title: Reducing ambulance response times using geospatial-time analysis of ambulance deployment.
abstract: OBJECTIVE
  This study aimed to determine if a deployment strategy based on geospatial-time analysis is able to reduce ambulance response times for out-of-hospital cardiac arrests (OOHCA) in an urban emergency medical services (EMS) system.
  
  
  METHODS
  An observational prospective study examining geographic locations of all OOHCA in Singapore was conducted. Locations of cardiac arrests were spot-mapped using a geographic information system (GIS). A progressive strategy of satellite ambulance deployment was implemented, increasing ambulance bases from 17 to 32 locations. Variation in ambulance deployment according to demand, based on time of day, was also implemented. The total number of ambulances and crews remained constant over the study period. The main outcome measure was ambulance response times.
  
  
  RESULTS
  From October 1, 2001, to October 14, 2004, a total of 2,428 OOHCA patients were enrolled into the study. Mean ± SD age for arrests was 60.6 ± 19.3 years with 68.0% male. The overall return of spontaneous circulation (ROSC) rate was 17.2% and survival to discharge rate was 1.6%. Response time decreased significantly as the number of fire stations/fire posts increased (Pearson χ(2) = 108.70, df = 48, p < 0.001). Response times for OOHCA decreased from a monthly median of 10.1 minutes at the beginning to 7.1 minutes at the end of the study. Similarly, the proportion of cases with response times < 8 minutes increased from 22.3% to 47.3% and < 11 minutes from 57.6% to 77.5% at the end of the study.
  
  
  CONCLUSIONS
  A simple, relatively low-cost ambulance deployment strategy was associated with significantly reduced response times for OOHCA. Geospatial-time analysis can be a useful tool for EMS providers.
authors.affiliation: Department of Emergency Medicine, Singapore General Hospital, Singapore. marcus.ong.e.h@sgh.com.sg
authors.forename: Marcus Eng Hock
authors.initials: ME
authors.lastname: Ong
authors.forename: Tut Fu
authors.initials: TF
authors.lastname: Chiam
authors.forename: Faith Suan Peng
authors.initials: FS
authors.lastname: Ng
authors.forename: Papia
authors.initials: P
authors.lastname: Sultana
authors.forename: Swee Han
authors.initials: SH
authors.lastname: Lim
authors.forename: Benjamin Sieu-Hon
authors.initials: BS
authors.lastname: Leong
authors.forename: Victor Yeok Kein
authors.initials: VY
authors.lastname: Ong
authors.forename: Elaine Ching
authors.initials: EC
authors.lastname: Ching Tan
authors.forename: Lai Peng
authors.initials: LP
authors.lastname: Tham
authors.forename: Susan
authors.initials: S
authors.lastname: Yap
authors.forename: V
authors.initials: V
authors.lastname: Anantharaman
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000552:Ambulances / Q000706:statistics & numerical data*; D004638:Emergency Treatment / Q000379:methods; D005260:Female; D040362:Geographic Information Systems; D005843:Geography; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D058687:Out-of-Hospital Cardiac Arrest / Q000453:epidemiology* / Q000628:therapy; D011446:Prospective Studies; D012111:Residence Characteristics; D012846:Singapore / Q000453:epidemiology; D015996:Survival Rate; D013997:Time Factors; D019037:Urban Health Services