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In this chapter, we explore how data-driven modeling can improve the understanding of OHCA risk, help identify the limitations of current AED placement strategies, and guide the development of optimal AED networks to increase the chance of AED use and OHCA survival. More specifically, we frame AED network design and related response efforts as a facility location problem, focusing on the maximum coverage location and p-median problems. We also highlight how novel tools that combine techniques from areas including information theory and machine learning with optimization models can shape the future of OHCA response efforts and AED placement strategies.
In South Korea, the law concerning automated external defibrillators (AEDs) states that they should be installed in specific places including apartment complexes. This study was conducted to investigate the current status and effectiveness of installation and usage of AEDs in South Korea.
Methods:
Installation and usage of AEDs in South Korea is registered in the National Emergency Medical Center (NEMC) database. Compared were the installed number, usage, and annual rate of AED use according to places of installation. All data were obtained from the NEMC database.
Results:
After excluding AEDs installed in ambulances or fire engines (n = 2,003), 36,498 AEDs were registered in South Korea from 1998 through 2018. A higher number of AEDs were installed in places required by the law compared with those not required by the law (20,678 [56.7%] vs. 15,820 [43.3%]; P <.001). Among them, 11,318 (31.0%) AEDs were installed in apartment complexes. The overall annual rate of AED use was 0.38% (95% CI, 0.33-0.44). The annual rate of AED use was significantly higher in places not required by the law (0.62% [95% CI, 0.52-0.72] versus 0.21% [95% CI, 0.16-0.25]; P <.001). The annual rate of AED use in apartment complexes was 0.13% (95% CI, 0.08-0.17).
Conclusion:
There were significant mismatches between the number of installed AEDs and the annual rate of AED use among places. To optimize the benefit of AEDs in South Korea, changes in the policy for selecting AED placement are needed.
Rapid access to defibrillation is a key element in the management of out-of-hospital cardiac arrests (OHCAs). Public automated external defibrillators (PAEDs) are becoming increasingly available, but little information exists regarding the relation between the proximity to the arrest and their usage in urban areas.
Methods
This study is a retrospective, observational, cross-sectional analysis of non-traumatic OHCA during a 24-month period in the greater Montreal area (Quebec, Canada). Using logistic regression, bystander shock odds are described with regards to distance from the OHCA scene to the nearest PAED, adjusted for prehospital care arrival delay and time of day, and stratifying for type of location.
Results
Out of a total of 2,443 OHCA victims identified, 77 (3%) received bystander PAED shock, 622 (26%) occurred out-of-home, and 743 (30%) occurred during business hours. When controlling for time (business hours versus other hours) and minimum response delay for prehospital care arrival, a marginal negative association was found between bystander shock and distance to the nearest PAED in logged meters (aOR=0.80; CI, 0.64-0.99) for out-of-home cardiac arrests. No significant association was found between distance and bystander shock for at-home arrests. Out-of-home victims had significantly higher odds of receiving bystander shock up to 175 meters of distance to a PAED inclusively (aOR=2.52; CI, 1.07-5.89).
Conclusion
For out-of-home cardiac arrests, proximity to a PAED was associated with bystander shock in the greater Montreal area. Strategies aiming to increase accessibility and use of these life-saving devices could further expand this advantage by assisting bystanders in rapidly locating nearby PAEDs.
Neves BriardJ, de MontignyL, RossD, de ChamplainF, SegalE. Is Distance to the Nearest Registered Public Automated Defibrillator Associated with the Probability of Bystander Shock for Victims of Out-of-Hospital Cardiac Arrest?Prehosp Disaster Med. 2018;33(2):153–159.
Much attention has been given to the strategic placement of automated external defibrillators (AEDs). The purpose of this study was to examine the correlation of strategically placed AEDs and the actual location of cardiac arrests.
Methods
A retrospective review of data maintained by the Maryland Institute for Emergency Medical Services Systems (MIEMSS), specifically, the Maryland Cardiac Arrest Database and the Maryland AED Registry, was conducted. Location types for AEDs were compared with the locations of out-of-hospital cardiac arrests in Howard County, Maryland. The respective locations were compared using scatter diagrams and r2 statistics.
