Dispatch of lay responders to out-of-hospital cardiac arrests

Background and aim Out-of-hospital cardiac arrest (OHCA) remains a major public-health problem affecting around 300 000 Europeans each year. If treatment is not started within a couple of minutes the chances of survival are slim. One important predictor of survival is the time from call to start of treatment. To reduce this time frame, different strategies, in addition to emergency medical services (EMS), such as widespread deployment of automated external defibrillators (AEDs) and dispatch of fire fighters and police officers have been implemented. The aim of this thesis is to study the implementation and effects of a third additional resource, lay responders dispatched by the emergency dispatch center. The aim of study 1 was to evaluate the technical function and performance of a lay responder system during a run-in phase. The aim of study 2 was to measure the travelling speed and response time of the dispatched lay responders. In study 3 the aim was to investigate the emotional response, both positive and negative, wellbeing and post-traumatic stress disorder, among dispatched lay responders. In study 4 the aim was to investigate if lay responders instructed to fetch a public AED by using a smartphone application could increase the bystander use of AEDs before arrival of EMS, fire fighters and police officers. Methods and results In study 1 data from the smartphone application were collected and linked to cardiac arrest data from the Swedish Register for Cardiopulmonary Resuscitation (SRCR). During six months in 2016 the system was activated 685 times. 224 of these cases were EMS treated OHCAs. After exclusion of EMS-witnessed cases (n=11) and cases with missing survey data (n=15), 198 cases remained in the analytical sample. The results showed that dispatched lay responders reached the scene in 116 cases (58%), in 51 (26%) cases before the EMS. An AED was attached 17 times (9%) and defibrillated 4 times (2%). The median Euclidian distance to travel to perform CPR was 560 meters (IQR=332-860) compared with 1280 (IQR=748-1776) among for those who were directed to fetch an AED. In study 2, data on lay responder movement were collected from the smartphone application. During the 7-month study period 1406 suspected OHCAs were included. In these calls, 9058 lay responders accepted the mission and 2176 reached the scene of the suspected cardiac arrest (the study population). Among all cases the median travelling speed was 2.3 meters/sec (IQR=1.4–4.0) while the response time was 6.2 minutes, and the travelling distance was 956 meters (IQR=480–1661). In the most densely populated areas the median travelling speed was 1.8 meters/sec compared with 3.1 in the least densely populated areas. In study 3 we included 886 unexposed and 1389 exposed lay-responders. The lay responders were divided into 3 groups; unexposed, exposed-1 (who tried, but failed to reach the scene before EMS) and exposed-2 (who either reached the scene before EMS or performed CPR). Using the two dimensions of the Swedish Core Affect Scales (SCAS), valence and activation the results suggested that exposed lay responders showed higher activation (Exp-1=7.5, Exp-2=7.6) than unexposed lay responders (7.0) (p<0.001). Exposed lay responders had lower valence (Exp-1=6.3, Exp-2=6.3) compared with unexposed lay responders (6.8) (p<0.001). PCL-6 mean scores were highest in the unexposed group (10.4) compared with the exposed group (Exp-1=8.8, Exp-2=9.2) (p=0.007). There were no differences in the WHO wellbeing index, (Un-Exp: 77.7; Exp-1: 77.8; Exp-2: 78.2) (p=0.963). In Study 4, cases of suspected OHCA were randomly assigned to either an intervention group, where the majority of lay responders (4/5) were guided to the nearest AED, or to a control group, where all lay responders were directed to perform CPR. Data from the smartphone application system were linked to data from the SRCR. During the 13-month