Managing life with Diabetes through AI/ML.

Stakeholders wanted our blood-glucose monitors to be useful, but patients had piles of BGMs in kitchen drawers and weren't looking for a new one.

Project Problem Statement: Could we create a digital coaching product central to a behavior-change service, and could that service truly improve a person's ability to solve problems and make good decisions?

The business goal

We needed to find a way to use data from an subcutaneous blood sugar sensor to help people with diabetes understand their blood-glucose levels and use that information in concert with our diabetes products to take care of themselves.

The team

Me, a UI designer, a small research agency, a behavioral scientist, a diabetes nurse, a content strategist, an AI researcher, an AI developer, and the product owner.

My role

Our insights

Among people with diabetes whose condition was wildly out of control, we found that self-managing through tools, no mater how easy to use, didn't address the real issues.

These patients needed help with the behaviors that led to their condition, and that help needed to be empathetic, simple to use, and specific to the moments that were most challenging for the individual.

Our hypotheses

If we could break the coaching process down to discrete challenges tailored to someone's immediate needs and abilities, then we could turn incremental changes into meaningful improvements to their health over time.

A service based in our patented behavioral science interventions primarily focused on problem solving and action planning, coupled with high-quality educational content pertinent to their data could move the needle with people having the most trouble.

What we did

First we needed to better understand the truth of life with diabetes. What were the challenges facing people with wildly out of control glycated haemoglobin levels.

Our subject matter experts felt that the only way to really make a difference would be to have a personal chef, a nurse, a personal trainer, and a life coach follow patients around 24 hours a day.

Our team had extensive experience talking to people with type-2 diabetes and was able to map out their typical journey. This allowed us to target users who we could impact the most, and who's needs would extend to the larger population.

Once we had a handle on the ins and outs of life with diabetes for our target users, we were able to identify what we needed our service to do.

We were then able to identify the minimum viable service and which components could be digital.

We then conducted research…

and co-created prototypes with patients.

Once we had a handle on where people were struggling, we jumped into converting the science into a digital user experience.

We figured out what data would provide the greatest most important insights…

we established what content would have the greatest impact on user progress…

and we created a script for our pilot MVP.

What we delivered

Then we designed an interactive prototype that we tested with our users with the help of a small research agency.