I have ideas for two fantasy QS systems, one for the body and one that is not. Both of these devices are aimed to help in the treatment of my type-1 diabetes.

The device for my body would be integrated into a watch. Instead of second, minute and hour hands, it would have three zones that correlate with today, this week and this month. Instead of presenting the time, it would present a color-coded scale showing whether blood sugar range is good or bad.

The blood glucose data could either be generated by the watch (a device was developed called the Glucowatch, but failed to take off) or a separate glucose monitor that transmits data to the watch. But the uniqueness and value of the watch would come not from generating data but by visualizing it in a simple, easily accessible way. It allows the patient to see the “bigger picture” instead of becoming obsessed with individual readings. With a chronic disease like diabetes, overall health is determined by success in achieving good long-term control.

The second fantasy system I would design would create an easier way to gather data from a variety of devices. This is my current collection of devices and the cables or receivers needed to extract data.

A PC with an internet connection and separate software with separate logins are needed to aggregate the data. I imagine a system that would have a simpler user interface. This machine would require a patient simply to put their finger on a finger print scanner.

The machine would recognize the person and absorb all the data from the requisite devices, working across all manufacturer’s lines of products. The data would then be sent over a mobile phone network to a central server. The data visualization and analysis could then be accessed in other ways, either on a phone or on a browser. But the user experience would be so simple that patients could transmit their data daily (before they went to bed perhaps). A central server could then respond when unusual or dangerous trends were spotted.

I was lucky enough to attend a QS meeting at ITP this summer. It was great to experience a few of the speakers, including the very powerful presentation made by Ari Meisel. I can relate to his experience because I am also a patient, be it with a different condition. At the event, he told an extremely personal story and certainly had a memorable impact.

Yet in choosing the two videos to discuss here, I went in a different direction. I chose to focus on two speakers that I found interesting because of the combined simplicity and power of their applications. I find this compelling from my own experience in researching and prototyping for an application called Databetes. I hope in the future that this program can help me and the rest of the diabetes patient community.

Managing diabetes is a rather complex task, especially for a type 1 patient like myself. I use three medical devices on a daily basis: an insulin pump, a continuous glucose monitor (CGM) and a standard blood glucose monitor. These are complicated devices, each with a different manufacturer, each with a different software and hardware interfaces, each with different requirements for getting the data off the device. Yet even if you extract the combined 300+ data points per day from these devices, you still only have blood glucose and medication data. Any information on food/carbohydrates, exercise, mood, etc. must be aggregated through a different method and device. The complexity of the user experience is frustrating even for me, a person dedicated to heavy monitoring. I find it quite easy to understand how patients might not stay current in their data aggregation. I also find it frustrating that I need to keep all these devices on me at all times. My CGM, for example, needs to stay within 5 feet of me or the receiver does not pick up the signal from the transmitter on my belly.

Hence my positive reaction to Ted Punt’s Contactless monitoring system.

QS – Ted Punt – Contactless monitoring systems

His products provides wireless non invasive monitoring with radar technology. I think this is terrific for a few different reasons. First, one can count on there being a complete data set regardless of time or other complicating factors that would otherwise distract from manual entry. Plus, the fact that this technology can work from a distance of up to 10 meters means that there is one less thing to carry around. I highly suspect that with just a few sensors (one at our work desk, one in our car, one in the bedroom, one in the kitchen), we could catch a high percentage of our daily readings. To highlight my focus on user experience, this would also require us to do close to anything. Hard to argue with that.

This simplicity and low barrier to success is also a design approach by Victor van Doorn at ReplyMyDay.com

Victor van Doorn – Replay My Day

I think his automatic diary works for a few reasons. First off, beyond data, he has created a system for telling a story with a cinematic flair. Humans love stories and find them compelling, dare I say more compelling than pie charts and graphs. Second, the system is effortlessly simple. Even well intended self trackers still get overwhelmed by work deadlines and the rest of life. This system is also compelling because it knows its limit, allowing for the import of data already being recorded elsewhere (twitter feeds, for example). At the same time it is also customizable, allowing users to create new categories of readings and thus greatly expanding the range of data that can be tagged. Finally, from the presentation I appreciate that the creator of the app is having fun with it. I am sure this attitude caries over into the user experience, making people interested in using it more.

In general, I think these technologies will have a positive effect on the QS movement because the services adjust to the normal lives of users instead of the other way around. I think this will result in more data being aggregated and more lessons learned.