Cvetković Vladimir M, Tanasić Jasmina, Renner Renate, Rokvić Vanja, Beriša Hatiža
Department of Disaster Management and Environmental Security, Faculty of Security Studies, University of Belgrade, Gospodara Vučića 50, 11040 Belgrade, Serbia.
Scientific-Professional Society for Disaster Risk Management, Dimitrija Tucovića 121, 11040 Belgrade, Serbia.
Healthcare (Basel). 2024 Oct 1;12(19):1962. doi: 10.3390/healthcare12191962.
BACKGROUND/OBJECTIVES: Emergency Medical Response Systems (EMRSs) play a vital role in delivering medical aid during natural and man-made disasters. This quantitative research delves into the analysis of risk and effectiveness within Serbia's Emergency Medical Services (EMS), with a special emphasis on how work organization, resource distribution, and preparedness for mass casualty events contribute to overall disaster preparedness.
The study was conducted using a questionnaire consisting of 7 sections and a total of 88 variables, distributed to and collected from 172 healthcare institutions (Public Health Centers and Hospitals). Statistical methods, including Pearson's correlation, multivariate regression analysis, and chi-square tests, were rigorously applied to analyze and interpret the data.
The results from the multivariate regression analysis revealed that the organization of working hours ( = 0.035) and shift work ( = 0.042) were significant predictors of EMS organization, explaining 1.9% of the variance ( = 0.019). Furthermore, shift work ( = -0.045) and working hours ( = -0.037) accounted for 2.0% of the variance in the number of EMS points performed ( = 0.020). Also, the availability of ambulance vehicles ( = 0.075) and financial resources ( = 0.033) explained 4.1% of the variance in mass casualty preparedness ( = 0.041). When it comes to service area coverage, the regression results suggest that none of the predictors were statistically significant. Based on Pearson's correlation results, there is a statistically significant correlation between the EMS organization and several key variables such as the number of EMS doctors ( = 0.000), emergency medicine specialists ( = 0.000), etc. Moreover, the Chi-square test results reveal statistically significant correlations between EMS organization and how EMS activities are conducted ( = 0.001), the number of activity locations ( = 0.005), and the structure of working hours ( = 0.001).
Additionally, the results underscore the necessity for increased financial support, standardized protocols, and enhanced intersectoral collaboration to strengthen Serbia's EMRS and improve overall disaster response effectiveness. Based on these findings, a clear roadmap is provided for policymakers, healthcare administrators, and EMS personnel to prioritize strategic interventions and build a robust emergency medical response system.
背景/目标：紧急医疗响应系统（EMRSs）在自然灾害和人为灾难期间提供医疗援助方面发挥着至关重要的作用。这项定量研究深入分析了塞尔维亚紧急医疗服务（EMS）中的风险和有效性，特别强调工作组织、资源分配以及大规模伤亡事件的准备情况如何影响整体灾难准备工作。
该研究通过一份包含7个部分、共88个变量的问卷进行，问卷分发给172家医疗机构（公共卫生中心和医院）并回收。严格应用包括皮尔逊相关性分析、多元回归分析和卡方检验在内的统计方法来分析和解释数据。
多元回归分析结果显示，工作时间安排（=0.035）和轮班工作（=0.042）是EMS组织的重要预测因素，解释了1.9%的方差（=0.019）。此外，轮班工作（=-0.045）和工作时间（=-0.037）占EMS执行点数方差的2.0%（=0.020）。而且，救护车车辆的可用性（=0.075）和财政资源（=0.033）解释了大规模伤亡事件准备情况中4.1%的方差（=0.041）。在服务区域覆盖方面，回归结果表明没有一个预测因素具有统计学意义。基于皮尔逊相关性分析结果，EMS组织与几个关键变量之间存在统计学显著相关性，如EMS医生数量（=0.000）、急诊医学专家数量（=0.000）等。此外，卡方检验结果显示EMS组织与EMS活动开展方式（=0.001）、活动地点数量（=0.005）以及工作时间结构（=0.001）之间存在统计学显著相关性。
此外，研究结果强调需要增加财政支持、规范协议并加强部门间合作以加强塞尔维亚的EMRS并提高整体灾难应对有效性。基于这些发现，为政策制定者、医疗保健管理人员和EMS人员提供了一份清晰的路线图，以确定战略干预的优先事项并建立一个强大的紧急医疗响应系统。
