Spatial analysis of ambulance response times related to prehospital cardiac arrests in the city-state of Singapore.

OBJECTIVES: The main objective of this study was to establish the spatial variation in ambulance response times for out-of-hospital cardiac arrests (OHCAs) in the city-state of Singapore. The secondary objective involved studying the relationships between various covariates, such as traffic condition and time and day of collapse, and ambulance response times. METHODS: The study design was observational and ecological in nature. Data on OHCAs were collected from a nationally representative database for the period October 2001 to October 2004. We used the conditional autoregressive (CAR) model to analyze the data. Within the Bayesian framework of analysis, we used a Weibull regression model that took into account spatial random effects. The regression model was used to study the independent effects of each covariate. RESULTS: Our results showed that there was spatial heterogeneity in the ambulance response times in Singapore. Generally, areas in the far outskirts (suburbs), such as Boon Lay (in the west) and Sembawang (in the north), fared badly in terms of ambulance response times. This improved when adjusted for key covariates, including distance from the nearest fire station. Ambulance response time was also associated with better traffic conditions, weekend OHCAs, distance from the nearest fire station, and OHCAs occurring during nonpeak driving hours. For instance, the hazard ratio for good ambulance response time was 2.35 (95% credible interval [CI] 1.97-2.81) when traffic conditions were light and 1.72 (95% CI 1.51-1.97) when traffic conditions were moderate, as compared with heavy traffic. CONCLUSIONS: We found a clear spatial gradient for ambulance response times, with far-outlying areas' exhibiting poorer response times. Our study highlights the utility of this novel approach, which may be helpful for planning emergency medical services and public emergency responses.

Spatial variation and geographic-demographic determinants of out-of-hospital cardiac arrests in the city-state of Singapore.

STUDY OBJECTIVE: Our primary objective is to calculate the relative risk of cardiac arrests at the development guide plan (DGP) (equivalent to census tract) level in a city-state, Singapore, and examine its relationship with key area-level population characteristics. METHODS: This was an observational ecological study design. We calculated the relative risk as the ratio of the observed and population standardized expected counts of out-of-hospital cardiac arrests in Singapore, aggregated at DGP level. Data were collected from October 2001 to October 2004. We used conditional autoregressive spatial models to examine the predictors of increased risk at the DGP level. RESULTS: We found a spatial distribution of cardiac arrests, with an unexpected cluster caused by nonresident arrests occurring at the international airport. The risk of out-of-hospital cardiac arrest more than doubled, 2.35 (95% confidence interval [CI] 1.28 to 4.48), for each 5-point increase in the proportion of people aged 65 years and older. For each 5-point increase in the proportion of Chinese individuals living in a DGP, the risk of out-of-hospital cardiac arrest was reduced by a factor of 0.8 (95% CI 0.7 to 0.9). The risk of out-of-hospital cardiac arrest increased by 1.49-fold (95% CI 1.18 to 1.82) for every 5-point increase in the proportion of households with no family nucleus (live alone). When restricted to residential cases of out-of-hospital cardiac arrest, none of the variables remained significant, possibly because of small sample size. CONCLUSION: The risk of cardiac arrests could be related to the age and racial and family structure of DGPs in Singapore. This article models how such data can help to direct public health education, cardiopulmonary resuscitation training, and public access defibrillation programs in other health systems.