Conformity of Diabetes Mobile apps with the Chronic Care Model

Abstract

BackgroundDespite the growing use of mobile applications (apps) for chronic disease management, the evidence on the effectiveness of this technology on clinical and behavioural outcomes of the patients is scant. Many studies highlight the importance of the theoretical foundations of mobile-based interventions. One of the most widely accepted models for the management of chronic diseases, such as diabetes, is the Chronic Care Model (CCM). In this study, we investigated the conformity of the selected diabetes mobile apps with CCM.MethodWe searched online journal databases related to diabetes mobile apps to find common features. Then considering the components of the CCM as a reference model, features of some popular and top-ranking apps were compared with CCM.ResultsAmong 23 studied apps, 34 per cent of them had medium conformity and 66 per cent of these apps were in weak conformity. The self-management support component is covered by 100 per cent of them. Ninety-five per cent of apps have covered the proactive follow-up component.ConclusionsApp conformance with CCM is generally weak. App developers are recommended to give greater consideration to established theoretical models in their design and implementation.

What’s the Name of the Game? The Impact of eHealth on Productive Interactions in Chronic Care Management

“…Previous research showed promising results of eHealth interventions in terms of their effects on clinical outcomes and diabetes self-management [17]. Integrated, patientcentered care based on the CCM has been identified as very cost-effective for diabetes patients [18], but the conformity of mobile eHealth applications to the components of the CCM is generally weak [19]. Interventions appear to be most effective when an interactive format is used, such as text messaging [20].…”

“…Interventions appear to be most effective when an interactive format is used, such as text messaging [20]. Yet, many eHealth applications have just focused on some essential functionalities to monitor health parameters, such as tracking of blood pressure, blood glucose, weight, and activity [19,21]. There has been little focus on how both patients and providers can use patient-generated data together [22], and features enabling productive interactions between patients and staff are often lacking [23].…”