Executive summary
In cases of medical emergencies – whether it’s a car crash on a busy highway, a serious injury at home, a building fire, or the aftermath of a natural disaster – every minute spent without proper treatment can dramatically reduce someone’s chance of survival or full recovery. In fact, those minutes often matter more than we realise: when the brain is deprived of oxygen, permanent damage begins after just 4 minutes, with death following only 4-6 minutes later. In this race against time, emergency services are increasingly embracing innovative technologies to shorten their response times and ensure better patient outcomes.
- Technologies like AI, robotics, and VR are being used to transform every step of the emergency response process, from dispatching all the way to triage.
- Corti has developed a smart assistant designed to help dispatchers analyse emergency calls in real time and accurately assess the severity of the situation.
- Mediwave’s connected ambulance can transmit a patient’s vital signs to the hospital in real-time, giving doctors a head start on treating the patient.
- Johns Hopkins Hospital is using an AI-powered tool named TriageGO to help nurses assess patients’ risk levels and streamline the triage process.
- One ambulance service in the UK is using VR to help its incident commanders practise their response to scenarios like car crashes or terrorist attacks.
As emergency departments continue to face unprecedented pressure and healthcare workers experience growing burnout, these tools offer a dual benefit. Not only do they improve patient outcomes, but they also lighten the cognitive burden on medical professionals who have been carrying an increasingly impossible load. The result is a smarter, faster, and more capable emergency response system that ensures each patient receives the best care possible in their most vulnerable moments.
Medical emergencies often strike without warning – one moment you’re going about your day, the next you’re facing a critical situation where every minute counts and time can be the difference between life and death. As remarkable as the human body undoubtedly is, it’s also incredibly fragile and starts to deteriorate quickly when deprived of what it needs. Studies have shown that just four minutes without oxygen is enough to cause permanent brain damage, while another four to six minutes results in death. Pretty sobering when you think about it, right?
Emergency medicine has always operated within this unforgiving timeline. Today’s healthcare professionals know all too well that the time that passes between an incident occurring and the moment of medical intervention often determines whether someone walks away from a crisis or doesn’t recover at all. In this race against the clock, emergency services worldwide are increasingly turning to the bleeding edge of technology to accelerate response times and expand their treatment capabilities. So, let’s take a closer look at how modern tools are revolutionising the field of emergency medicine, enabling healthcare providers to deliver critical care when and where it matters most.
“It’s a win-win. We get to patients faster, and are more effective at responding with existing resources.”
Dovie Maisel, VP of operations at United Hatzalah
AI-assisted dispatch
AI promises to revolutionise how dispatchers do their jobs, eliminating language barriers and reducing the number of errors.
It all starts with the phone call. Someone in distress dials emergency services, their voice often shaking with fear or urgency. On the other end, a dispatcher picks up, ready to assess the severity of the situation and mount the appropriate response. These are remarkable professionals, trained to stay calm amid chaos and make quick, accurate judgments under immense pressure – but they are still human at the end of the day. The sheer volume of calls flooding in day after day can be overwhelming for even the most experienced dispatcher. There’s also the very real possibility that the caller may not be a native or speak the language well, limiting the dispatcher’s ability to parse the situation correctly and make the right call in a timely manner.
An AI-powered ally for dispatchers
Fortunately, dispatchers now have a helping hand from AI. Danish startup Corti has developed a smart assistant that works alongside dispatchers and helps them analyse emergency calls in real time. It automatically captures all of the relevant information and compares it against millions of historical cases to provide dispatchers with actionable insights that can help them accurately assess the severity of the situation and make better-informed decisions. What’s particularly impressive is how Corti goes beyond just words. In addition to analysing the conversation between the caller and the dispatcher, the AI can also pick up on non-verbal cues like agonal breathing, the distinct gasping sound often present during cardiac arrest or stroke.
The presence of the smart assistant has been shown to give the dispatcher’s abilities an appreciable boost. It can even guide dispatchers through the call, suggesting important questions to ask, recommending next steps, and proposing possible diagnoses. The results speak for themselves: clients using Corti have seen a 40% increase in correct diagnoses, 25% more accurate protocol selection, and have cut down call times by around 10%.
