Objective: To evaluate whether continuous remote monitoring can identify dyskinesia at scale, detect between-visit worsening, and support more efficient patient-clinician communication about management.

Background: Dyskinesia fluctuates and is difficult to reconstruct during episodic visits. Remote monitoring that combines wearable data with targeted screeners may better quantify burden and support earlier management discussions.

Method: The Dyskinesia Insight Network is an ongoing remote observational program embedded in StrivePD, a broader digital Parkinson disease platform for longitudinal symptom tracking and wearable monitoring that was used to identify and recruit patients at scale, deploy routine dyskinesia screeners, integrate passive wearable and patient-reported data, and generate longitudinal reports to support more efficient patient-clinician discussions between visits. Adults with Parkinson’s disease on levodopa for more than 2 years and dyskinesia identified by clinicians or platform screening were monitored with consumer smartwatch and smartphone data, medication logs, symptoms, and serial remote questionnaires including the Unified Dyskinesia Rating Scale Part 1B. We compared referral-source characteristics and longitudinal dyskinesia trajectories.

Results: Eighty-two participants were enrolled against a target of 80; 59 were identified through platform screening and 23 by clinician referral. All surveyed participants reported prior clinician recognition of dyskinesia, and platform-identified and clinician-referred participants had similar dyskinesia profiles, supporting remote identification beyond specialty-center referral alone. Most participants reported bothersome dyskinesia, and serial remote UDysRS Part 1B assessments showed worsening more often in the platform-identified cohort than the clinician-referred cohort (42% vs 20%), with worsening greater than 5 points in 18% vs 0%. This suggests unmet need in patients identified outside traditional movement-disorders referral workflows.

Conclusion: Continuous remote monitoring identified a geographically distributed cohort with clinically recognized dyskinesia and detected worsening between visits. These findings support digital monitoring as a scalable workflow to identify the right patients, reveal unmet need, and strengthen patient-clinician communication around dyskinesia recognition and management.

« Back to 2026 International Congress

MDS Abstracts - https://www.mdsabstracts.org/abstract/a-large-scale-digital-parkinson-disease-platform-matches-clinician-identification-of-dyskinesia-and-uncovers-unmet-need-between-visits/