Background: The National Institutes of Health Stroke Scale is used globally to rate neurological deficits in patients with acute stroke. Originally designed for research use, the scale uses idiosyncratic scoring rules and requires thorough training for proper use. Currently available training and certification systems are timeworn and limited in the range of demonstrated neurological findings. We aimed to develop a new training and certification method to address the limitations of the prior system.
Methods: We describe a new animated system that uses state-of-the-art digital motion capture, avatar rendering, and digital animation that enables illustration of all possible scale item responses within a training module. For certification, we created 20 unique case vignettes, which can be viewed from many angles allowing better scoring scenario presentation. Training to use the scale via telemedicine was added. Alpha and beta testing was completed to enhance iterative development. From a penultimate version, we measured interrater agreement among 42 pilot users who each viewed 6 cases. After further improvement, we finalized the application and confirmed interrater agreement in a second sample of 365 consecutive, unselected users viewing 3 cases. Clinometric analysis methods followed our prior studies of the scale.
Results: Users agreed the new, animated training module is more engaging and informative than legacy training videos. We compared the new system to the legacy live-video certification system for clinometric reliability. In the confirmatory sample, the intraclass correlation coefficient was 0.979 (97.5% CI, 0.919-0.99). Kappa scores ranged from 0.25 to 0.90 across all 15 scale items. These results are comparable to previous studies.
Conclusions: A new, animated training and certification system showed equivalent clinometric properties to legacy systems, providing a reliable method for National Institutes of Health Stroke Scale training and certification. The new system allows modification and reconfiguration if needed to maintain user interest and case novelty.
Keywords: avatar; certification; humans; motion capture; telemedicine.