Faith in the Emergency Room is being restored. Blame it on Artificial Intelligence for forecasting patient flow and avoiding unnecessary trips to the Emergency Department.
At a glance:
Imagine you’re an emergency physician. You’re known for your short attention span, but also your ability to put puzzle pieces together fast. You get excited about providing the best possible journey for the unexpected, urgent patients you’re going to see. But once you approach the waiting room, you are faced with reality. Crowds are shuffling in and you won’t have much time for each patient. Emergency medicine is one of the most tiring specialties in medicine. Is it time to revolutionize it?
Patients numbers in the ER continue to rise
Some cold, hard facts. Emergency rooms (ERs) worldwide are suffering. Crowds are seeking primary care behind emergency doors and creating obstacles for real emergencies. The trend is not new, and visits to the ER have been rising at a rate of 1.5-2% a year since at least 1966. Everyone knows the situation and is doing their best to cope.
Why would a patient without an urgent condition prefer to go to the emergency department rather than see his primary care physician? Pretty much the same reason people would rather use giants like Amazon than go to the local bookshop: convenience, working hours, the “one-stop shop” factor, the lack of limitations, and available specialists.
Let’s be honest. Primary care physicians are overwhelmed with inquiries from patients and lack the human power to respond promptly. ER staff is burning out because they don’t feel that they are offering a satisfactory patient journey as often as they’d like when the patient crosses those doors.
How AI in emergency medicine can help cut unjustified visits to the ER?
If we’re interested in reducing unjustified visits to the ER, it’s time we empowered our patients with reliable symptom checkers they can use before they come in. The are several vendors out there with solutions powered by Symptom Checker being the tool offered by Infermedica. The patient is asked several questions in a clear manner and ultimately gets an idea of what might be going on. Once they reach the health checkup results page, they can be directed either to the ER or to a booking system with an appropriate physician (a general practitioner or a specialist).
Another way of avoiding unnecessary trips to the ER is to take emergency care to the patient’s home, and that’s Call9’s business. Call9 uses highly-skilled first-responders, known as Clinical Care Specialists (CCs) who will go to nursing homes and rehab centers, providing access to emergency care 24/7. Using the CCs and technology, a physician working remotely, can diagnose and prescribe treatment, avoiding unnecessary trips to the ER.
Using AI to forecast the flow of patients in ER
Emergency medicine is gaining a new appreciation for Artificial Intelligence thanks to new tools for good health management. The forecasting era in the Emergency Room is upon us! Say goodbye to code black days. Powerful algorithms that take into account multiple factors can anticipate when patients will go to the ER. Equipped with innovative forecasting models at the cutting edge of technology, Opta Urgences claims to be able to predict the number of patients arriving at the emergency room on any given day. With a forecast reliability of more than 92%, it enables, in theory, enhancement of services and better management of human and material resources.
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Qventus builds on this and allows for efficient management of resources. In crisis situations, when there is little time to think, ER teams will be glad they can count on this state of art virtual assistant. Are there enough beds? And ambulances? How about healthcare workers? Qventus knows.
Knowing such information beforehand allows the ER team to organize human and material resources to respond accordingly. But the use of artificial intelligence in the ER is not limited to predicting the flow of patients.
“This is an innovation with the potential to change the way Emergency Medical Services handle emergency calls.” —Freddy Lippert, MD, CEO EMS Copenhagen
In 2016, dispatchers in Copenhagen began using Corti - think Siri on steroids and with predicting skills. This artificial intelligence digital guru recognizes cardiac arrest by analyzing the sounds and voices heard on the line when someone calls 112 (or 911 in the USA).
Fast-track patient journey in the AI emergency room
In a recent article published in the American Journal of Emergency Medicine, Berlyand Y. et al. salute the potential of AI to accelerate the patient journey within the ER: “rapidly interpreting clinical data to classify patients and predict outcomes is paramount to emergency department operations, with direct impacts on cost, efficiency, and quality of care.”
According to this research team, there is sufficient potential for AI to transform the emergency room at nearly every step of the patient journey:
Artificial intelligence interventions and subsequent operations benefits at different stage of ED Workflow
It comes as no surprise then that AI devices for the Emergency Room are trending. Better, faster and stronger triage is in! Physicians or nurses rating their patients on the emergency severity index alone are out. Machine-Learning-Based Electronic Triage, or E-triage to its friends, is here to stay.
There is much more to say about AI in the Emergency Room, but we will follow up on that in another article. For now, we know that pairing robust AI with hardcore healthcare professionals leads to increased efficiency in the ER.
This power duo cuts time and costs while improving patient outcomes. Isn’t that what we’ve wanted all along?
Berlyand, Raja, Dorner and others. How artificial intelligence could transform emergency department operations. American Journal of Emergency Medicine.
Jernite and Halpern. Predicting Chief Complaints at Triage Time in the
Emergency Department. AMIA Annual Symposium Proceedings.
Nicholl and Mason. Return of the “corridors of shame?”. BMJ.
Turner, Nicholl, Mason, O’Keeffe and Anderson. Whole System Solutions for Emergency and Urgent Care. University of Sheffield.