title: The PulsePoint Respond mobile device application to crowdsource basic life support for patients with out-of-hospital cardiac arrest: Challenges for optimal implementation.
abstract: BACKGROUND
  PulsePoint Respond is a novel mobile device application that notifies citizens within 400 m (∼ 1/4 mile) of a suspected cardiac arrest to facilitate resuscitation. Our objectives were to (1) characterize users, and (2) understand their behavior after being sent a notification. We sought to identify challenges for optimal implementation of PulsePoint-mediated bystander resuscitation.
  
  
  METHODS
  PulsePoint Respond users who sent a notification between 04/07/2012 and 06/16/2014 were invited to participate in an online survey. At the beginning of our study, PulsePoint Respond was active in more than 600 US communities.
  
  
  RESULTS
  There were 1274 completed surveys (response rate 1448/6777, 21.4%). Respondents were firefighters (28%), paramedics (18%), emergency medical technicians (9%), nurses (7%), MDs (1%), other health care professionals (12%), and non-health care professionals (42%). Of those who received a PulsePoint notification, only 23% (189/813) responded to the PulsePoint notification. Of those who responded, 28% (52/187) did not arrive on scene. Of those who did arrive on scene, only 32% (44/135) found a person unconscious and not breathing normally. Of those who arrived on scene prior to emergency medical services and found a cardiac arrest victim, 79% (11/14) performed bystander cardiopulmonary resuscitation.
  
  
  CONCLUSIONS
  Challenges for optimal implementation of PulsePoint Respond include technical aspects of the notifications (audio volume, precision of location information), excessive activation radii, insufficient user density in the community, and suboptimal cardiac arrest notification specificity. PulsePoint Respond has the potential to improve the community response to cardiac arrest, with 80% of responders attempting basic life support when they found a cardiac arrest victim prior to EMS.
authors.affiliation: Department of Emergency Medicine, Queen's University at Kingston, Kingston, Ontario, Canada; Rescu, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Division of Emergency Medicine, Department of Medicine, University of Toronto, Toronto, Ontario, Canada. Electronic address: brookss1@kgh.kari.net.
authors.forename: Steven C
authors.initials: SC
authors.lastname: Brooks
authors.affiliation: Department of Emergency Medicine, Queen's University at Kingston, Kingston, Ontario, Canada.
authors.forename: Graydon
authors.initials: G
authors.lastname: Simmons
authors.affiliation: Department of Emergency Medicine, Queen's University at Kingston, Kingston, Ontario, Canada.
authors.forename: Heather
authors.initials: H
authors.lastname: Worthington
authors.affiliation: Arizona Emergency Medicine Research Centre, University of Arizona College of Medicine, Tucson, AZ, United States.
authors.forename: Bentley J
authors.initials: BJ
authors.lastname: Bobrow
authors.affiliation: Rescu, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Division of Emergency Medicine, Department of Medicine, University of Toronto, Toronto, Ontario, Canada.
authors.forename: Laurie J
authors.initials: LJ
authors.lastname: Morrison
mesh_terms: D016887:Cardiopulmonary Resuscitation; D063045:Crowdsourcing; D004632:Emergency Medical Services; D005260:Female; D006801:Humans; D008297:Male; D063731:Mobile Applications; D058687:Out-of-Hospital Cardiac Arrest / Q000628:therapy*; D011446:Prospective Studies; D011795:Surveys and Questionnaires; D014481:United States
keywords: Automated external defibrillators; Bystanders; Cardiac arrest; Cardiopulmonary resuscitation; Crowdsourcing; Mobile devices