study period 2553 suspected OHCAs were randomized. Among these, 815 (32%) were EMS-treated. The AED attachment rate was 13.2% in the intervention group compared with 9.4 in the control group (p=0.087). In both groups combined, 29.3% of all bystanders attached AEDs, and 35.3% of all cases of bystander CPR were performed by a dispatched lay responder. Conclusions The conclusion from the first run-in study (study 1) was that it is feasible to dispatch lay responders to suspected OHCAs but that further system improvements are needed to reduce the time to defibrillation. The results from study 2 suggested that lay responders travel faster than previously estimated and that the travelling speed is dependent on population density, information that may be used for simulation studies as well as in configurations in app-based systems. Study 3 showed that lay responders rated the experience as high-energy and mostly positive. No indication of harm was seen, as the lay responders had low post-traumatic stress scores and high levels of general wellbeing at follow-up. Study 4 revealed that smartphone dispatch of lay responders to public AEDs did not increase the AED attachment rate before arrival of the EMS or first responders, versus smartphone dispatch to perform CPR. If dispatched lay responders arrived prior to the EMS, the likelihood of bystander AED use and CPR was increased

Implementierung einer Smartphone-basierten Ersthelfer-Alarmierung im Rettungsdienst als Mittel zur Verkürzung des reanimationsfreien Intervalls

Background and Aim Smartphone-based alerting systems for voluntary first-aiders could make a contribution to improve the treatment of patients with cardiac arrest in the prehospital setting. For the first time in Germany, such a project named Mobile Rescuers has been evaluated regarding feasibility and outcome-related parameters. This study was performed to test the hypothesis that mobile-phone based alerting of CPR-trained volunteers (Mobile Rescuers) simultaneously with ambulance leads to a better outcome of out-of-hospital cardiac arrest (OHCA) victims. Methods Mobile Rescuers were alerted complementary to the regular emergency medical service (EMS). This was achieved by an app which connected the rescue coordination centre with the smartphone of the Mobile Rescuer via a central web service, navigating the first-aider to the emergency scene. Endpoints were the time period between emergency call and arrival of adequate emergency care at the scene, return of spontaneous circulation, hospital admission and discharge rate as well as neurological function of survivors. The outcome of 770 OHCA-patients was prospectively examined depending on who initiated the CPR. The following groups were compared: Mobile Rescuers-initiated-CPR (n=98), Emergency Medical System (EMS)-initiated-CPR (n=386), lay bystander-initiated-CPR (n=138), telephone-CPR (T-CPR, n=148). Results Five-hundred-fifty Mobile Rescuers were recruited and trained (1.6‰ of the entire population). Sixty percent of them had a rescue service-associated profession. The majority (81%) was male. Mobile Rescuers arrived at the scene in 46% of all triggered alarms. Median response time of Mobile Rescuers was 4 (3-6[1-11]) min and those of EMS-teams 7 (5-11[3-19]) min (p<0.001). Patients who underwent Mobile Rescuerinitiated- CPR showed a tendency to be admitted to hospital with a higher return of spontaneous circulation (ROSC) rate but this effect was not significant (Mobile Rescuer vs. EMS, p=0.067). Significant differences were found in terms of hospital discharge rate and neurological outcome (Cerebral-Performance-Categories-Score). Both values were highest in patients who underwent Mobile Rescuer-initiated-CPR and lowest in patients who underwent EMS-initiated-CPR (hospital discharge rate: p=0.027, CPC 1 or 2 at discharge: p=0.049). No significant differences existed in comparison with lay bystander-initiated CPR and T-CPR. Conclusion Simultaneous alerting of nearby