Catalia Health’s Mabu Robo-Nurse Profiled

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Catalia is a Rosenman Innovator company.


From Engineering & Technology.

A nurse takes your blood, helps you up on to the freshly laundered bed, and holds your shaking hand. They’re a clinician, carer and comforter. The vast majority of us have, at some point in our lives, been looked after by a ward sister, matron or community nurse. Most of us were delivered into this world by a midwife. Nurses are an essential part of our healthcare from birth to our final days.

This year marks 200 years since the birth of the world’s most famous nurse, Florence Nightingale. The World Health Organisation (WHO) has designated 2020 The Year of the Nurse and Midwife. Nightingale200 events nationwide include a commemoration service at Westminster Abbey, an app-based augmented-reality walk of fame across Derby starring Nightingale (who grew up in the city), and an international #Nightingale2020 ‘Transforming the Impact of Nursing’ conference in London in October.

Many of a nurse’s practical daily tasks are gradually being delegated to machines to make better use of their valuable time. With the threat and demands of Covid-19, this need has suddenly amplified.

Venipuncture – inserting a needle into a vein to get a blood sample – is the world’s most common clinical procedure. But despite its frequency, clinicians still fail in around 27 per cent of patients without visible veins and 60 per cent of emaciated patients. Failure to insert an IV line is one of the leading causes of injury and infection.

Researchers at Rutgers University in the US have developed a robot that finds blood vessels, even if they’re very small, and successfully inserts a needle or catheter. It uses ultrasound and near-infrared imaging to image the tissue, and artificial intelligence (AI) to interpret the images, detect blood vessels and calculate their depth and size. “A device like ours could help clinicians get blood samples quickly, safely and reliably, preventing unnecessary complications and pain in patients from multiple needle insertion attempts,” says Josh Leipheimer of Rutgers’ School of Engineering.

Another method to reduce the number of failed insertions is AccuVein, a form of vein illumination. It uses augmented reality to project the patient’s veins over the skin, allowing nurses to see a map of peripheral veins on the skin’s surface. This has proved to make it 3.5 times more likely a nurse will find blood vessels on the first attempt.

Nurses are being offered a technological helping hand in many ways. Robear is an experimental human-sized nursing-care robot distinguished by its cosmetic sticking-up teddy-bear-like ears. It’s being developed by the Riken-SRK Collaboration Centre in Japan as a tool to lift patients out of beds and into wheelchairs, and to help those who need to stand up. According to Riken, robots like Robear can play an important role in taking the strain off nurses who may have to lift patients 40 or more times a day, risking causing themselves and their patients injury.

At a time of acute nurse shortage, back pain is one of the most common reasons for nurses to be signed off sick. Nurses are in demand today more than ever. Before the outbreak of Covid-19, there were an estimated 40,000 nurse vacancies in the UK. With the arrival of the virus, many nurses are forced into self-isolation while the demand for nursing services spirals.

Technology may not only replace the practical nursing tasks like taking a blood sample or helping a patient into bed. One robot is being designed to meet a patient’s emotional as well as medical needs. Mabu, with its sunflower-yellow body, friendly expression and moony large blue eyes, stands just 15in tall. Manufactured by US start-up Catalia Health, the software inside this non-human nurse is programmed with expertise in psychology and in medical treatment plans to help patients manage chronic conditions.

Through daily conversations, Mabu uses AI to learn about a patient’s medical and psychological needs. “In a clinical setting, if we talk about a doctor with good bedside manner, we don’t mean that he or she has more clinical knowledge than the next person, we simply mean they’re better at connecting with patients,” says Cory Kidd, Catalia Health’s founder and CEO. “I’ve looked at the psychology behind that – what does it mean to be able to do that? – and turned that into the algorithms we use to help create conversations with patients.”

Every day, Mabu talks to patients under ‘her’ care, each conversation lasting three or four minutes, to do a ‘check-in’ and build up a picture of their ongoing health status. The underlying AI algorithms are constantly building and refining the patient’s information. The medical model contains information on specific disease states and drugs, tracks data over time, and self-reports treatment compliance. Psychological data starts off with nothing.

Mabu learns over time, adapting the conversation, picking up emotive cues from both facial recognition and NLP (natural language processing) to assess mental health states. “A lot of conversations start with ‘How are you feeling?’, similar to what a nurse might ask. From there, it might go off in many directions. There are also a few things nurses would ask if they could talk to these patients every day,” says Kidd.

Mabu processes these conversations to give patients tips, medication reminders, and information on their condition. “Based on patients’ answers, Mabu might say ‘You might want to call your doctor’, or ‘I’ll send them this information’, or ‘Let’s check in tomorrow’,” says Kidd. “Mabu has a lot of information about problems a patient might be dealing with, so she’s able to give quick feedback. Simultaneously, she’s sending that information to a clinician.”

Applications on the Mabu Care Insights Platform are built out one disease state at a time. The first users of this robotic nurse were heart failure patients as part of a partnership with US healthcare provider Kaiser Permanente. “One of our primary areas of focus at Catalia Health is to continue building this across new conditions,” says Kidd.

