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26 July 2024
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Technology: Using machine learning to improve ambulance response times
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Jordan MacLachlan, PhD candidate in Computer Science, is working on a project that could help save lives. His research applies machine learning to the challenge of emergency dispatch, with a current focus on ambulances. When someone calls for an ambulance, paramedics strive to arrive as quickly as possible. Simply sending the nearest available ambulance is rarely the best approach. Jordan's models analyse the situation and urgency level to determine which ambulance or ambulances should respond to minimise response times.
“There is a clear link between patient mortality and response times. Our goal is to improve the average response times of our emergency services to better utilise existing resources to ensure they’re available for those who need them most. Literally, every minute matters. If we can use machine learning models to improve response times transparently, it could significantly improve emergency services' ability to meet growing demand," Jordan explains.
Jordan's personal experience drove his interest in this research area. "I was unwell for several years and often required an ambulance," he says. "Our trips to the Emergency Department were so frequent that the ambulance crew suggested my sister become a paramedic, given her ability to handle stress. Investing considerable time and effort into a widely ignored problem was an effective way I could give back and if possible, make my sister’s job a little easier.”
After completing his PhD at Te Herenga Waka-Victoria University of Wellington, Jordan hopes to commercialise the outcomes to deliver an improved ambulance dispatch system to emergency services like Wellington Free Ambulance.
"I am currently working alongside the University on a Ministry of Business, Innovation and Employment Smart Ideas Grant that expands on the work of my PhD. With additional people, we will further improve the realism and efficacy of our models. I want to expand this internationally, maintain research ties between scholars and industry, and ultimately see response times decrease across the board."
If you would like to help with this project, please contact: [email protected]
Source: Te Herenga Waka - Victoria University of Wellington
“There is a clear link between patient mortality and response times. Our goal is to improve the average response times of our emergency services to better utilise existing resources to ensure they’re available for those who need them most. Literally, every minute matters. If we can use machine learning models to improve response times transparently, it could significantly improve emergency services' ability to meet growing demand," Jordan explains.
Jordan's personal experience drove his interest in this research area. "I was unwell for several years and often required an ambulance," he says. "Our trips to the Emergency Department were so frequent that the ambulance crew suggested my sister become a paramedic, given her ability to handle stress. Investing considerable time and effort into a widely ignored problem was an effective way I could give back and if possible, make my sister’s job a little easier.”
After completing his PhD at Te Herenga Waka-Victoria University of Wellington, Jordan hopes to commercialise the outcomes to deliver an improved ambulance dispatch system to emergency services like Wellington Free Ambulance.
"I am currently working alongside the University on a Ministry of Business, Innovation and Employment Smart Ideas Grant that expands on the work of my PhD. With additional people, we will further improve the realism and efficacy of our models. I want to expand this internationally, maintain research ties between scholars and industry, and ultimately see response times decrease across the board."
If you would like to help with this project, please contact: [email protected]
Source: Te Herenga Waka - Victoria University of Wellington