CPR-trained volunteers complementary to professional EMS-teams can reduce both, response time and resuscitation-free interval and improve hospital discharge rate as well as neurological outcome after OHCA. This effect is especially important in cases where ambulance response time is long and patients do not receive any CPR by lay bystanders before the arrival of EMS personnel.Hintergrund und Fragestellung Smartphone-basierte Alarmierungssysteme für Ersthelfer sollen beitragen, die Versorgung von Patienten nach prähospital erlittenem Herz-Kreislauf-Stillstand zu verbessern. Erstmalig in Deutschland wurde im Kreis Gütersloh (NRW) ein solches Projekt namens Mobile Retter im Hinblick auf Machbarkeit und Outcome-relevante Aspekte evaluiert. Mit dieser Studie wurde die Hypothese überprüft, dass die Smartphone-basierte Alarmierung freiwilliger Ersthelfer (Mobile Retter) zeitgleich mit dem Rettungsdienst zu einem besseren Outcome von Patienten mit prähospital erlittenem Herz-Kreislauf-Stillstand führt. Methodik Die Alarmierung der Mobilen Retter erfolgte komplementär zum Rettungsdienst. Ermöglicht wurde dies durch eine App, die über einen zentralen Webserver einen Datenaustausch zwischen dem Smartphone des Ersthelfers und der Rettungsleitstelle gewährleistet. Die wichtigsten Endpunkte waren der Zeitraum vom Beginn der Notrufabfrage bis zum Eintreffen adäquater Hilfe am Einsatzort, die Rückkehr eines Spontankreislaufs nach Herz-Kreislauf-Stillstand, die Krankenhausaufnahmerate, die Entlassungsrate aus dem Krankenhaus sowie die neurologische Funktion bei Krankenhausentlassung. Insgesamt wurde das Outcome von 770 Patienten mit prähospital erlittenem Herz-Kreislauf-Stillstand in Abhängigkeit davon untersucht, wer mit den Reanimationsmaßnahmen begonnen hat. Dementsprechend wurden folgende Gruppen miteinander verglichen: Reanimation durch Mobile Retter initiiert (n=98), Reanimation durch regulären Rettungsdienst initiiert (n=386), Reanimation durch Laien (Bystander) initiiert (n=138) und Dispatcher-assistierte Telefonreanimation (n=148). Ergebnisse Im Beobachtungszeitraum konnten 550 Ersthelfer (1,6‰ der Gesamtbevölkerung) ausgebildet werden. Die Mehrheit kam aus rettungsdienstlichen Berufen (60%). Deutlich mehr Männer (81%) als Frauen wurden rekrutiert. Für 46% aller Alarmierungen erfolgte eine Einsatzübernahme durch Mobile Retter. Die durchschnittliche Hilfsfrist konnte durch den Einsatz Mobiler Retter deutlich reduziert werden (Mobile Retter: 4 (3-6[1-11]) min versus Rettungsdienst: 7 (5-11[3-19]) min; p<0,001). Patienten, deren Reanimation durch Mobile Retter initiiert wurde, zeigten bei Krankenhausaufnahme eine höhere ROSC (return of spontaneous circulation/wiedergekehrter Spontankreislauf) -Rate, aber dieser Effekt war nicht signifikant (Mobile Retter versus Rettungsdienst; p=0,067). Signifikante Gruppenunterschiede wurden im Hinblick auf die Krankenhausentlassungsrate und die neurologische Funktion bei Krankenhausentlassung (Cerebral-Performance- Categories-Score/CPC) gefunden. Beide Werte waren in der Mobile Retter-Gruppe am höchsten und in der Rettungsdienst-Gruppe am niedrigsten (Krankenhausentlassungsrate: p=0,027; gute neurologische Funktion ≙ CPC1+2: p=0,049). Diesbezüglich gab es keine signifikanten Gruppenunterschiede zwischen der Mobile Retter-Gruppe und der Telefonreanimations- bzw. Laienreanimationsgruppe. Schlussfolgerungen Das Smartphone-basierte Alarmierungssystem Mobile Retter führt zu einem Zeitvorteil gegenüber den etablierten Rettungsdienstkonzepten und somit zur Reduktion des reanimationsfreien Intervalls bei Patienten im außerklinischen Herz-Kreislauf- Stillstand. Dies wiederum ist verbunden mit einer höheren Krankenhausentlassungsrate und einer besseren neurologischen Funktion bei der Krankenhausentlassung. Dieser Effekt ist in jenen Fällen besonders bedeutungsvoll, in denen der Rettungsdienst eine lange Anfahrtszeit hat und gleichzeitig keine Reanimationsmaßnahmen durch umstehende Laien eingeleitet werden