Abstract 19778: Reframing Clinical Neurorehabilitation in Individuals After Stroke Using a Big-Data Approach
Background and Objective: Advances in connected health delivery systems to provide communication rehabilitation have provided a unique opportunity to maximize intervention effectiveness while collecting large sets of data to facilitate clinical decision making. Such data can be vastly insightful to neurorehabilitation in general where the evidence for gains in chronic stroke patients is weak.
Methods: Over a span of 18 months (2013-2014), data was anonymously aggregated and analyzed from over 2,500 patients with post-stroke aphasia. Data was collected using a mobile therapy platform, Constant Therapy. The program was used by patients in the clinic with clinicians, at home as homework, and independently if they were not currently receiving therapy. This program was administered in a uniform way across patients but also individualized for each patient and dynamically adapted to each patient’s progress. Patients who completed between 3 and 1000 treatment sessions of at least 15 items or more were analyzed in a case-mix adjusted way controlling for intensity of practice and initial severity to determine which tasks demonstrated statistically significant improvement.
Results: Our analyses take into account the number of patients who completed a specific task and show a significant change (p-values at least <.05) for either accuracy or latency. Thus, patients (ranging from 10 to over 450 individuals across the 60 different evidence-based tasks in Constant Therapy) were binned in terms of their initial severity on the tasks. For example, patients who initially performed at 70% accuracy or below showed 18% gain in auditory processing, 21% gain in naming, 17% gain in reading, 19% gain in writing, 20% gain in sentence planning, 24% gain in verbal production, 25% gain in attention, 26% gain in visuo-spatial processing, 11% gain in memory and 23% gain in problem solving. The magnitude of improvement on these domains increased with lower initial severity scores.
Conclusion: These results show that all patients, including the most severe, can make progress in their rehabilitation. Analysis of large data sets can be used to inform neurorehabilitation by highlighting therapies that are effective by taking into account etiology and individual performance variability.
- Healthcare delivery systems
- Precision medicine
- Mobile technology
- Rehabilitation post stroke
Author Disclosures: S. Kiran: Research Grant; Significant; NIH/NIDCD. Ownership Interest; Significant; Co-Founder, Constant Therapy. Consultant/Advisory Board; Significant; Constant Therapy Scientific Advisor. M. Advani: Employment; Significant; Constant Therapy. Ownership Interest; Significant; Constant Therapy. J. Godlove: Employment; Significant; Constant Therapy. V. Anantha: Employment; Significant; Constant Therapy. Ownership Interest; Significant; Constant Therapy.
- © 2016 by American Heart Association, Inc.