Actionable Wearables Data for the Neurology Clinic: A Proof-of-Concept Tool

Abstract

Objective: Wearable devices can monitor key health and fitness domains. In multiple sclerosis (MS), monitoring step count and sleep is feasible, valid, and offers a holistic glimpse of patient functioning and worsening. However, data generated from wearables are typically unavailable at the point of care. We describe the design, development, and evaluation of a proof-of-concept tool that delivers patient-generated wearables data in accessible, interpretable, and actionable formats to an outpatient Neurology clinic.

Methods: Through a process of human-centered design, stakeholders were engaged to create a technological solution to access and display wearables data via a launch from the electronic health record (EHR). Designs were informed by patient-centered observational research and clinician interviews to ensure user alignment and validity. Qualitative and quantitative evaluations (Health ITUES framework) as well as live observations of use assessed functionality, ease of use, and clinical integration.

Results: During development, 25 clinicians and four engineers across eight clinical settings provided feedback. The proof-of-concept wearable selected was Fitbit, which was connected via a custom solution to the EHR dashboard (BRIDGE). In the final validation, clinician satisfaction was high: mean scores > 4/5 for all performance and ease of use components. Live visualizations during clinical encounters highlighted a range of potential uses: detecting progression by step count, setting motivating and realistic activity goals despite limitations, referring to rehabilitation after activity drops, and measuring effects of interventions on sleep quality.

Interpretation: Integrating wearables data into a clinical workflow for neurology is feasible and highlights novel areas to support shared decision-making and data-driven, personalized care.

Keywords: fitbit; sleep; steps/activity; visualizations; wearables.