The objective was to use continuously collected consumer wearable data in order to differentiate patients with MS from those in a non-MS control group. The intent was that this data could help determine mobility, which might serve as a proxy for both disease state and progression in patients living with MS.
In partnership with a top 10 pharmaceutical company, Evidation used administrative medical claims data to identify ~500 individuals with MS and ~1500 individuals without MS to partake in this study. Those without MS met age, sex, and geography controls, and all participants met weartime requirements, ensuring data continuity and quality. Throughout the duration of the study, researchers computed daily summaries of both step and sleep data recorded by the minute via participants’ wearables. Combining this data with medical claims and demographics data, experts could see notable differences between MS and non-MS individuals. In addition, they were able to identify flare-up events in patients with MS, paving the way for remote monitoring and management.
The findings suggest that data collected from consumer wearables, or person-generated health data, has the potential to:
• Identify patients living with MS
• Passively assess the quality of life in patients living with MS
• Document meaningful events
Lower mobility is significantly associated with increased pain
This finding indicates that data from passive trackers may be used to build an index of pain symptoms over time. RWD such as this allows experts to develop clinical cohorts differentiated by comorbidity level, medical utilization, and pain symptoms.
When controlling for symptoms, patients who have switched DMTs receive neuro MRIs 1.5x more often than single-DMT patients
This suggests that some single-DMT patients appear to be clinically monitored at suboptimal levels, potentially leading to inferior medication regimens.
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