Clinical paperAn observational study describing the geographic-time distribution of cardiac arrests in Singapore: What is the utility of geographic information systems for planning public access defibrillation? (PADS Phase I)☆
Introduction
Of the approximately 16 000 deaths that occur in Singapore every year, about 23% will be from a cardiac cause,1 of which, some 30–40% will occur suddenly, outside of a hospital. The mechanism of death is usually a fatal arrthymia, most often ventricular tachycardia or fibrillation.2
The “chain of survival” concept3 states that survival can be improved with early access, early cardiopulmonary resuscitation (CPR), early defibrillation and early advanced care. There is currently good evidence that indicates the importance of delivering early defibrillation (<4 min).4, 5, 6, 7
It has been pointed out that it would be prohibitively expensive and logistically difficult for ambulances to respond within 4 min for every OHCA. With the invention of the simple-to-use automated external defibrillator (AED), it has been found that even untrained bystanders can successfully deliver life-saving defibrillation.8 This is the principle behind public access defibrillation (PAD), which has shown great potential to increase cardiac arrest survival rates.4, 9, 10, 11 These programs empower laypersons to perform life-saving early defibrillation by making AEDs available in public places.12, 13 Programs have been described, successfully placing AEDs at casinos,4 airports14, 15 and with trained first responders such as fire16, 17, 18 or police6 personnel.
It has been noticed that acute medical events like cardiac arrests are not random events, but rather have definite time-geographic distribution patterns.19, 20, 21 This is related to the underlying population demographics and movement patterns. Using geographic information systems (GIS) technology, we are able to depict such time-geographic patterns to aid planning for cardiac arrest interventions, such as PAD. GIS is multi-layering mapping software that is able to portray multiple geographic-time information in an easy to read, graphical manner.
The question is, what is the location and pattern of OHCA in Singapore and how can we design the most cost effective PAD strategy?22, 23 Describing the geographic pattern of cardiac arrests may also be helpful for planning ambulance deployment for cardiac arrests. This study will be a natural follow-on to the Cardiac Arrest and Resuscitation Epidemiology (CARE) project.24
We aimed to conduct a multi-phase study in Singapore, with phase I describing the geographic epidemiology of prehospital cardiac arrest in Singapore using GIS technology. This will allow us to assess the potential for deployment of a PAD program in subsequent phases and derive the most cost effective deployment strategy by type and geography of location.
Section snippets
Materials and methods
The PADS study is a multi-phase, observational prospective study looking at the geographic location of pre-hospital cardiac arrest in Singapore. The study period was 1 October 2001 to 14 October 2004.
Singapore is a city-state with a land area of 682.3 km2 and a population of 4.1 million. The island's emergency medical services (EMS) system is run by the Singapore Civil Defence Force (SCDF) which currently operates 32 ambulances based in 14 fire stations and 10 satellite stations. It is primarily
Results
From 1 October 2001 to 14 October 2004, 2428 patients were enrolled into the study. Table 1 shows the characteristics of patients in the study. Mean age was 60.6 years with 68.0% male. 67.8% of arrests occurred in residences, with 54.5% bystander witnessed and another 10.5% EMS witnessed. Mean EMS response time was 9.6 min with 21.7% receiving prehospital defibrillation.
For those collapses that occurred in residential homes (n = 1629), 865 (53.2%) were witnessed by bystanders, 635 (39.1%) were
Discussion
In this study, we found a definite geographical distribution pattern of cardiac arrest. This demonstrates the utility of using GIS in cardiac arrest research and for planning interventions.
In our study, we found cardiac arrest occurrence was highest in the suburban town centers of the Eastern and Southern (Figure 1). This roughly corresponds with population densities, with higher distribution in the Eastern and Southern part of the country. The communities listed in Table 3 with the highest
Conclusion
In this study, we found a definite geographical distribution pattern of cardiac arrest. This study demonstrates the utility of GIS with a national cardiac arrest database. Our findings have implications for planning a community PAD program, targeted CPR training, AED placement and ambulance deployment. We intend to continue with an in-depth analysis of possible sites of AED placement for a pilot PAD program. These results will enable us to derive the most cost effective deployment strategy by
Conflict of interest statement
All the authors have neither commercial nor personal associations or any sources of support that might pose a conflict of interest in the subject matter or materials discussed in this manuscript.
Acknowledgements
We thank the following CARE study group investigators:
Masnita Rahmat, RN: Medical Department, Singapore Civil Defence Force, Singapore.
Siti Afzan, BHSc (Nursing), RN: Medical Department, Singapore Civil Defence Force, Singapore.
Glibert Lau, MBBS (S’pore), FRCPath, DMJ (Path), FAMS: Centre for Forensic Medicine, Health Sciences Authority, Singapore.
David P. Edwards MBA, EMT-P: Richmond Ambulance Authority, Virginia, USA.
Derek Andresen, EMT-P: Richmond Ambulance Authority, Virginia, USA.
Peter
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A Spanish translated version of the summary of this article appears as Appendix in the final online version at 10.1016/j.resuscitation.2007.09.006.