Benjamin Y Andrew1, Colleen M Stack2, Julian P Yang2, Jodi A Dodds3. 1. Clinical Research Training Program, Duke University School of Medicine, Durham, North Carolina. 2. Department of Neurology, Duke University School of Medicine, Durham, North Carolina. 3. Department of Neurology, Duke University School of Medicine, Durham, North Carolina. Electronic address: jodi.dodds@duke.edu.
Abstract
OBJECTIVE: This study aimed to evaluate the effect of method and time of system activation on clinical metrics in cases utilizing the Stop Stroke (Pulsara, Inc.) mobile acute stroke care coordination application. METHODS: A retrospective cohort analysis of stroke codes at 12 medical centers using Stop Stroke from March 2013 to May 2016 was performed. Comparison of metrics (door-to-needle time [DTN] and door-to-CT time [DTC], and rate of DTN ≤ 60 minutes [goal DTN]) was performed between subgroups based on method (emergency medical service [EMS] versus emergency department [ED]) and time of activation. Effects were adjusted for confounders (age, sex, National Institutes of Health Stroke Scale [NIHSS] score) using multiple linear and logistic regression. RESULTS: The final dataset included 2589 cases. Cases activated by EMS were more severe (median NIHSS score 8 versus 4, P < .0001) and more likely to receive recombinant tissue plasminogen activator (20% versus 12%, P < .0001) than those with ED activation. After adjustment, cases with EMS activation had shorter DTC (6.1 minutes shorter, 95% CI [-10.3, -2]) and DTN (12.8 minutes shorter, 95% CI [-21, -4.6]) and were more likely to meet goal DTN (OR 1.83, 95% CI [1.1, 3]). Cases between 1200 and 1800 had longer DTC (7.7 minutes longer, 95% CI [2.4, 13]) and DTN (21.1 minutes longer, 95% CI [9.3, 33]), and reduced rate of goal DTN (OR .3, 95% CI [.15, .61]) compared to those between 0000 and 0600. CONCLUSIONS: Incorporating real-time prehospital data obtained via smartphone technology provides unique insight into acute stroke codes. Activation of mobile electronic stroke coordination in the field appears to promote a more expedited and successful care process.
OBJECTIVE: This study aimed to evaluate the effect of method and time of system activation on clinical metrics in cases utilizing the Stop Stroke (Pulsara, Inc.) mobile acute stroke care coordination application. METHODS: A retrospective cohort analysis of stroke codes at 12 medical centers using Stop Stroke from March 2013 to May 2016 was performed. Comparison of metrics (door-to-needle time [DTN] and door-to-CT time [DTC], and rate of DTN ≤ 60 minutes [goal DTN]) was performed between subgroups based on method (emergency medical service [EMS] versus emergency department [ED]) and time of activation. Effects were adjusted for confounders (age, sex, National Institutes of Health Stroke Scale [NIHSS] score) using multiple linear and logistic regression. RESULTS: The final dataset included 2589 cases. Cases activated by EMS were more severe (median NIHSS score 8 versus 4, P < .0001) and more likely to receive recombinant tissue plasminogen activator (20% versus 12%, P < .0001) than those with ED activation. After adjustment, cases with EMS activation had shorter DTC (6.1 minutes shorter, 95% CI [-10.3, -2]) and DTN (12.8 minutes shorter, 95% CI [-21, -4.6]) and were more likely to meet goal DTN (OR 1.83, 95% CI [1.1, 3]). Cases between 1200 and 1800 had longer DTC (7.7 minutes longer, 95% CI [2.4, 13]) and DTN (21.1 minutes longer, 95% CI [9.3, 33]), and reduced rate of goal DTN (OR .3, 95% CI [.15, .61]) compared to those between 0000 and 0600. CONCLUSIONS: Incorporating real-time prehospital data obtained via smartphone technology provides unique insight into acute stroke codes. Activation of mobile electronic stroke coordination in the field appears to promote a more expedited and successful care process.
Authors: Chris F Bladin; Kathleen L Bagot; Michelle Vu; Joosup Kim; Stephen Bernard; Karen Smith; Grant Hocking; Tessa Coupland; Debra Pearce; Diane Badcock; Marc Budge; Voltaire Nadurata; Wayne Pearce; Howard Hall; Ben Kelly; Angie Spencer; Pauline Chapman; Ernesto Oqueli; Ramesh Sahathevan; Thomas Kraemer; Casey Hair; Dion Stub; Dominique A Cadilhac Journal: BMJ Open Date: 2022-07-18 Impact factor: 3.006
Authors: Hernán Bayona; Brenda Ropero; Antonio José Salazar; Juan Camilo Pérez; Manuel Felipe Granja; Carlos Fernando Martínez; Juan Nicolás Useche Journal: J Med Internet Res Date: 2020-07-27 Impact factor: 5.428