- ISSN: 1999-7086
- E-ISSN: 1999-7094
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oa Ambulance services resource allocation using geospatial analyses for road traffic incidents in a middle-income country
- المصدر: Journal of Emergency Medicine, Trauma and Acute Care, Volume 2026, Issue 1, فبراير ٢٠٢٦, 3
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- ٠٩ مارس ٢٠٢٥
- ٠٢ يوليو ٢٠٢٥
- ٢٢ يناير ٢٠٢٦
Introduction: Ambulance resource allocation by using an evidence-based approach is very much required so that pre-hospital care service allocation is targeted to areas that prove to have a high incidence burden of injuries on the road. Hence, we conducted a geographic information system (GIS) hotspot analysis in a district to identify hotspot areas and temporal trending, aiming to guide the ambulance providers to provide service efficiently and hence improve the early care of trauma in a resource-limited setting. The study centers utilized the hospital-based Anglo-American model of ambulance services.
Methods: All ambulance dispatch cases for road traffic incidents (RTIs) from two tertiary centers in the District of Kota Bharu, Malaysia, were included. Data collection was carried out for 10 months commencing January 2023. The digital map consisted of layers of borough boundaries, and the road network was obtained from the local municipal office. The x and y GIS coordinates for each RTI location were recorded from the automated vehicle location (AVL) mapping system installed in the dispatch center that was linked to each of the ambulance units. Cases were included for all ambulance dispatch cases related to RTIs. Self-referrals, other modes of emergency department attendances, and missing GIS coordinates were excluded from analysis. The data were transferred into the Excel format, which in turn underwent GIS analysis by using ArcGIS (10.1). The GIS clustering analysis involved mapping of RTI cases based on borough and road network digital layers by using inverse distance weighting (IDW) analysis. Other secondary data were obtained from ambulance services records from both hospitals.
Results: A total of 439 RTI cases were recruited over the 10-month data collection period. Temporal analysis showed that there were obvious peaked RTI incidences (37% of all cases) in the late morning and early evening. Thirty percent of cases of RTI occurred during the weekend, with a slight surge on Saturdays. Urban area was the most common location for RTI (n = 247; 59.9%). Clustering analyses had shown two boroughs, namely Boroughs Demit and Binjai, with hotspot and high-severity injured cases, respectively.
Conclusion: The study identified two boroughs with hotspots for RTI that peaked in the early morning and during the weekend. Geographical information system findings had given insight to PHC providers for future planning in ambulance resource allocation in the area of interest based on location and time that needed the most.
