Background: Reperfusion is the most effective acute treatment for ischemic stroke within a narrow therapeutic time window. Ambulance-based telestroke is a novel way to improve stroke diagnosis and timeliness of treatment. This study aims to (1) assess the usability of our ambulance-based telestroke platform and (2) identify strengths and limitations of the system from the user's perspective. Materials and Methods: An ambulance was equipped with a mobile telemedicine system to perform remote stroke assessments. Scripted scenarios were performed by actors during transport and evaluated by physicians using the National Institutes of Health Stroke Scale (NIHSS). Scores obtained during transport were compared with original scripted NIHSS scores. Participants completed the System Usability Scale (SUS), NASA Task Load Index (NASA TLX), audio/video quality scale, and a modified Acceptability of Technology survey to assess perceptions and usability. In addition, interviews were conducted to evaluate user's experience. Descriptive analysis was used for all surveys. Weighted kappa statistics was used to compare the agreement in NIHSS scores. Results: Ninety-one percent (59/65) of mobile scenarios were completed. Median completion time was 9 min (range 4-17 min). There was moderate inter-rater agreement (weighted kappa = 0.46 [95% confidence interval 0.33-0.60, p = 0.0018]) among mobile and original scripted scenarios. The mean SUS score was 68.8 (standard deviation = 15.9). There was variability between usability score and formative feedback among all end-users in the areas of usability issues (i.e., audibility and equipment stability) and safety. Conclusion: Before implementation of a mobile prehospital telestroke program, the use of combined clinical simulation and Plan-Do-Study-Act methodology can improve the quality and optimization of the telemedicine system.
Background: Reperfusion is the most effective acute treatment for ischemic stroke within a narrow therapeutic time window. Ambulance-based telestroke is a novel way to improve stroke diagnosis and timeliness of treatment. This study aims to (1) assess the usability of our ambulance-based telestroke platform and (2) identify strengths and limitations of the system from the user's perspective. Materials and Methods: An ambulance was equipped with a mobile telemedicine system to perform remote stroke assessments. Scripted scenarios were performed by actors during transport and evaluated by physicians using the National Institutes of Health Stroke Scale (NIHSS). Scores obtained during transport were compared with original scripted NIHSS scores. Participants completed the System Usability Scale (SUS), NASA Task Load Index (NASA TLX), audio/video quality scale, and a modified Acceptability of Technology survey to assess perceptions and usability. In addition, interviews were conducted to evaluate user's experience. Descriptive analysis was used for all surveys. Weighted kappa statistics was used to compare the agreement in NIHSS scores. Results: Ninety-one percent (59/65) of mobile scenarios were completed. Median completion time was 9 min (range 4-17 min). There was moderate inter-rater agreement (weighted kappa = 0.46 [95% confidence interval 0.33-0.60, p = 0.0018]) among mobile and original scripted scenarios. The mean SUS score was 68.8 (standard deviation = 15.9). There was variability between usability score and formative feedback among all end-users in the areas of usability issues (i.e., audibility and equipment stability) and safety. Conclusion: Before implementation of a mobile prehospital telestroke program, the use of combined clinical simulation and Plan-Do-Study-Act methodology can improve the quality and optimization of the telemedicine system.
Authors: Jason M Lippman; Sherita N Chapman Smith; Timothy L McMurry; Zachary G Sutton; Brian S Gunnell; Jack Cote; Debra G Perina; David C Cattell-Gordon; Karen S Rheuban; Nina J Solenski; Bradford B Worrall; Andrew M Southerland Journal: Telemed J E Health Date: 2015-11-24 Impact factor: 3.536
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Authors: Sherita N Chapman Smith; Prasanthi Govindarajan; Matthew M Padrick; Jason M Lippman; Timothy L McMurry; Brian L Resler; Kevin Keenan; Brian S Gunnell; Prachi Mehndiratta; Christina Y Chee; Elizabeth A Cahill; Cameron Dietiker; David C Cattell-Gordon; Wade S Smith; Debra G Perina; Nina J Solenski; Bradford B Worrall; Andrew M Southerland Journal: Neurology Date: 2016-06-08 Impact factor: 9.910