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Mobile App User Data

Through relevance, personalizing the user experience is a potent amplifier of behavior change, and to personalize you need data about the user. Through personalization you can focus your behavior change initiative on where it matters most for the user and targeted outcomes, increase retention, and especially engagement. The market standard across industries leads users to expect minimal effort to access data, and avoidance of redundant manual data entry at all costs, “If it exists, import it so I don’t have to enter it”. Although much of healthcare data is sensitive and siloed, your users will expect you to make it easy to harness relevant health data, with minimal steps during enrollment and automatically over time. Related to this, you will want to leverage as much accessible, accurate, and timely data as possible in your solution to personalize the user experience, with the goal of increasing the perceived value of your solution (making it almost “human-feeling”), with lower cost automated algorithms and AI to increase margins. Furthermore, recent legislature related to information blocking regulation is giving individuals more authority over their data while lowering the threshold to connect through standardization. When strategizing around user data and considering how to leverage data to change behavior and maintain engagement over time, it can help to consider the following 4 data categories, and how to connect.

#1 EHR Data

Health Records on iPhones, for example, are already available from >800 institutions across 12k locations. FHIR based access to real-time or scheduled aggregated data, provider vs user initiated, and matching processes. Register your app with the EHR to receive an authorization code and client ID to authenticate, then use the FHIR API to request patient data in FHIR format, then parse the data into JSON.

#2 Wearable/Tracker Data

About 25% of people in the US (87M) use smartwatches, 45% wear them regularly, 20% prefer Apple, while 16% prefer Fitbit. If you’re pulling data from any device, using IOS as an example, obtain access to the Apple HealthKit framework, prompt the user for permission to access their health data, then request specific data from HealthKit (heart rate, step count, activity minutes), next parse the data into JSON.

#3 Provider/Coach Entered Data

Telehealth use increased 38X from the pre-COVID-19 baseline, with average visits lasting between 12-15 minutes. It is critical to enable efficient data entry by providers or coaches during synchronous (audio and/or video) or asynchronous (chat) encounters, to collect discrete data that can further personalize the app experience both short and long-term.

#4 User Entered Data

Collect minimal data to facilitate enrollment, then use assessments to collect data to personalize the app experience in the short-term, and enable personalized ongoing engagement that is automated, scalable, but feels human to increased perceived app value, and reduce churn. Keep in mind that In-App surveys have a 9% response rate, while personalized prompted surveys have a 57% response rate among Medical & Fitness apps.


Over the last decade, ImplementHIT has developed behavior change solutions impacting hundreds of thousands of physicians and patients, and the software used in over 2,000 hospitals and clinics throughout North America. Let's work together!

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