VR solutions for medical training.
VR for medical training: consulting
- Concept productization.
- Long-term road-mapping.
- Design of scalable architecture.
- Integration planning.
- Technology stack optimization.
VR for medical training: development
- Architecture design.
- UX and UI design.
- VR development and testing.
- Integration with hardware.
- Continuous support and evolution.
About ScienceSoft
ScienceSoft is a global software development and consulting company, established in 1989 and headquartered in McKinney, TX. Employing mature quality and data security management systems, supported by ISO 9001 and ISO 27001 certificates, we offer VR software development to healthcare and other industries.