RAD-PD: Registry for the advancement of DBS in Parkinson's disease

Objective: To describe a deep brain stimulation (DBS) registry proposal for the purpose of improving DBS therapy and outcomes for Parkinson's disease (PD) patients. Background: Although considerable evidence favors DBS over continued best medical management when bothersome motor complications are present in PD, variability in outcomes are not well understood, best practices are not well-defined, and prospective, long-term health economics data and comparisons of treatment techniques are lacking. Randomized trials are impractical to investigate these questions. Methods: A survey of potential clinical sites investigated which clinical data are routinely captured. RAD-PD was designed as a quality improvement effort. A large and heterogeneous PD cohort undergoing DBS will be prospectively and comprehensively characterized using a standard assessment battery and image analysis. Clinician-measured and patientreported outcomes and imaging will be gathered from over 1,000 participants at up to 40 clinical sites across 5 years of DBS therapy. Results: Across 25 responding sites, 96% complete an MDS-UPDRS part III, 70-77% complete MDS-UPDRS parts I, II and IV, 91% complete Hoehn and Yahr staging, and 85% complete a MoCA prior to surgery. The majority do not systematically assess non-motor symptoms or impulse control disorders, and only 68% capture the PDQ-39. No respondents assess operative risk or patient satisfaction. A comprehensive set of data elements was devised to be systematically captured and benchmarked for analysis in RAD-PD. Dashboarding to participating sites will enable them to consider implementing changes in therapeutic strategies to improve the quality of DBS care and outcomes for PD patients. Conclusion: RAD-PD is needed to prospectively capture standard and comprehensive assessments in a large PD cohort undergoing DBS, with the primary goal of improving DBS therapy and outcomes. Results will have broad applicability to a range of practice scenarios and patient characteristics and the infrastructure can be applied to other disease states.