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Robots help patients manage chronic illness at home

Move over, Alexa and Siri. Talking Mabu robot provides one-to-one support while relaying information to doctors.
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Catalia Health uses a personal robot assistant, Mabu, to help patients managing chronic diseases.
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Caption: Catalia Health uses a personal robot assistant, Mabu, to help patients managing chronic diseases.
Credits: Courtesy of Catalia Health

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Catalia Health uses a personal robot assistant, Mabu, to help patients managing chronic diseases.
Catalia Health uses a personal robot assistant, Mabu, to help patients managing chronic diseases.
Courtesy of Catalia Health

The Mabu robot, with its small yellow body and friendly expression, serves, literally, as the face of the care management startup Catalia Health. The most innovative part of the company’s solution, however, lies behind Mabu’s large blue eyes.

Catalia Health’s software incorporates expertise in psychology, artificial intelligence, and medical treatment plans to help patients manage their chronic conditions. The result is a sophisticated robot companion that uses daily conversations to give patients tips, medication reminders, and information on their condition while relaying relevant data to care providers. The information exchange can also take place on patients’ mobile phones.

“Ultimately, what we’re building are care management programs to help patients in particular disease states,” says Catalia Health founder and CEO Cory Kidd SM ’03, PhD ’08. “A lot of that is getting information back to the people providing care. We’re helping them scale up their efforts to interact with every patient more frequently.”

Heart failure patients first brought Mabu into their homes about a year and a half ago as part of a partnership with the health care provider Kaiser Permanente, who pays for the service. Since then, Catalia Health has also partnered with health care systems and pharmaceutical companies to help patients dealing with conditions including rheumatoid arthritis and kidney cancer.

Treatment plans for chronic diseases can be challenging for patients to manage consistently, and many people don’t follow them as prescribed. Kidd says Mabu’s daily conversations help not only patients, but also human care givers as they make treatment decisions using data collected by their robot counterpart.

Robotics for change

Kidd was a student and faculty member at Georgia Tech before coming to MIT for his master’s degree in 2001. His work focused on addressing problems in health care caused by an aging population and an increase in the number of people managing chronic diseases.

“The way we deliver health care doesn’t scale to the needs we have, so I was looking for technologies that might help with that,” Kidd says.

Many studies have found that communicating with someone in person, as opposed to over the phone or online, makes that person appear more trustworthy, engaging, and likeable. At MIT, Kidd conducted studies aimed at understanding if those findings translated to robots.

“What I found was when we used an interactive robot that you could look in the eye and share the same physical space with, you got the same psychological effects as face-to-face interaction,” Kidd says.

As part of his PhD in the Media Lab’s Media Arts and Sciences program, Kidd tested that finding in a randomized, controlled trial with patients in a diabetes and weight management program at the Boston University Medical Center. A portion of the patients were given a robotic weight-loss coach to take home, while another group used a computer running the same software. The tabletop robot conducted regular check ups and offered tips on maintaining a healthy diet and lifestyle. Patients who received the robot were much more likely to stick with the weight loss program.

Upon finishing his PhD in 2007, Kidd immediately sought to apply his research by starting the company Intuitive Automata to help people manage their diabetes using robot coaches. Even as he pursued the idea, though, Kidd says he knew it was too early to be introducing such sophisticated technology to a health care industry that, at the time, was still adjusting to electronic health records.

Intuitive Automata ultimately wasn’t a major commercial success, but it did help Kidd understand the health care sector at a much deeper level as he worked to sell the diabetes and weight management programs to providers, pharmaceutical companies, insurers, and patients.

“I was able to build a big network across the industry and understand how these people think about challenges in health care,” Kidd says. “It let me see how different entities think about how they fit in the health care ecosystem.”

Since then, Kidd has watched the costs associated with robotics and computing plummet. Many people have also enthusiastically adopted computer assistance like Amazon’s Alexa and Apple’s Siri. Finally, Kidd says members of the health care industry have developed an appreciation for technology’s potential to complement traditional methods of care.

“The common ways [care is delivered] on the provider side is by bringing patients to the doctor’s office or hospital,” Kidd explains. “Then on the pharma side, it’s call center-based. In the middle of these is the home visitation model. They’re all very human powered. If you want to help twice as many patients, you hire twice as many people. There’s no way around that.”

In the summer of 2014, he founded Catalia Health to help patients with chronic conditions at scale.

“It’s very exciting because I’ve seen how well this can work with patients,” Kidd says of the company’s potential. “The biggest challenge with the early studies was that, in the end, the patients didn’t want to give the robots back. From my perspective, that’s one of the things that shows this really does work.”

Mabu makes friends

Catalia Health uses artificial intelligence to help Mabu learn about each patient through daily conversations, which vary in length depending on the patient’s answers.

“A lot of conversations start off with ‘How are you feeling?’ similar to what a doctor or nurse might ask,” Kidd explains. “From there, it might go off in many directions. There are a few things doctors or nurses would ask if they could talk to these patients every day.”

For example, Mabu would ask heart failure patients how they are feeling, if they have shortness of breath, and about their weight.

“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,’” Kidd says.

Last year, Catalia Health announced a collaboration with the American Heart Association that has allowed Mabu to deliver the association’s guidelines for patients living with heart failure.

“A patient might say ‘I’m feeling terrible today’ and Mabu might ask ‘Is it one of these symptoms a lot of people with your condition deal with?’ We’re trying to get down to whether it’s the disease or the drug. When that happens, we do two things: 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 — a doctor, nurse, or pharmacists — whoever’s providing care.”

In addition to health care providers, Catalia also partners with pharmaceutical companies. In each case, patients pay nothing out of pocket for their robot companions. Although the data Catalia Health sends pharmaceutical companies is completely anonymized, it can help them follow their treatment’s effects on patients in real time and better understand the patient experience.

Details about many of Catalia Health’s partnerships have not been disclosed, but the company did announce a collaboration with Pfizer last month to test the impact of Mabu on patient treatment plans.

Over the next year, Kidd hopes to add to the company’s list of partnerships and help patients dealing a wider swath of diseases. Regardless of how fast Catalia Health scales, he says the service it provides will not diminish as Mabu brings its trademark attentiveness and growing knowledge base to every conversation.

“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,” Kidd says. “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.”

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