DiaFit: The Development of a Smart App for Patients with Type 2 Diabetes and Obesity

Abstract

Background Optimal management of chronic diseases, such as type 2 diabetes (T2D) and obesity, requires patient-provider communication and proactive self-management from the patient. Mobile apps could be an effective strategy for improving patient-provider communication and provide resources for self-management to patients themselves. Objective The objective of this paper is to describe the development of a mobile tool for patients with T2D and obesity that utilizes an integrative approach to facilitate patient-centered app development, with patient and physician interfaces. Our implementation strategy focused on the building of a multidisciplinary team to create a user-friendly and evidence-based app, to be used by patients in a home setting or at the point-of-care. Methods We present the iterative design, development, and testing of DiaFit, an app designed to improve the self-management of T2D and obesity, using an adapted Agile approach to software implementation. The production team consisted of experts in mobile health, nutrition sciences, and obesity; software engineers; and clinicians. Additionally, the team included citizen scientists and clinicians who acted as the de facto software clients for DiaFit and therefore interacted with the production team throughout the entire app creation, from design to testing. Results DiaFit (version 1.0) is an open-source, inclusive iOS app that incorporates nutrition data, physical activity data, and medication and glucose values, as well as patient-reported outcomes. DiaFit supports the uploading of data from sensory devices via Bluetooth for physical activity (iOS step counts, FitBit, Apple watch) and glucose monitoring (iHealth glucose meter). The app provides summary statistics and graphics for step counts, dietary information, and glucose values that can be used by patients and their providers to make informed health decisions. The DiaFit iOS app was developed in Swift (version 2.2) with a Web back-end deployed on the Health Insurance Portability and Accountability Act compliant-ready Amazon Web Services cloud computing platform. DiaFit is publicly available on GitHub to the diabetes community at large, under the GNU General Public License agreement. Conclusions Given the proliferation of health-related apps available to health consumers, it is essential to ensure that apps are evidence-based and user-oriented, with specific health conditions in mind. To this end, we have used a software development approach focusing on community and clinical engagement to create DiaFit, an app that assists patients with T2D and obesity to better manage their health through active communication with their providers and proactive self-management of their diseases.

Mobile phone applications and their use in the self-management of Type 2 Diabetes Mellitus: a qualitative study among app users and non-app users

“…Recent data from an Australian qualitative study demonstrated that people with T2DM would prefer an app to address the practical aspects of diabetes self-management and to improve, and reduce the cognitive burden of self-management [17]. Further studies using focus groups for app development have highlighted the importance of blood glucose monitoring, dietary tracking, education, interactive content, peer support and realistic goal setting [19–22]. Despite this, the uptake of apps usage to support diabetes self-management remains low, [12].…”

Mobile App for Simplifying Life With Diabetes: Technical Description and Usability Study of GlucoMan

“…For example, the app mySugr allows a user to document blood sugar and other values uploaded from measurement systems [7]. DiaFit [8] supports uploading data from gadgets such as Apple Watch for fitness activity and glucose monitoring. Lithgow et al [9] claim that existing apps often do not support synchronization with a glucometer, although this feature is desired by patients.…”

Sleep Tracking and Exercise in Patients With Type 2 Diabetes Mellitus (Step-D): Pilot Study to Determine Correlations Between Fitbit Data and Patient-Reported Outcomes

“…Constant communication and encouragement through personalized messages has been shown to result in higher physical activity and reduced HbA 1c levels, as compared with patients who did not receive such messages [ 39 , 40 ]. Mobile apps such as DiaFit or MyCarolinas Tracker, which integrate physical activity, glucose level, nutrition, and medication data for easy review by health care providers, can also be used to communicate with patients [ 41 , 42 ]. In future, such personalized and secure communication between patients and health care providers could decrease the current diabetes epidemic.…”