Impressive for a Robot: Home Care Chatbots Included in AI Tools Adopted by the Australian Healthcare Sector

Peta Rolls grew accustomed to receiving the AI's daily check-in at 10am.

A daily check-in call by an automated voice assistant was not part of the service Rolls envisioned when she signed up for St Vincent’s in-home support but when they asked to be part of the pilot program several months back, the 79-year-old said yes because she wanted to help. Even though, to be honest, her hopes were low.

Nevertheless, when she got the call, she says: “I was so overtaken by how interactive the AI was. It was remarkable for a machine.”

“The system would inquire ‘how you are today?’ and that gives you an opportunity if you’re feeling sick to mention your symptoms, or I might reply ‘I’m fine, thank you’.”

“She would go on to ask follow-up questions – ‘have you had a chance to step outside today?’”

Aida would also inquire about what Rolls had planned for the day and “it would reply appropriately.”

“When I mentioned I’m going shopping, she’d say are you shopping for clothes or groceries? I found it entertaining.”

AI Reducing the Workload on Healthcare Professionals

This pilot, which has now wrapped up its initial stage, is one of the ways in which progress in AI technology are being taken up in healthcare.

Digital health company the provider approached the care organization regarding the trial to utilize its generative AI technology to offer companionship, as well as an option for elderly recipients to report any health issues or issues for a staff member to follow up.

A senior director, national director of the home care division, explains the AI check-in being trialled does not replace any in-person visits.

“Clients still receive a weekly face to face meeting, but between these meetings … the automated system enables a daily check-in, which can then flag any potential concerns to either our team or a client’s family,” the director notes.

Dr Tina Campbell, the CEO of the company, reports there have been no any adverse incidents noted from the pilot program.

The company uses advanced AI “with very clear guardrails and prompts” to ensure the conversation is safe and procedures are in place to respond to serious health issues promptly, the director says. For example, if a client is experiencing chest pains, it would be flagged to the medical staff and the conversation terminated so the person could dial triple zero.

She believes AI has an important role given significant workforce challenges throughout the healthcare sector.

“What we can do very safely, with technology like this, is lessen the admin burden on the workforce so trained clinicians can concentrate on doing the job that they’re trained to do,” she says.

Artificial Intelligence Long Established as You Might Think

An expert, the founder of the Australian Alliance for Artificial Intelligence in Healthcare, explains older forms of artificial intelligence have been a common feature of healthcare for a long time, frequently in “administrative functions” such as analyzing scans, ECGs and lab reports.

“Any computer program that carries out a task that involves decision making in some way is AI, regardless of how it accomplishes it,” states the professor, who is also the head of the health informatics center at a leading university.

“If you go the imaging department, radiology department or diagnostic laboratory, you’ll see programs in machines performing these tasks.”

In recent years, newer forms of artificial intelligence known as “machine learning” – an algorithmic approach that enables systems to learn from extensive datasets – have been employed to read diagnostic scans and enhance detection, Coiera notes.

Recently, a screening service became Australia’s first population-based screening program to adopt AI analysis tools to assist radiologists in reviewing a specific set of mammography images.

They are specialized tools that still require a specialist doctor to evaluate the findings they might suggest, and the accountability for a medical decision rests with the healthcare provider, Coiera emphasizes.

AI’s Role in Early Disease Detection

A research center in the city has been working alongside researchers from UCL London who first developed AI methods to detect neurological lesions known as specific brain malformations from MRI images.

These abnormalities trigger epileptic episodes that crequently cannot be controlled with drugs, so surgery to remove them becomes the sole option. However, the procedure can only be performed if the doctors can locate the affected area.

A study recently released in the journal Epilepsia, a group from the institute, led by specialist the lead researcher, demonstrated their “neural network tool” could detect the lesions in nearly all of cases from advanced imaging in a specific form of the malformations that have traditionally been overlooked in the majority of cases (60%).

The AI was trained on the scans of 54 patients and then tested on pediatric cases and 12 adults. Among the youngsters, 12 had surgery and eleven became free of seizures.

The tool employs neural network classifiers similar to the mammography analysis – highlighting regions of abnormality, which are still checked by specialists “but it makes it a lot quicker to reach a conclusion,” the researcher says.

She emphasises the researchers are still in the “early phases” of the work, with a additional research required to advance the tool heading towards real-world use.

A leading neurologist, a brain specialist who was not involved in the research, notes modern imaging now generate such vast quantities of high-resolution data that it is challenging for a person to review it accurately. Thus for clinicians the challenge of finding these lesions was like “identifying the needle in the haystack.”

“It’s a great demonstration of how AI can assist doctors in making earlier, more accurate diagnoses, and has the potential to improve operation opportunities and results for children with treatment-resistant seizures,” Cook comments.

Disease Detection in the Future

A public health expert, the deputy head of the international body's digital health and artificial intelligence section, says advanced AI systems are additionally used to track and forecast disease outbreaks.

The expert, who presented last month at the Public Health of Australia’s conference in the city, gave as an example Blue Dot, a company set up by medical experts and which was one of the first organisations to identify the Covid-19 outbreak.

Generative AI is a additional branch of deep learning, in which the technology can produce original material using training data. Such applications in medicine include tools such as the virtual assistant as well as the automated note-takers clinicians are adopting more.

Dr Michael Wright, the head of the national GP body, says family doctors have been embracing AI scribes, which records the appointment and turns into a medical summary that can be included in the health file.

The president says the primary advantage of the tools is that it enhances the quality of the communication between the doctor and patient.

Dr Danielle McMullen, the chair of the Australian Medical Association, concurs that AI note-takers are assisting physicians manage schedules and says AI also has the potential to help doctors avoid repeated examinations and scans for their clients, if the {promised digitisation|planned digitalization