Meanwhile, across the Atlantic, a call centre in Delaware County, Pennsylvania, has implemented a platform called Prepared Assist, which uses AI and natural language processing technology to automatically translate a call in real time and help dispatchers in high-stress situations better understand what’s going on. The software can also flag key phrases that might warrant specific responses and help ensure no crucial details slip through the cracks. According to the company behind it, the technology can shorten a call by nearly five minutes – an eternity for someone in need of emergency assistance.
Predictive emergency response
Of course, there’s always a way to take preparedness to the next level. Rather than waiting for an incident to happen, Israeli emergency medical services organisation United Hatzalah is using AI to predict when and where the next medical emergency will occur. So, how does it work exactly? The system analyses 18 years’ worth of emergency call data, alongside factors such as weather, time of day, and season, to identify locations where an incident is more likely to happen.
While it cannot predict the exact nature of the emergency, the system enables United Hatzalah to strategically position its resources in advance, significantly reducing the time it takes for them to arrive at the scene. “It’s a win-win,” says Dovie Maisel, VP of operations at United Hatzalah. “We get to patients faster, and are more effective at responding with existing resources.” During a three-month pilot, the organisation saw its accuracy rate increase by 85% in urban areas, while its response time was reduced to just 90 seconds.
“I, as a physician, can be there in real time with that paramedic seeing what they’re seeing, hearing what they’re hearing and guiding them on procedures and just being a second set of eyes on things that are complex or challenging.”
Dr Christopher Russi, emergency medicine physician at the Mayo Clinic
Streamlining emergency care
Emergency departments worldwide are increasingly using digital technology to streamline communication and ensure that critical patients reach the hospital in time.
Once paramedics arrive at an emergency scene, their first task is to assess the situation, stabilise patients, and get them to the hospital as quickly as possible. Don’t let this description deceive you into thinking the job is a simple one, though – the cognitive load and emotional toll on first responders is immense. There are typically just two of them handling the entire emergency – one has to drive the ambulance safely but quickly through traffic, while the other is single-handedly managing a potentially critical patient in the back, as well as a potentially distraught loved one.
All the while, they’re trying to communicate vital information to the hospital so the emergency department can prepare appropriately for their arrival. It is little wonder that communication breaks down sometimes. As patient details pass from paramedic to dispatcher to hospital staff, vital information can easily be lost or plain misunderstood. Such miscommunications can have serious consequences, resulting in treatment delays, medical complications… and in the worst-case scenario, a patient’s death.
A virtual ride-along
It comes as a relief to discover that multiple technologies now exist that can help. Digital healthcare startup Mediwave recently showcased its latest innovation: the world’s first AI and AR-powered emergency response suite. The central component of the suite is a connected ambulance equipped with 4G/5G technology and the Internet of Medical Things (IoMT), which enables paramedics to transmit the patient’s vital signs to the hospital in real time. This gives doctors a better insight into the patient’s condition before they even arrive, allowing them to prepare appropriate treatments and eliminating communication errors.
Paramedics are also supplied with an AR headset that allows them to display information about the patient in their field of view or receive suggestions on proper use of medical equipment, such as the optimal placement of ECG probes. They can also share a live camera feed from the ambulance with the hospital or communicate with a doctor over video to ensure optimal care for the patient during transport. There is also an intelligent EMT assistant that uses AI and speech-to-text transcription to automatically fill out forms and generate incident reports, allowing paramedics to focus on what matters most – saving lives.
Similarly, the Mayo Clinic recently joined forces with telehealth technology company OPTAC-X on a pilot that will see the hospital’s doctors virtually riding along with paramedics as they head out to a scene. By putting on a pair of specially designed smart glasses, doctors will be able to observe as paramedics administer treatment to a patient and even guide them through the procedure, significantly improving the patient’s chances of survival. “I, as a physician, can be there in real time with that paramedic seeing what they’re seeing, hearing what they’re hearing and guiding them on procedures and just being a second set of eyes on things that are complex or challenging,” explains Dr Christopher Russi, emergency medicine physician at the Mayo Clinic in Rochester, Minnesota.
Green wave
Of course, getting to the hospital quickly remains a major challenge, especially in our ever-congested urban networks. To solve this problem, cloud software firm LYT has developed an AI system that can communicate with a city’s traffic infrastructure and clear a path for emergency vehicles. As the vehicle approaches an intersection, the system sends a signal to the city’s traffic control centre and requests a green light, ensuring that the vehicle can pass the intersection without stopping and enabling it to reach its destination as quickly as possible.
