INTRODUCTION: Pre-hospital ambulance calls are not random events, but occur in patterns and trends that are related to movement patterns of people, as well as the geographical epidemiology of the population. This study describes the geographic-time epidemiology of ambulance calls in a large urban city and conducts a time demand analysis. This will facilitate a Systems Status Plan for the deployment of ambulances based on the most cost effective deployment strategy. MATERIALS AND METHODS: An observational prospective study looking at the geographic-time epidemiology of all ambulance calls in Singapore. Locations of ambulance calls were spot mapped using Geographic Information Systems (GIS) technology. Ambulance response times were mapped and a demand analysis conducted by postal districts. RESULTS: Between 1 January 2006 and 31 May 2006, 31,896 patients were enrolled into the study. Mean age of patients was 51.6 years (S.D. 23.0) with 60.0% male. Race distribution was 62.5% Chinese, 19.4% Malay, 12.9% Indian and 5.2% others. Trauma consisted 31.2% of calls and medical 68.8%. 9.7% of cases were priority 1 (most severe) and 70.1% priority 2 (moderate severity). Mean call receipt to arrival at scene was 8.0 min (S.D. 4.8). Call volumes in the day were almost twice those at night, with the most calls on Mondays. We found a definite geographical distribution pattern with heavier call volumes in the suburban town centres in the Eastern and Southern part of the country. We characterised the top 35 districts with the highest call volumes by time periods, which will form the basis for ambulance deployment plans. CONCLUSION: We found a definite geographical distribution pattern of ambulance calls. This study demonstrates the utility of GIS with despatch demand analysis and has implications for maximising the effectiveness of ambulance deployment.
INTRODUCTION: Pre-hospital ambulance calls are not random events, but occur in patterns and trends that are related to movement patterns of people, as well as the geographical epidemiology of the population. This study describes the geographic-time epidemiology of ambulance calls in a large urban city and conducts a time demand analysis. This will facilitate a Systems Status Plan for the deployment of ambulances based on the most cost effective deployment strategy. MATERIALS AND METHODS: An observational prospective study looking at the geographic-time epidemiology of all ambulance calls in Singapore. Locations of ambulance calls were spot mapped using Geographic Information Systems (GIS) technology. Ambulance response times were mapped and a demand analysis conducted by postal districts. RESULTS: Between 1 January 2006 and 31 May 2006, 31,896 patients were enrolled into the study. Mean age of patients was 51.6 years (S.D. 23.0) with 60.0% male. Race distribution was 62.5% Chinese, 19.4% Malay, 12.9% Indian and 5.2% others. Trauma consisted 31.2% of calls and medical 68.8%. 9.7% of cases were priority 1 (most severe) and 70.1% priority 2 (moderate severity). Mean call receipt to arrival at scene was 8.0 min (S.D. 4.8). Call volumes in the day were almost twice those at night, with the most calls on Mondays. We found a definite geographical distribution pattern with heavier call volumes in the suburban town centres in the Eastern and Southern part of the country. We characterised the top 35 districts with the highest call volumes by time periods, which will form the basis for ambulance deployment plans. CONCLUSION: We found a definite geographical distribution pattern of ambulance calls. This study demonstrates the utility of GIS with despatch demand analysis and has implications for maximising the effectiveness of ambulance deployment.
Authors: Hanzhang Xu; Ying Xian; Fung Peng Woon; Janet Prvu Bettger; Daniel T Laskowitz; Yih Yng Ng; Marcus Eng Hock Ong; David Bruce Matchar; Deidre Anne De Silva Journal: Stroke Vasc Neurol Date: 2020-04-08