5 ways AI's efficiency is benefiting emergency care

20th August 2020
Lanna Cooper

Artificial Intelligence (AI) is everywhere now, and in most cases it is making industries better and more efficient. The AI industry generated about $80m of capital investments, from every corner of the commerce globe. The healthcare industry, in particular, has greatly improved quality of emergency care throughout the hospital space by utilising AI in everything from health education to ambulatory service processes.

Guest blog written by Amber Harris, Academic Resources, Circa Interactive

Though new technologies in the healthcare industry tend to take a while to implement, hospital emergency departments are utilising the AI technologies in many different ways, and here are 5 that stand out.

Urgency defined

With AI collecting an analysing data almost instantly, doctors can more efficiently determine which patients need care the fastest. Utilising a set of questions, urgent care reception can weigh patients’ ailments against each other and let doctors know who needs immediate care and who can stand to wait for a little bit. This is especially important during the coronavirus pandemic, as hospitals are overcrowded and patient selection is more important than ever.

For patients that do not end up checking the 'urgent' box, scheduling of appointements is also much easier thanks to AI.


Of all the parts that make the hospital machine work, scheduling may be the most essential. Without doctors and nurses care can’t happen, and mis-scheduling of patients can result in down-time for healthcare professionals that could have been utilised somewhere else. AI allows for instant scheduling and schedule changing, and keeps all parties up to speed  with the click of a button.

In an attempt to fix the common complaint of waiting times, AI algorithms can better determine how long meetings will take, and make for a much more streamlined approach to timing, keeping waiting rooms emptier and doctors busier.

Advances in advanced imaging

Advanced imaging procedures like CT scans and MRI’s are also more efficient thanks to AI. Some things are just still too impossible for the naked eye to see, but common things that can be 'seen' at a granular level by machines can allow doctors to form very strong hypotheses from the computer analyses of a given advanced image. Machine learning takes AI a step further... whereas the computers are actually programmed to recognise changes and, thus, 'learn' new trends that they can provide analysis to doctors for.


At the core of all AI is data. Whether that data is programmed one time into the AI machine, or it is regularly added, it is still the motor behind what AI can do for any industry. Where that comes into play in healthcare is with patient records. Being able to have a literal world view of a patient’s data (and how it compares to other patients across the globe for a given set of symptoms) can truly save lives when used correctly.

Protecting such large amounts of data is a whole other story, but the access to such a vast amount of information regarding patient health is a goldmine for means of increasing patient care.

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