With these developments, Catalia Health is beginning to help patients dealing with conditions such as rheumatoid arthritis and kidney cancer. “So many patients feel they don’t want to bother their doctor, but Mabu encourages them to monitor how they’re doing and take more care, have more control, so they can stay well,” says Kidd.

If you’re embarrassed about pestering your healthcare provider, you can always ask a chatbot – a piece of software that conducts a conversation using auditory or textual methods. Chatbots have been dubbed ‘the future best friend of nurses’. Their chat is often designed to simulate how a human would behave if they were having a conversation with you. ‘Florence’ – an emoji-like female nurse’s face in a blue uniform and starched nurse’s hat – is one such electronic ‘personal nurse’ who pops up on your iPhone. ‘She’ can remind a patient to take their pills and motivate them to adhere to their medical regime. She can also track weight and mood.
Nursebot illustration, inline

Making the technology come to the patient, rather than the patient have to come to the nurse in a healthcare setting, is one of the aims of such technologies. Mabu can be in a heart patient’s home 24/7 in a way a nurse could never be. “This not only benefits the patient, but alleviates some of the strains on the nursing profession. Nurses are frequently overwhelmed when it comes to helping patients with ongoing, chronic conditions,” says Kidd. “Mabu helps to fill in the gaps.”

The portability of new technologies is just as important within the hospital as in the home. Portable devices can monitor vital signs like ECG, respiratory rates, and oxygen saturations while transmitting the information back to a central monitor. This means instead of nurses having to check on patients hourly as in most hospitals, they get sent an alarm notification if there’s any emergency or any changes. That allows nurses to track at the right time, even if there are lots of other things going on.

Wireless patient monitoring, using chips and sensors, is being integrated into beds, blankets, and mattress pads to
report on weight, blood pressure and movement, serving as an extra layer of observation. This helps patients avoid bedsores and falls, and alerts nurses to any changes in patients’ status, whether dramatic or slow building.

Sometimes, it’s simply down to having a firm grip of the data. Florence Nightingale knew all about the importance of that. “Nightingale was one of the first people to use data so that it showed the actual effect of what people were doing in healthcare,” says Dame Christine Beasley, former Chief Nursing Officer for England and chair of the Florence Nightingale Museum. “Today, she’d be Chief Nursing Information Officer.”

Central to this data gathering are electronic patient records (EPR), which can transform the way a nurse operates. EPRs also safeguard patients by accurately tracking progression through various care pathways, and allow test results, diagnoses, procedures, and treatments to be recorded and accessible. In the past, nurses would spend a significant amount of time trying to collate all these disparate elements of information at the bedside.

But there have been continual hurdles to the nationwide implementation of EPR in the NHS. Health Secretary Matt Hancock, a fan of the transforming power of technology in all his previous ministerial roles, set up NHSX – a joint unit bringing together teams from the Department of Health and Social Care, NHS England and NHS Improvement to drive the digital transformation of care. NHSX is due to be working on a ‘tech plan for health and care’ through the first half of this year, though Covid-19 will inevitably divert resources elsewhere. The NHS has launched a digital nursing fellowship programme and the Royal College of Nursing pledged “Every nurse an e-nurse” by this year. As yet, none of these milestones look likely to be met.

At least nurses are now being seen as those who can implement new technologies, rather than as a potential barrier to
them. “It’s easy to overlook the fact that nurses have for generations changed practice and adapted to new demands such as rising acuity, new treatments and prevention of adverse events,” says the National Institute of Health Research at University of Leeds.

Is every nurse equipped to be an e-nurse? Kidd says he’s watched the costs associated with robotics plummet. Many have also enthusiastically adopted computer assistance like Amazon’s Alexa and Apple’s Siri. He believes clinicians have developed an appreciation for technology’s potential to complement traditional methods of care.

“Young nurses are more ready for it; their lives have been more full of technology,” says Beasley, who is also a trustee of the Burdett Trust for Nursing. “And there’s more being introduced into postgraduate training. But the real barrier to nurses using technology is that it simply hasn’t been available to them. There are still community nurses that don’t have iPads, things we all have at home. The NHS has been slow in this.”

Beasley still believes that, while technology can be useful, nursing is, “at heart about care, human to human. Of course some robots can do an enormous amount of technical interventions. But the human touch – holding people’s hands and showing concern – is still right at the heart of nursing. Artificial intelligence is still a big way from that.”

Kidd agrees that the primary use of technology in medicine is to extend the capabilities of human caregivers. He says Mabu does that “by scaling availability both across numbers of patients, but most importantly across time. Mabu is available any time of day or night that a patient wants to talk.” Diagnosis and treatment, though, are still done better by humans, he says.

Beasley emphasises that technology should be the servant, not the master, of nursing and patient needs. “Developments in technology need to be targeted at and driven by need, not the technology itself,” she says. The current Covid-19 crisis has thrown that need into even sharper focus. “Technology is an enabler and transformer. That’s how it supports nursing. We need to ask ‘what does this enable a nurse to do better or faster?’.”