Engineering, Nursing team up to transform medical training through XR, AI, ML
The Ohio State University College of Nursing will soon be able to use the latest in high-tech virtual simulations to train for real-life medical emergencies thanks to a collaboration with the College of Engineering.
ISE Assistant Professor Mike Rayo will join forces with Co-principal Investigators Michael Ackerman, director of the College of Nursing’s Center for Healthcare Innovation and Leadership, Wendy Bowles, assistant dean for baccalaureate programs and Amy Jauch, director of prelicensure programs.
Ohio State was awarded a three-year, $1.5 million Reimagining Nursing Initiative grant from the American Nurses Foundation (ANF) for its Disrupting Nursing Education with XR (extended reality), AI (artificial intelligence) and ML (machine learning). ANF chose 10 pilot programs designed to transform healthcare from among nearly 350 proposals submitted.
Rayo will lead two efforts for the project. “The first is the creation of a simulation that allows nurses to use an AI/ML-infused decision support tool that we have designed to better anticipate and detect patients who will be imminently decompensating, i.e., ‘crashing,’” he says. “We will use real patient data collected from The Ohio State University Wexner Medical Center (OSUWMC), and will therefore know which patients will decompensate, and which will not.”
Rayo says in the first year of the grant, the team will build a limited simulation in which nurses review individual patients on a computer workstation – in the real world, not in XR.
“In year two, our computer simulation will be embedded in an XR universe, in which participants are taking care of multiple patients, and use the AI/ML-infused tool to determine which patients to prioritize and see first, which to go to next and which to deprioritize and just see them during their next scheduled time.”
These simulations serve two purposes, he says. “First, student performance in these simulations will be one of their assessments in one course each year. Second, their performance using the AI/ML-infused tool will be compared to their performance without having the tool available, which allows us to understand the relative benefits and drawbacks of using AI/ML tools to assist with patient diagnosis and response,” according to Rayo.
“In addition to building and running this simulation, we will also be training a machine learning algorithm to dynamically place nursing students into in-person clinicals based on how they are assessed on the previous year’s classes. It is our aim to better connect students with the instructors and learning environments that they need to thrive.”
Rayo says a number of ISE undergraduate and graduate students will be involved in the work. “Students will be leading the design of the AI/ML algorithms, the decision-support software that the AI/ML is integrated into, and the simulation design – both in the real world and in XR – that the nurses will experience,” he says. “Two of my PhD students, Dane Morey and Morgan Reynolds, will be leading the research study design, incorporating a number of AI/ML technologies that will interact in different ways with the nursing students, including some that will give initial advice, some that will critique the students’ plans after those plans have been entered and some that will simultaneously display advice, rationale for the advice and the underlying data for that advice.
“In this way, we will learn how best to instruct students on how to work with AI/ML, and we will learn how to better design AI/ML to work with students,” according to Rayo.
The XR settings will be created as part of the grant. he says, adding that examples of XR classrooms planned to be built include hospital environments, outdoor settings– urban, suburban and rural, “and even classrooms inside the human body.”
He says the Cognitive Systems Engineering Laboratory (CSEL) has had a long-standing relationship with OSUWMC and collaborated with many CON faculty members. “We have been studying how well new technologies can be integrated into nurses’ workflow for over two decades,” he says.
CSEL had been working with Bowles to research how different forms of AI/ML combined with novel methods of data visualization and screen interaction could best support nurses in detecting early signs of patient decompensation.
“The University is encouraging investigators to work together in interdisciplinary and multidisciplinary projects,” Rayo says. “There are also many initiatives that are connecting the College of Engineering and the Colleges of Medicine, Nursing and Public Health. As we all get to know each other better, we are able to envision new ways of working together and new ways to jointly solve both healthcare and engineering problems.”
Story by Nancy Richison