“We can see where an incident is, we can see where the vehicle is, and based on historical travel patterns, we can predict the route that the vehicle will take and clear each corridor,” says Laramie Bowron, LYT’s vice president of sales. According to the company, their technology has demonstrated remarkable effectiveness in the field, improving emergency response times by up to 69%.
High-tech ER
With ER staff buckling under pressure, AI and robots are stepping up to accelerate the triage process and ensure that those in need of immediate assistance get it as soon as possible.
Unfortunately, the challenges don’t end once the patient finally arrives at the ER. In fact, that’s often where a whole new set of problems begins. It’s safe to say that emergency departments worldwide are buckling under pressure. Once designed as safety nets for only the most urgent medical crises, they’ve now become the default option for many patients, leading to overcrowding, longer waiting times, and staff burnout. Picture this all-too-common scene: You arrive at an ER with severe chest pain, but so do fifteen other people with various complaints ranging from sprained ankles to high fevers. Who gets seen first?
That decision typically falls to a triage nurse who might have just seconds to assess your condition. And when you’re evaluating hundreds of patients during a 12-hour shift, even the best clinicians can miss subtle warning signs or inadvertently prioritise the wrong cases. This highly subjective evaluation process sometimes means the quiet heart attack patient might wait while the more visibly distressed but less critical case gets immediate attention. The consequences can be serious – patients deteriorating in waiting rooms, others giving up and leaving without treatment, and healthcare teams struggling with the emotional weight of knowing they simply can’t get to everyone fast enough.
Optimising triage with AI
The situations unfolding in emergency rooms around the world may be dire, but solutions are emerging that can help ease the strain. A team of researchers at Johns Hopkins Hospital developed an AI-powered tool named TriageGO, which is designed to help ER nurses make faster, more accurate triage decisions. Trained on a comprehensive dataset that includes patient-reported information, vital signs, and electronic health records, the tool can evaluate a patient’s risk levels with a high degree of accuracy and suggest a suitable triage category for them. Early results were rather impressive. After bringing TriageGO in, the hospital saw wait times plummet by 30%. They could treat more patients and significantly reduced the number of people who walked out without receiving proper care. But most importantly, it enabled the hospital to identify low-risk cases early and redirect them to more appropriate care alternatives, freeing up resources to focus on those who require immediate help.
The emergency department at Scarborough Hospital in England has taken a slightly different approach by adding a humanoid robot named Diagnostic Artificial Intelligence System, or DAISY for short, to its ranks. DAISY’s role will be to ask patients who walk into the ER a series of questions and gather important information about their condition, including their symptoms, pulse rate, and body temperature. It will then analyse this information and use it to build a detailed clinical report that helps the staff make better-informed decisions about what to do. However, the hospital has been careful to emphasise that DAISY isn’t replacing any humans – patients still receive their actual treatment based on a doctor’s assessment. This pilot phase is really about seeing whether the robot can gather reliable patient information while freeing up medical professionals to focus on treatment rather than data collection.
Virtual practice makes perfect
The nature of emergency response work presents a unique training challenge. Could VR offer a solution to this problem?
Like any profession, mastering emergency care requires practice – lots of it. But here’s the thing: how do you practice responding to a major highway accident or a terrorist attack? You can’t exactly stage a 12-car pileup on the interstate or simulate a building collapse with real people for training purposes. And scenarios involving mass casualties, hazardous materials, or extreme weather conditions? Those would be either dangerous, unethical, or downright impossible to recreate safely in the real world. So, how do emergency services train their personnel without putting anyone at risk? Well, in many cases, virtual reality can bridge that training gap.
For example, the South Western Ambulance Service NHS Foundation Trust (SWASFT) in the UK has implemented VR technology to train its incident commanders in situations otherwise impossible to replicate. Among the scenarios offered by SWASFT are terrorist attacks, devastating floods and multi-vehicle crashes on the highway. These virtual scenarios enable commanders to test their knowledge, decision-making skills, and crisis management abilities in environments that feel remarkably real. They use the same information, intelligence, risk assessments, and procedures they’d use in real life to develop strategies for handling these complex situations.
