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

Sammanfattning: 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.