Improving Healthcare Education and Simulation with AWS
Medical professionals require the latest in education and training in order to effectively care for patients. Healthcare simulation is a broad concept that healthcare professionals use for education, assessment, research, and health system integrations for helping with patient safety. In healthcare organizations, this often means creating advanced simulations designed to push clinicians and test a wide range of scenarios using purpose-built mannequins, actors, and hospital rooms.
These rigorously designed scenarios have instructors often emulate a medical event, and the clinicians respond as if the scenario is occurring in the real world. Just like how NASA trains astronauts with advanced simulations before sending people into space, healthcare simulation is designed to train clinicians to be ready for anything.
Healthcare simulation continues to be improved using the latest in technology, research, and instructor knowledge. However, simulation programs at healthcare organizations are now often tasked to train as many clinicians as possible, while keeping costs down. They often have to utilize smaller support staff, while collecting as many data points as possible. This is challenging, given that simulations take clinicians and staff away from the patient floor. Also, mannequins and equipment can be expensive to purchase and maintain. Coordinating schedules and booking rooms can be complex, and video recordings of simulations for play-by-play debriefs must be stored securely, yet also be easily accessible to the correct audience. Capturing data and reporting on trainees is also difficult, because simulations often involve hundreds of trainees throughout the year. Simulations may last only ten minutes, and each simulation might have a specific scenario played out where multiple trainees respond in different ways to that single event.
Over the past ten years, simulation programs started to explore the use of virtual reality (VR) as one way to automate, expand access to simulations, and open up new scenarios that might be difficult to simulate in the real world (example: helicopters or ambulances). However, customers have told us that the technology was clunky, expensive, and more novel than practical. In short, it wasn’t solving the problems it was intended for. That said, technology has been rapidly improving and only getting better. This post will outline why it is time for simulation programs to re-evaluate VR, and how they can start using VR and Amazon Web Services (AWS) to reduce costs while expanding access to simulations.
Healthcare Education Use Cases
There are three use cases in healthcare that can benefit from simulation: education, assessment, and research.
Figure 1: Simulation Education – Doctor instructing students through the use of a mannequin
Simulation education is a bridge between classroom learning and real-life clinical experiences. A realistic experience is key to acceptance by medical professionals and certification authorities. Similar to aviation training, there are multitudes of hardware and software solutions that are used together in order to deliver an optimal training experience. Healthcare simulation in education relies on simulating real-world scenarios in order to learn how to operate all systems used in care delivery. Complex live simulation exercises may rely on computerized mannequins, which perform dozens of human functions realistically in a healthcare setting, such as an operating room or critical care unit, becoming indistinguishable from the real thing. Whether training in a “full mission environment”, or working with virtual reality that copies the features of a risky procedure, training simulations do not put actual patients at risk. These virtual reality simulations can simulate an operating room and the medical devices associated with caring for the patient, such as IV pumps or cardiac monitors.
Simulation-based assessment is used to evaluate the overall competency of a trainee. The objective is to not only test the knowledge of the trainee, but also the assumed basic skills required to use that knowledge. Typical evaluation methods, such as written or multiple-choice tests, only evaluate the knowledge of the trainees. Using a simulation-based approach, the knowledge is coupled with the basic skills required to complete the task, and thus both are evaluated simultaneously. This can identify gaps in the trainees assumed basic skills in addition to their knowledge. For example, not only does the trainee know which drug to administer in a crisis situation, but do they have the skills to administer it effectively.
Simulation-based research is for researchers who may be trying to understand why a particular event happened, and to simulate the event under a variety of conditions. New procedures for giving dangerous drugs or using advanced resuscitation methods may be studied under simulated conditions. Entire populations, tests, and costs may be represented by patterns of data in a computer and multiple simulations can be run to find optimal solutions for attaining the best health of a community. Different types of simulations—live, virtual reality, and computer-based—may be combined to attack a question from different angles. The ultimate goal is to increase knowledge and understanding, which improve training, evaluation, and optimize care delivery.
Simulation-based learning creates several advantages for healthcare use cases:
- Simulation extends the range of easily accessible learning opportunities.
- Simulation affords freedom to make mistakes and to learn from them.
- The learning experience can be customized.
- Simulation affords trainees the opportunity to receive detailed feedback and evaluation.
Game Engines are Not Just for Games
Healthcare simulations have recently begun to take advantage of commercial game engines, including Unreal Engine and Unity. In fact, these game engines are no longer just for games. The companies and technologies have broadened their focus to including training and simulation across many industries and sectors.
Game engines have become very accessible tools for creators to build and deploy all types of content. Engines include editors, which are used to build environments and add interactive elements from real-life objects. The engines can also create simulated people with visually defined behavior, or write scripts, which bring that experience to life. The end result is interactive content, only limited by the ideas of the creators.
These simulations can then be deployed easily across many platforms including, but not limited to, PC/Mac, iOS and Android devices, AR/VR platforms, game consoles, and streamed to users via modern web browsers. This means you can build your simulation once, and deploy it to many types of people who have access to a diverse set of platforms.
These engines have built-in functionality that let many people connect into shared simulations, just like any multi-player game would. This functionality can be used for connecting training simulations in much the same ways. Users connect to the session from any of the supported platforms, and can immediately engage in the interactive simulation.
Game engines remove much of the work needed to build out connected simulations. Going from an idea to a reality can seem overwhelming. Both Unreal Engine and Unity offer a very large development community, including individuals, as well as companies, who build solutions for their customers. Both engine companies also offer stores, where both free and paid content can be added to utilized in custom built solutions. Content can include not only 3D objects, but also the scripts used as a base for simulations.
With the power of game engines, their development community, and pre-built content, you can start with an idea and build out training simulation focusing on only what will make it successful.
AWS solutions which can help include:
- Powerful 3D accelerated virtual workstations for running game engines.
- NICE DCV is a high-performance remote display protocol that provides customers with a secure way to deliver remote desktops and application streaming from any cloud or data center to any device, over varying network conditions.
- Content Creation Station is an AWS sample for deploying Teradici Cloud Access Software on either CentOS 7 or Windows Server 2019 GPU-Enabled Amazon Elastic Compute Cloud (Amazon EC2) instances.
- Open 3D Engine (O3DE) is a modular, open source, cross-platform 3D engine built to power anything from AAA games to cinema-quality 3D worlds to high-fidelity simulations.
- Perforce, a leading version control solution with game engines, can be deployed into AWS allowing you to centralize your game product assets on AWS for an efficient, cloud first development operations pipeline.
- Deploying Unreal Engine Pixel Streaming Server on Amazon EC2 is a pixel streaming solution to stream unreal engine content to modern browsers.
Current technology allows simulation programs to reduce costs while expanding access to learners by leveraging the power of game engine technology and AWS. Healthcare customers can decrease both time-to-market and development cost of virtual simulation programs. As a result, the existing pain points such as cost, ease of access, and reach can be addressed for the use cases of education, assessment, and research simulation.
While this blog post highlights some of the opportunities at a high level, we encourage our healthcare customers and AWS Partners to reach out to their AWS account teams or contact AWS Sales to begin a conversation around the possibilities of simulation on AWS. Now is the time to take another look at simulations, and applications of the underlying technology, as a solution to some of the most challenging use cases.
To learn more about centralizing your game production assets on AWS, you can read Centralize your Game Production Assets on AWS With Perforce Helix Core.