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NIHI develops chatbot to answer patient queries

NIHI develops chatbot to answer patient queries

Date: 10 October 2018

Researchers at the National Institute for Health Innovation are developing a chatbot to answer patients questions after surgery.

The two-year Engagebot project is funded by a Health Research Council Explorer Grant, which support transformative research ideas.

NIHI co-lead health informatics and technology programme co-lead Gayl Humphrey says the aim is to determine if creating a chatbot in this area is possible, useful and acceptable to patients.

Hospital patients are given information, either verbally or on paper, before being sent home but they often do not remember it or misplace the pieces of paper, she says.

This can be worrying for patients who may try to call the hospital department, turn up at the emergency department or spend a stressful few weeks before their next follow-up.

A chatbot could be a good way of providing information in the time between clinical visits.

“It’s about how do we support patients much better and provide information to them how and when they need it, rather than as and when we can provide it?” Humphrey tells

NIHI is working with Waitemata DHB clinical director otolaryngology head and neck surgery David Grayson to teach the chatbot by gathering information on the kinds of questions patients often want to ask and to develop the answers provided.

Participants who are coming up for day surgeries in the service will be recruited to test the bot.

“We’re working with a prototype to look at what are the key things that people forget or want to ask, but didn’t ask at the time and be able to deliver information back that’s relevant to those questions via a chat technology,” says Humphrey.

“A phoneline would need to be staffed 24/7 by people who understand the particular condition. We’re using chat functionality, building up initially the library and training the chatbot using natural language processing.”

She says the project is starting with a ‘blank chat’ as existing natural language processing infrastructures often are not clinical.

“In the health sector we know the workforce is under a lot of pressure. Patients are much more informed and want to be more informed, which means more demand on our health workforce, and some things they want to know are pretty generic,” Humphrey says.

“We are not so good in the transition-to-home area and we don’t have the resourcing to enable phone calls back or routine contact.

“The idea of this is to act as an in between. Chatbots are becoming quite ubiquitous across a variety of settings,” she says.


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