Meanwhile, student paramedics in the West Midlands are using a sophisticated VR simulator to improve their emergency driving skills. The simulator, which consists of an ambulance dashboard with a steering wheel, moving pedals, and flashing lights, immerses students in a wide range of scenarios they can expect to encounter in real life, such as driving in extreme weather conditions or a pedestrian suddenly stepping into the road. This allows trainees to develop muscle memory and quick reflexes for emergency driving without putting themselves or the public at risk. “These are scenarios that could happen while driving an ambulance, but we cannot stage them in a real-life setting,” explains instructor Russell Ames. “We want to ensure that they are given the chance to prepare for this so that they can respond to patients safely and continue to save lives.”
The battle within
Emergency workers face a wide range of traumatic experiences at work, often resulting in the development of mental health issues. What can be done to prevent this?
As we’ve already mentioned several times throughout the article, emergency work takes a heavy emotional toll on the people involved in it. While we often focus on the physical dangers and technical challenges emergency workers face, there’s another battle happening beneath the surface – one that unfolds in the minds and hearts of those who rush toward the disasters others flee from. Think about what emergency workers witness in a typical week: devastating car accidents, children fighting for their lives, suicide attempts, domestic violence, and moments of profound human suffering. They’re routinely exposed to the kind of traumatic events most of us might encounter once or twice in a lifetime, if at all. It’s no wonder these experiences leave deep psychological imprints.
According to the National Institutes of Health, nearly 20% of emergency workers have been diagnosed with anxiety, while 10% struggle with mood disorders. Furthermore, studies have found that healthcare workers in the UK experience PTSD at a rate of nearly 14%. What’s particularly troubling is that many emergency workers only seek help once their symptoms become debilitating. By this point, the psychological wounds have deepened, making recovery more challenging and prolonged. “If people are helping others deal with their trauma, they often put their own aside,” explains Dr Nicola Cogan, chief scientific adviser at the University of Strathclyde in the UK. “On average, nine years pass before first responders seek help for trauma. They may think they need to be stoical and cope with everything, but they do need to take care of their own needs as well.”
A culture shift
To provide emergency workers with the support they need and help them address their mental health challenges, researchers from the University of Strathclyde partnered with software design company Sentiental to develop an AI-powered application named Sentinel, which was designed to help emergency workers identify early signs of trauma and react before they escalate into more serious conditions. Developed in close collaboration with emergency workers themselves, the app offers a wide range of mental-health-related features, including psychoeducation, grounding techniques, sleep therapy, physical exercises, coping strategies, journaling, and advanced mood tracking and reporting.
In addition to helping emergency workers deal with their mental health challenges, tools like Sentinel could have an added benefit in that they could help facilitate a culture shift within emergency services. By normalising regular emotional check-ins and early intervention, they could challenge the outdated “tough it out” mentality that has contributed to so many hidden struggles. Many workers fear being perceived as weak or unreliable if they acknowledge their mental health struggles. Others simply normalise their symptoms, not recognising that what they’re experiencing isn’t just “part of the job” but actually treatable psychological distress. “Staff can no longer be told ‘you signed up for this,’” says Mykay Kamara, Sentinel’s chief executive. “There needs to be a duty of care for these employees.”
Learnings
So, what’s the big takeaway here? For those working in emergency services – from dispatchers to paramedics to ER doctors – these technologies offer something profoundly personal: the chance to save more lives while bearing less of the impossible weight that comes with making split-second decisions amid chaos. The emotional toll of emergency work is immense, but imagine the difference when an AI confirms your instinct about a cardiac arrest, or when virtual reality has prepared you for a scenario you’ve never faced but are now equipped to handle.
As patients and potential patients (which, let’s face it, is all of us), these advances offer something equally profound: the possibility that when our moment of crisis arrives – that car accident that heart attack, that allergic reaction – the system responding to us will be smarter, faster, and more capable than ever before. Of course, this path forward isn’t without thorny questions. As we entrust more decisions to artificial intelligence, how do we ensure these systems don’t perpetuate existing healthcare disparities? And how do we maintain the delicate balance between technological efficiency and the compassionate human touch that can itself be healing in moments of crisis?
