Staribacher Daniel, Rauner Marion Sabine, Niessner Helmut
Medical University Vienna, Spitalgasse 23, A-1090 Vienna, Austria.
Clinic for Neurosurgery, Sozialstiftung Bamberg, Buger Straße 80, D-96049 Bamberg, Germany.
Healthcare (Basel). 2023 Oct 11;11(20):2713. doi: 10.3390/healthcare11202713.
Using a discrete-event simulation (DES) model, the current disaster plan regarding the allocation of multiple injured patients from a mass casualty incident was evaluated for an acute specialty hospital in Vienna, Austria. With the current resources available, the results showed that the number of severely injured patients currently assigned might have to wait longer than the medically justifiable limit for lifesaving surgery. Furthermore, policy scenarios of increasing staff and/or equipment did not lead to a sufficient improvement of this outcome measure. However, the mean target waiting time for critical treatment of moderately injured patients could be met under all policy scenarios. Using simulation-optimization, an optimal staff-mix could be found for an illustrative policy scenario. In addition, a multiple regression model of simulated staff-mix policy scenarios identified staff categories (number of radiologists and rotation physicians) with the highest impact on waiting time and survival. In the short term, the current hospital disaster plan should consider reducing the number of severely injured patients to be treated. In the long term, we would recommend expanding hospital capacity-in terms of both structural and human resources as well as improving regional disaster planning. Policymakers should also consider the limitations of this study when applying these insights to different areas or circumstances.
利用离散事件模拟（DES）模型，对奥地利维也纳一家急性专科医院当前针对大规模伤亡事件中多名受伤患者分配的灾难预案进行了评估。根据现有资源，结果显示，目前分配的重伤患者数量可能需要等待超过医学上合理的救命手术时限。此外，增加工作人员和/或设备的政策方案并未充分改善这一结果指标。然而，在所有政策方案下，中度受伤患者关键治疗的平均目标等待时间均能达到。通过模拟优化，可为一个说明性政策方案找到最佳人员组合。此外，模拟人员组合政策方案的多元回归模型确定了对等待时间和生存率影响最大的人员类别（放射科医生和轮转医生数量）。短期内，当前医院灾难预案应考虑减少待治疗的重伤患者数量。从长远来看，我们建议在结构和人力资源方面扩大医院容量，并改善区域灾难规划。政策制定者在将这些见解应用于不同地区或情况时，也应考虑本研究的局限性。
