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Emily Seto Part 2, mHealth Apps

In part 2 of this Exclusive Interview, Dr. Emily Seto talks with Diabetes in Control Publisher Steve Freed during the ADA meeting in San Diego, CA about the apps in development and their impact on improving diabetes management.

Emily Seto, PhD, PEM is an Assistant Professor and Lead for the health informatics programs at the Institute of Health Policy, Management and Evaluation at the University of Toronto.

Transcript of this video segment:

Steve Freed: How long have you been doing this?

Emily Seto: Looking at mHealth, about 10 years now we’ve been doing this.

Steve Freed: Ok so in those 10 years, what have you developed as far as apps go?

Emily Seto: We have a number of apps, I’ll just maybe mention one or two. The first is a platform for chronic disease management that we called, Medly. The idea here is that it can be used for single chronic conditions or for people with multiple chronic conditions as well. It’s a telemonitoring system so patients at home take the required measurements that they normally would do. So maybe blood sugars for diabetes, or if you have heart failure, weight and blood pressure. Then also, any symptoms you may have. So this is all automated through Bluetooth enabled devices and it automatically transfers to the cell phone, which acts as “the hub,” and then from there, it gets sent to data servers where we have algorithms that we spent a lot of time working on with clinicians to create an algorithm so that, in real time, the patients get self-care messages back through the app. Then the care providers can get alerted at the earliest signs that the patient is getting worse and then they could intervene and close that loop and provide, for example, education over the phone or even changing medication. Really, the idea is to keep patients from going into hospitals over and over again.

Steve Freed: So what you do, it’s not just about diabetes?

Emily Seto: Oh no, [although] we also have apps for diabetes as well. One is called Bant. It is a free app that’s available on the iTunes store right now. We’ve created a number of different apps, some for diabetes and some for other chronic diseases as well.

Steve Freed: And do you do studies with these apps to see if they actually improve?

Emily Seto: Yes, absolutely. So after we have created them, we always start out with some pilot trials to see how it kind of fits into the healthcare system. We iron it out to make sure that everything is in place before we do larger trials such as randomized control trials, and then we make sure that it’s ready for deployment. Of course our end goal is to deploy it out for real-use by patients and clinicians.

Steve Freed: So because A1C is the gold standard, have you done studies to see if it lowers A1C? If it does lower A1C, it is a good program. If it doesn’t change, you throw it away, and start all over again.

Emily Seto: Well, I hope that is not the case! (Laughs) Actually showing A1C change can be quite difficult and you need a lot of patients to do that. We have been doing studies, for sure, looking at A1Cs. We have also been looking to see if your blood sugar readings are in range and also how many times, for example, do you take your blood sugar readings if you are a type 1 diabetic. Also looking at, for type 2 diabetes, whether or not you are following good lifestyle changes, right? So, are you eating properly, are you exercising properly, and then kind of correlating all of that information so the patient can actually have control over what they’re doing and understand how it relates to the diabetes. So I think there’s a lot more to it than just hemoglobin A1C values, but certainly, we have done studies looking at that as well.

Steve Freed: So for mHealth, do you try to work with apps for medical professionals or patients, or both?

Emily Seto: Both. So it depends on the type of app. Sometimes if you’re looking at the diabetes app, maybe it is purely for self-care and then the patients is using it. We also have apps for diabetes that connect patients to their clinicians and again, we try not to give the clinician reams of data to look at because they are extremely busy. So we definitely want to make sure their time is utilized properly. Through smart algorithms, we can alert them when they actually need to be intervening to help their patients. So if patients’ blood sugars are completely out-of-whack for a trending, for example, or hypoglycemic, then we could alert the appropriate care providers to intervene at that time.

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