In our digital age, mobile phone users can access a wide variety of apps to help manage their health, but the personal health data that users generate often exist in what Dr. Michalak calls ‘islands of data’.
“Think about yourself. If you’re an app user you might have a mindfulness app that you’re using, a sleep app, or some type of social activity [app],” Dr. Michalak explains. “But we’re not doing a good enough job yet at pulling together those pieces of data.”
Her project seeks to centralize user data, which means that it could be used to generate more meaningful insights into how the changes a user makes might impact different parts of their life.
The app will harness block chain technology, which provides greater security for sensitive information. It will also give users authority to decide whether they’d like to share data with their healthcare team, researchers, or other people in their life – and revoke access for any party, at any time.
Every stage of this project is being driven with users’ worldviews in mind. Approximately one third of the team – including project Co-lead Dr. Steven Barnes – live with bipolar disorder, which importantly brings a diverse range of expertise and lived experience to the work. Further, a key part of the design process has involved mapping out the many types of users that may rely on the app’s services.
Considering the user journey helps the team think about how they can develop personalized content. For example, Dr. Michalak explains that a woman living with bipolar disorder may be at an increased risk for a mood episode in the postpartum period. Thinking about this unique need means that they can build an app responsive to a user’s life changes.
The team will use artificial intelligence and machine-learning technologies to analyze any data that users opt to share through the app. Dr. Michalak hopes that in future, any patterns that emerge through data analysis will provide a new way to predict quality of life.
“With this platform and this type of data I would like to be able to say ‘Based on what we know from lots of other people like you using machine learning techniques, these are the things that you can do that might make a difference to outcomes for you.’”
To learn more about Dr. Michalak’s work, visit the CREST.BD site.