With all the technology and data we have around us today, why is it still so hard to manage type 1 diabetes? The products available to diabetes sufferers at the moment are only concerned with capturing one form of data – glucose levels at a particular moment in time. This makes the whole process very reactive and stressful.
Almost 400 million people around the world suffer from diabetes and the families and friends of sufferers are also affected, particularly when the patient is a young child.
The dynamics of diabetes are complicated. There are a multitude of factors that affect glucose levels, from sleep patterns, hydration levels and exercise plans to environmental factors like air temperature. For a parent of a diabetes patient, trying to keep track of them all on a daily basis is impossible without controlling every aspect of their lives – something that risks damaging relationships as they grow.
Our aim has been to create a platform that could handle multiple streams of data capture and apply advanced analytics to make it useful and meaningful.
In our research phase we wanted to get an understanding of the problem. We wanted to know everything there was to know about living with diabetes and the impact it has on daily life.
In the describe phase we wanted to know about all the data available to us that would have an effect on glucose. We settled on the key areas of data capture: physical activity, carbohydrate levels, blood analysis, stress levels and insulin. This helped us begin to shape customer journeys, the service ecosystem and put together storyboards of how a user would experience this service concept in their everyday life.
We hope we could help in three key ways:
To learn: The goal is to help to manage uncertainty in a diabetic’s daily life. It will help see correlations between the cause (activity, meals, insulin etc.) and the effect on blood glucose levels and identify historical patterns so you’re better prepared for the future.
To act: Having quick access to the information you need at the right time. The information needs to be relevant and meaningful for the user. You shouldn’t have to be a data scientist to understand how to make use of it.
To predict: The Fjord Fido concept currently hopes to make use of all the historical data it captures to plan for future activities – like going on a bike ride, spending the day in the office or heading out for a meal. Not only this, but it is expected that it can feed in calendar events like birthday parties and environmental factors like air temperature so the users can better understand their own situation.
This is still a high-level concept of a possible application. The current project’s final stage will be to design, with the aim of producing a “proof of concept prototype” – a basic but accurate representation of the final platform to show that it was a viable design.