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Estimating the right allocation of resources on weekends and public holidays in Green Zone using hybrid methods

机译:使用混合方法估算周末和公共假期资源的正确配置

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Long patient waiting time and congestion is a major problem faced by Green Zone in Emergency Department at Hospital Universiti Sains Malaysia (EDHUSM) especially during weekends and public holidays. Even though the Green Zone is servicing only the non-critical patients, patient waiting time, causing the department fails to achieve its Key Performance Indicator (KPI). The long waiting time is due to the insufficient resources provided during the weekends and public holidays versus the large number of patients. Currently, only two doctors supported by two nurses are scheduled for every shift during weekends and public holidays. The numbers of patients are higher during weekends and public holidays as compared to weekdays, but the scheduled number of doctors and nurses are the same as weekdays. Therefore, this study presents a hybrid method to estimate the right number of doctors and nurses for improving the services of the Green Zone during weekends and public holidays. Fifty scenarios based on current and proposed schedules of doctors and nurses are simulated and analysed using the hybrid method of Discrete Event Simulation (DES) and Data Envelopment Analysis (DEA). Banker, Charnes and Cooper (BCC) input-oriented model and Super-Efficiency models of DEA were used to analyse the efficiency of the scenarios. The results show that the best schedule is a combination of four doctors supported by four nurses in every shift during weekends and public holidays for the Green Zone. The findings show that such schedule will not only help the department to achieve its KPI but also enable a more optimal utilization of the resources.
机译:长期患者等候时间和拥塞是在医院大学马来西亚(埃德胡斯州)的急诊部门面临的绿地面临的主要问题,特别是在周末和公众假期。尽管绿区仅服务于非关键患者,但患者等待时间,导致该部门未能实现其关键绩效指标(KPI)。漫长的等待时间是由于周末提供的资源不足,公众假期与大量患者。目前,只有两名护士支持的两位医生都安排在周末和公众假期的每一个班次。与日田相比,周末和公众假期的患者数量较高,但预定的医生和护士数量与平日相同。因此,本研究提出了一种混合方法,估计在周末和公众假期期间改善绿区服务的合适数量的医生和护士。使用离散事件仿真(DES)和数据包络分析(DEA)的混合方法模拟并分析基于当前和拟议的医生和护士日程的五十个方案。银行家,夏尔通和库珀(BCC)以输入为导向的模型和超级效率模型,用于分析方案的效率。结果表明,最好的时间表是四名医生的组合,在周末和绿地的公共假期期间四名护士支撑。调查结果表明,此类时间表不仅可以帮助该部门实现其KPI,而且还能实现更优化的资源。

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