title: Spatial analysis of ambulance response times related to prehospital cardiac arrests in the city-state of Singapore.
abstract: OBJECTIVE
  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.
authors: Centre for Quantitative Medicine, Office of Clinical Sciences, Duke-NUS Graduate Medical School (AE), Singapore.
authors: Arul
authors: A
authors: Earnest
authors: Marcus Eng
authors: ME
authors: Hock Ong
authors: Nur
authors: N
authors: Shahidah
authors: Wen
authors: W
authors: Min Ng
authors: Chuanyang
authors: C
authors: Foo
authors: David John
authors: DJ
authors: Nott
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D000552:Ambulances / Q000458:organization & administration* / Q000706:statistics & numerical data*; D001499:Bayes Theorem; D016208:Databases, Factual; D004630:Emergencies; D004632:Emergency Medical Services / Q000592:standards* / Q000639:trends; D005260:Female; D006297:Health Services Accessibility; D006801:Humans; D008297:Male; D008875:Middle Aged; D058687:Out-of-Hospital Cardiac Arrest / Q000401:mortality / Q000628:therapy*; D012189:Retrospective Studies; D018570:Risk Assessment; D012846:Singapore; D012959:Socioeconomic Factors; D016019:Survival Analysis; D013997:Time Factors; D014505:Urban Population