Behaviour Change Apps – a look under the hood:
Developing ways to support decisions from both clinicians and patients alike, have been the focus of more recent value-based medicine reform in healthcare. Involving the patient enables the 3-way healthcare governance triangle that includes the doctor, healthcare organization and the most important participant: the patient.
Ground level development using sophisticated ML (Machine Learning) tools within information systems, and especially within mobile apps has been among the main targets for many healthcare organizations and government healthcare initiatives as we’ve also already discussed, here on Salus digital.
An example of the application of ML tools and artificial intelligence (AI), includes work that has been going into a soon-to-be-launched Beta version of a mobile health app from a new and exciting Swedish Start-up, called: “HealthiHabits” for whom I’ve had the pleasure of working.
There are many ML-based AI driven tools and decision support systems in other industries: Spotify, Google, Facebook, etc. have all developed their own highly coveted algorithms. In healthcare, such tools have been used for predicting disease, adverse drug events and more.
HealthiHabits is one of the few Start-up companies who have been focusing on applying ML tools to sustain and support behavior change management – another subject discussed very recently – where such support tools require a number of working parts in order to deliver a beneficial and sustainable effect on changing behavior.
This is where the AI comes into place by providing personalized, precise options at the point of need by finely integrating user input, social connections and clever recommendations within a GIS (Geographical Information System) to help support the choices that the users of the app have to make in the day-to-day life of a chronically ill patient such as diabetics.
HealthiHabits’ CEO and founder, Christian Guttmann is placed squarely in the middle of the AI which drives the innovative mobile app by having a Ph.D. in Computer Science and Software Engineering from Monash University and 20 years’ healthcare experience including time at IBM Research, leading innovation and research projects in AI, machine learning, and big data.
He describes his personal motivation for developing the HealthiHabits mobile health app:
“Moving into the area of digital health to battle the tsunami of chronic conditions is one of the most rewarding experiences of my career.”
The app targets diabetic and pre-diabetic patients to begin with, to then be rolled out to a wider audience in the future and is described as:
“A people-to-people discovery platform that finds personalized healthy behaviors for you, and achieves a sustainable lifestyle through instant and personalized support… A novel digital patient-to-patient app that makes your life easier and to take control of daily situations around food, exercise, stress, and medical guidelines.”
The major function of ML tools within the AI scope is to learn from data, thus inviting users to furnish the HealthiHabits app with their relevant needs, enables this and gives power to sufferers of a chronic illness such as diabetes to help support the considerable burden on their lives all in one place and by using technology they already have or can easily acquire.
In terms of other support tools for chronic diseases such as diabetes, as mentioned in a previous article, Omada Health provide healthcare behavior change support as demonstrated by their move into B2C by using real-life behavior change coaching rolled out to Medicaid patients. Whilst this is an appropriate step by the American Wellness company, it is not a very practical approach in terms of cost and maintenance overall, as coaches have to be employed to work around the clock and restricts the geographical benefits to a smaller area. By internalizing this process into an app and using AI to drive the coaching, HealthiHabits solves that part of the problem.
Another company – one which is also Sweden-based – is LifeSum which rolls out a similar service as HealthiHabits to the general population to help support healthy behaviors and to those wanting a tool to help track their exercise routines, log meals, etc. They provide alerts as reminders and a way to connect to a user’s already established network of friends – which is a great way to motivate the otherwise healthy individual. However, their app does not include the social connection in quite the same way as HealthiHabits – which allows for the addition of localized support/recommendations from other users with similar needs who are not necessarily already connected to them, thus expanding their network beyond their friendships and towards a virtual support group of members who know just what they are going through.