Amar Kendale, Livongo’s head of product at the Health 2.0 Conference in Santa Clara
Digital therapeutics have been positioned as part of the consumer-driven trends pushing forward healthcare innovation.
At a speaker event at the Health 2.0 Conference in Santa Clara, California various healthcare players from large employers to young startups spoke about their approaches to developing and implementing digital therapeutics with their workers or their patients. Here are three key takeaways.
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Move past gamification and into other methods for behavior change
David Hoke, senior director of associate health and well-being at Walmart took the stage with engagedIn CEO Kyra Bobinet to announce Fresh Tri, an app-based wellness and health application that is set to launch in 4,700 stores nationwide.
The application has people set a nutrition or fitness goal, a reason behind that action and clinically validated tasks to meet that goal. Users are essentially able to pilot that behavior and iterate or improve on it if it doesn’t work.
“We find something that works then we use it as a crutch, I think gamification is like that,” Hoke said. “Fundamentally what we started saying is that people in general don’t approach things in a gamified mindset, it’s a great way to get people engaged, but in reality we have to understand how people approach things in the beginning.”
Bobinet, a physician and author on behavior change, said according to neuroscience research, the reason people fail is that they quit trying. An experience with failure kills the motivation to keep trying again.
“Our whole thesis is basically going from goals to practice and failure to iteration,” Bobinet said. “All we want to do is organize a software that supports how the brain actually works and work with – instead of against – the brain.”
For at-home healthcare, make patient experience as simple as possible
There’s been a lot of attention paid to remote patient monitoring as a way to lower costs and improve outcomes, especially for patients with chronic conditions.
Support for the technology has come from both private investors as well as government bodies like CMS, which started reimbursing providers for remote patient monitoring earlier this year.
Amar Kendale, head of product at chronic disease management company Livongo announced the launch of the company’s “cuff-to-cloud” platform which combines the company’s hypertension and diabetes monitoring capabilities.
The mobile application integrates data from multiple sources including the company’s blood pressure, blood glucose monitors, as well as activity sensors
“In many ways the challenge is reducing how much complexity there is, reducing the feature overload that people deal with in order to focus on the most important things,” Kendale.
“Passive is the key, the idea is that the less we’re asking our users to do, the more data we’re going to get.”
By making it easy to visualize and analyze that data in one place, the company says its better able to drive behavior change and help users prioritize certain treatment actions based on current need.
Understand and adapt to user concerns about security
With the increasing ability and economic pressures for medical care to be provided at home, there’s also accompanying patient concerns that emerge about technology playing a surveillance role in people’s lives.
Ricardo Prada, principal UX researcher at Google was on hand to talk about how the company is trying to address the issue. He pointed to a simple idea that if people are uncomfortable around using the company’s technologies, then it is failing in its role as a technology provider.
“For us, a lot of it has to do with ensuring that people feel a sense of control and agency over the data and the devices that are in their lives,” Prada said.
One example is the company’s smart camera Google Clips, designed for pet owners or the parents of young children. Instead of data being automatically pushed to the cloud, the artificial intelligence work is done on the device itself, which gives the user more choice over what gets uploaded and what gets deleted.
That type of “on-device machine learning” is also being made available through computing chips like Google’s Edge TPU system which allow ML processing to be done locally to give users more control over their own data.
Picture: Kevin Truong, MedCity News
