mStroke: “Mobile Stroke”—Improving Acute Stroke Care with Smartphone Technology

Benjamin Y. Andrew, Colleen M. Stack, Julian P. Yang, Jodi A. Dodds

Research output: Contribution to journalArticle

1 Citation (Scopus)

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.

Original languageEnglish (US)
Pages (from-to)1449-1456
Number of pages8
JournalJournal of Stroke and Cerebrovascular Diseases
Volume26
Issue number7
DOIs
StatePublished - Jul 1 2017

Fingerprint

Stroke
Technology
Needles
Emergency Medical Services
National Institutes of Health (U.S.)
Smartphone
Hospital Emergency Service
Tissue Plasminogen Activator
Linear Models
Cohort Studies
Logistic Models

Keywords

  • acute care coordination
  • emergency medical service
  • medial application
  • Stroke
  • time to therapy

ASJC Scopus subject areas

  • Surgery
  • Rehabilitation
  • Clinical Neurology
  • Cardiology and Cardiovascular Medicine

Cite this

mStroke : “Mobile Stroke”—Improving Acute Stroke Care with Smartphone Technology. / Andrew, Benjamin Y.; Stack, Colleen M.; Yang, Julian P.; Dodds, Jodi A.

In: Journal of Stroke and Cerebrovascular Diseases, Vol. 26, No. 7, 01.07.2017, p. 1449-1456.

Research output: Contribution to journalArticle

Andrew, Benjamin Y. ; Stack, Colleen M. ; Yang, Julian P. ; Dodds, Jodi A. / mStroke : “Mobile Stroke”—Improving Acute Stroke Care with Smartphone Technology. In: Journal of Stroke and Cerebrovascular Diseases. 2017 ; Vol. 26, No. 7. pp. 1449-1456.
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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.",
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AU - Andrew, Benjamin Y.

AU - Stack, Colleen M.

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AU - Dodds, Jodi A.

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N2 - 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.

AB - 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.

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