Characterizing life events through self-report and wearable data

Healthcare industry stakeholders increasingly expect healthcare data to demonstrate the real-world value of new interventions to support approval, reimbursement, and prescribing decisions. Yet, this value is challenging to demonstrate with today’s siloed data sources. Combining passively collected wearable data and subjective, self-reported feedback helps identify unmet needs, predict who would benefit from intervention, and track the impact of treatments over time.

In this report, we:

• Provide examples of active survey responses combined with passive wearable data collection around a major life event
• Describe how these data detect post-event changes in activity, sleep, and heart rate patterns
• Suggest how these patterns could be used to impact health outcomes

Download the report here.

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