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New tech tool could lead to improved outcomes for non-English speaking patients and hospital staff.
Researchers and clinicians at the University of New South Wales are working on a new, multilingual AI chatbot designed to act as an interface between patients presenting to emergency departments and the healthcare workers who triage and treat them.
According to research from the South Western Sydney Local Health District, at least 55 per cent of people in the district speak a language other than English at home, making medical care a challenge for ED workers.
“The first thing admission staff will want to do is allocate patients with a score from one to five that measures the acuity – or severity – of the patient’s illness and the level of care required to treat them, with a score of one meaning a doctor will prioritise to see them within 30 seconds,” Dr Narasimhan, senior lecturer in UNSW’s School of Population Health, said in a statement.
“If there’s a language barrier and triage staff have difficulty understanding the person presenting to ED, it can lead to people with really severe or urgent medical conditions assigned a lower acuity score and potentially be made to wait, whereas people with a non-urgent condition can be misclassified as urgent and bumped up to see a doctor straight away.”
Dr Narasimhan, used the example of an Arabic-speaking patient presenting to an ED with acute abdominal pain.
“Beyond language barriers, cultural norms around stoicism might lead them to downplay discomfort, describing severe pain as mere ‘tiredness’,” Dr Narasimhan said.
“A triage nurse, unaware of these nuances, could misinterpret this, assigning a lower priority to a potentially critical condition like appendicitis.”
To solve this challenge, Dr Narasimhan is working with a team of AI engineers, linguistics specialists, and ED clinicians to develop a multilingual chatbot that can both translate for patients and healthcare workers, and highlight any cultural biases that may stand in the way of an accurate medical assessment.
“The idea is that this chatbot will be listening in at the registration point on a computer in an ED and will be able to interpret a patient’s description of their symptoms in real time, allowing triage staff to more quickly and accurately assess the severity of a patient’s condition,” Dr Narasimhan said.
“So if you speak Arabic, it will be able to interpret and translate your Arabic into English. And because it has natural language processing and machine learning capabilities, it will also be able to give an appropriate triage recommendation.”
The program will progress through three phases over the next few years. First, the AI system will be trained on other languages and ED-based medical terminology; next, the chatbot will be tested in a controlled ED-like triage environment.
Finally, the technology will be tested in real-life EDs in areas such as multiculturally diverse Western Sydney.
“We’re trying to access patented algorithms to use in specific settings, such as an ED. If it works in acute settings, it should be easy to adapt for other hospital settings, and even non-hospital settings, such as your GP’s office,” Dr Narasimhan said.
“We think it has multiple uses, and hope it removes one of the major barriers that can get in the way of multilingual people accessing healthcare services in Australia.”
David Hollingworth has been writing about technology for over 20 years, and has worked for a range of print and online titles in his career. He is enjoying getting to grips with cyber security, especially when it lets him talk about Lego.
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