Abstract：
Shortening the prehospital emergency medical service (EMS) response time is crucial for saving lives and lowering mortality and disability rates in patients with sudden illnesses. Descriptive analyses of prehospital EMS response time and each component were conducted separately using ambulance trip data from the 120 Dispatch Command Centre in the main urban area of Chongqing in 2021, and then, logistic regression analyses were used to explore the influencing factors. The median prehospital EMS response time in the main urban area of Chongqing was 14.52 min and the mean was 16.14 min. A 44.89% of prehospital EMS response time exceeded 15 min. Response time was more likely to surpass this threshold during peak hours and in high population density areas. Conversely, lower probabilities exceeding 15 min were observed during the night shift, summer, and autumn seasons, and areas with a high density of emergency station. 33.28% of preparation time was >3 min, with the night shift and high population density areas more likely to be >3 min, while for the summer and autumn seasons, high Gross National Product (GDP) per capita areas had a lower likelihood of having preparation time >3 min. 45.52% of travel time was >11 min, with peak hours, summer and autumn, and high GDP per capita areas more likely to have had a travel time >11 min, while night shift and high emergency station density areas had a lower likelihood of travel time >11 min. The primary factors influencing prehospital EMS response time were shifts, traffic scenarios, seasons, GDP per capita, emergency station density, and population density. Relevant departments can devise effective interventions to reduce response time through resource allocation and department coordination, staff training and work arrangement optimisation, as well as public participation and education, thereby enhancing the efficiency of prehospital emergency medical services.
摘要：
背景：缩短院前急救医疗服务（EMS）响应时间对于挽救生命，降低突发疾病患者的死亡率和致残率至关重要。
方法：利用重庆市主城区120调度指挥中心2021年救护车出行数据，分别对院前EMS响应时间和各构成进行描述性分析，然后采用logistic回归分析探讨影响因素。
结果：重庆市主城区院前EMS响应时间中位数为14.52分钟，平均值是16.14分钟.44.89%的院前EMS响应时间超过15分钟。在高峰时段和高人口密度地区，响应时间更有可能超过此阈值。相反，在夜班期间观察到超过15分钟的较低概率，夏季和秋季，以及应急站密度高的地区。33.28%的制备时间大于3分钟，夜班和人口密度高的地区更有可能超过3分钟，而夏季和秋季，高人均国内生产总值地区的准备时间超过3分钟的可能性较低。45.52%的旅行时间大于11分钟，在高峰时段，夏天和秋天，人均GDP高的地区旅行时间可能超过11分钟，而夜班和急救站密度高的地区旅行时间超过11分钟的可能性较低。
结论：影响院前EMS反应时间的主要因素是变化，交通场景，季节,人均GDP,应急站密度，和人口密度。相关部门可以设计有效的干预措施，通过资源分配和部门协调来减少响应时间，员工培训和工作安排优化，以及公众参与和教育，从而提高院前急救医疗服务的效率。
方法：利用重庆市主城区120调度指挥中心2021年救护车出行数据，分别对院前EMS响应时间和各构成进行描述性分析，然后采用logistic回归分析探讨影响因素。
结果：重庆市主城区院前EMS响应时间中位数为14.52分钟，平均值是16.14分钟.44.89%的院前EMS响应时间超过15分钟。在高峰时段和高人口密度地区，响应时间更有可能超过此阈值。相反，在夜班期间观察到超过15分钟的较低概率，夏季和秋季，以及应急站密度高的地区。33.28%的制备时间大于3分钟，夜班和人口密度高的地区更有可能超过3分钟，而夏季和秋季，高人均国内生产总值地区的准备时间超过3分钟的可能性较低。45.52%的旅行时间大于11分钟，在高峰时段，夏天和秋天，人均GDP高的地区旅行时间可能超过11分钟，而夜班和急救站密度高的地区旅行时间超过11分钟的可能性较低。
结论：影响院前EMS反应时间的主要因素是变化，交通场景，季节,人均GDP,应急站密度，和人口密度。相关部门可以设计有效的干预措施，通过资源分配和部门协调来减少响应时间，员工培训和工作安排优化，以及公众参与和教育，从而提高院前急救医疗服务的效率。
