Healthcare apps are being seen as a novel way of helping people with self-management of their medical conditions, and more than 1100 smartphone apps for diabetes care have now been identified (Garabedian et al, 2015). This is reflected by the three publications regarding apps summarised in these pages.
The scale of the challenge for healthcare professionals trying to assess what apps are available and how useful and reliable they are, in order to advise interested patients appropriately, is emphasised by the analysis performed by Basilico and colleagues. Searching Apple’s US App store with the keyword diabetes returned 952 results! Of these, 67 apps were to support diabetes self-management. All of the latter had a glucose log, but 88% of them required the user to input the data manually. Medication and nutrition logs were common features, but advanced features such as a bolus calculator (present in 17% of apps) were rare.
Another recent publication has highlighted that app-based bolus calculators may have potentially flawed algorithms underpinning the bolus doses recommended (Huckvale et al, 2015). In their paper, Basilico and colleagues focussed on how trustworthy the apps are, describing a “Pictorial Identification Schema” that users could complete to report how useful and reliable they found an app. Such a review system is a more advanced version of rating systems commonly used for apps and other online services, such as TripAdvisor. However, the authors acknowledge that an app rating system from a reputable healthcare body such as NICE or Diabetes UK would be the preferred way of flagging up which apps are likely to be most useful. The best apps are likely to be those that minimise data input and so capture glucose readings directly from a meter, record activity data using in-built accelerometers or other exercise logging apps and, perhaps one day, determining nutritional data from meal screenshots.
De Ridder and colleagues reviewed incentive-driven mobile health technology used in diabetes management. Nineteen publications involved the use of apps, and these were the dominant technology in publications from 2014, the last year considered in the review. The incentives included goal reminders; alerts when a health parameter was out of range; feedback where the user is provided with automated or manually inputted advice on the basis of the data provided; discussion with peers; education, where information is provided to the user on the basis of the inputted data or issues identified; financial, where rewards such as iTunes vouchers are offered when targets are achieved; and “gamification”, in which social competition is used to make self-management more fun. The latter is an increasingly common phenomenon and appears to be particularly attractive to adolescents and young adults with diabetes. Older people, in contrast, are more likely to favour simpler incentive-driven technologies such as SMS messaging – although our experience with using diabetes technologies such as pump therapy and continuous glucose monitoring is a caution against such age-based stereotyping!
We are left with an ever-increasing number of apps which people with diabetes may access to support them in self-management, but with little information as to the utility or reliability of a particular app, and with limited evidence that such interventions are effective in motivating or improving outcomes for users. However, it is encouraging that steps are being taken to try and assist users by providing app evaluation from other users. In describing their app to support women with gestational diabetes, Jo and Park provide an alternative means by which we might be able to evaluate individual apps.
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