Results
The r2 statistics for AED location compared with witnessed cardiac arrest and total cardiac arrests were 0.054 and 0.051 respectively, indicating a weak relationship between the two variables in each case. No AEDs were registered in the three most frequently occurring locations for cardiac arrests (private homes, skilled nursing facilities, assisted living facilities) and no cardiac arrests occurred at the locations where AEDs were most commonly placed (community pools, nongovernment public buildings, schools/educational facilities).
Conclusion
A poor association exists between the location of cardiac arrests and the location of AEDs.
LevyMJ, SeamanKG, MillinMG, BissellRA, JenkinsJL. A Poor Association Between Out-of-Hospital Cardiac Arrest Location and Public Automated External Defibrillator Placement. Prehosp Disaster Med. 2013;28(4):1-6.
A growing number of golfers are senior citizens, and it may be predicted that the number of golf-related medical emergencies, including the incidence of cardiac arrest, will increase. This study was designed to survey the level of preparedness of golf courses in Southeastern Pennsylvania to respond to cardiac arrest among their members.
Methods:
A telephone survey of all of the 180 golf courses in the area was conducted to determine their type (public/private), volume in rounds per year, presence of automated external defibrillator (AED) devices, number of employees, and percentage of employees with cardiopulmonary resuscitation (CPR) training. Participants also were asked to estimate the time needed to reach the farthest point on their course in order to estimate a maximum time to the application of an AED device.
Results:
A total of 131 of 180 golf courses completed the survey (53 private, 78 public) for an overall response rate of 73%. Private courses reported a greater average number of employees with CPR training [private = 9.1, public = 3.6; p = 0.001] and in AED presence [public = 9%, private = 58.5%; p = 0.0001]. Public courses support a higher volume of play than do private courses [public = 32,000, private = 24,000; p = 0.001], yet have far fewer employees [public = 25, private = 44; p = 0.004]. The longest time necessary to reach the most remote point on the course was between four and five minutes in all courses. Analysis was performed using the Student's t-test and Pearson's Chi-square as appropriate.
Conclusion:
Neither public nor private golf courses are well equipped to respond to cardiac arrest, but outcomes on public courses likely are to be far worse.
For patients who suffer out-of-hospital cardiac arrest, the time from collapse to initial defibrillation is the single most important factor that affects survival to hospital discharge. The purpose of this study was to compare the survival rates of cardiac arrest victims within an institution that has a rapid defibrillation program with those of its own urban community, tiered EMS system.
Methods:
A logistic regression analysis of a retrospective data series (n = 23) and comparative analysis to a second retrospective data series (n = 724) were gathered for the study period September 1994 to September 1999. The first data series included all persons at Casino Windsor who suffered a cardiac arrest. Data collected included: age, gender, death/survival (neurologically intact discharge), presenting rhythm (ventricular fibrillation (VF), ventricular tachycardia (VT), or other), time of collapse, time to arrival of security personnel, time to initiation of cardiopulmonary resuscitation (CPR) prior to defibrillation (when applicable), time to arrival of staff nurse, time to initial defibrillation, and time to return of spontaneous circulation (if any). Significantly, all arrests within this series were witnessed by the surveillance camera system, allowing time of collapse to be accurately determined rather than estimated. These data were compared to those of similar events, times, and intervals for all patients in the greater Windsor area who suffered cardiac arrest. This second series was based upon the Ontario Prehospital Advanced Life Support (OPALS) Study database, as coordinated by the Clinical Epidemiology Unit of the Ottawa Hospital, University of Ottawa.
Results:
The Casino Windsor had 23 cases of cardiac arrests. Of the cases, 13 (56.5%) were male and 10 (43.5%) were female. All cases (100%) were witnessed. The average of the ages was 61.1 years, of the time to initial defibrillation was 7.7 minutes, and of the time for EMS to reach the patient was 13.3 minutes. The presenting rhythm was VF/VT in 91% of the case. Fifteen patients were discharged alive from hospital for a 65% survival rate. The Greater Windsor Study area included 668 cases of out-of-hospital cardiac arrest: Of these, 410 (61.4%) were male and 258 (38.6%) were female, 365 (54.6%) were witnessed, and 303 (45.4%) were not witnessed. The initial rhythm was VF/VT was in 34.3%. Thirty-seven (5.5%) were discharged alive from the hospital.
Conclusion:
This study provides further evidence that PAD Programs may enhance cardiac arrest survival rates and should be considered for any venue with large numbers of adults as well as areas with difficult medical access.