Optimisation, Modelling, Analysis and Simulation (OptiMAS) Research Group, Faculty of Information & Communication Technology, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, Malaysia.
Planning Division, Ministry of Health Malaysia, Kompleks E, Presint 1, Pusat Pentadbiran Kerajaan Persekutuan, 62590, Putrajaya, Malaysia.
Health Care Manag Sci. 2018 Dec;21(4):573-586. doi: 10.1007/s10729-017-9413-7. Epub 2017 Aug 18.
The paper aims to provide an insight into the significance of having a simulation model to forecast the supply of registered nurses for health workforce planning policy using System Dynamics. A model is highly in demand to predict the workforce demand for nurses in the future, which it supports for complete development of a needs-based nurse workforce projection using Malaysia as a case study. The supply model consists of three sub-models to forecast the number of registered nurses for the next 15 years: training model, population model and Full Time Equivalent (FTE) model. In fact, the training model is for predicting the number of newly registered nurses after training is completed. Furthermore, the population model is for indicating the number of registered nurses in the nation and the FTE model is useful for counting the number of registered nurses with direct patient care. Each model is described in detail with the logical connection and mathematical governing equation for accurate forecasting. The supply model is validated using error analysis approach in terms of the root mean square percent error and the Theil inequality statistics, which is mportant for evaluating the simulation results. Moreover, the output of simulation results provides a useful insight for policy makers as a what-if analysis is conducted. Some recommendations are proposed in order to deal with the nursing deficit. It must be noted that the results from the simulation model will be used for the next stage of the Needs-Based Nurse Workforce projection project. The impact of this study is that it provides the ability for greater planning and policy making with better predictions.
本文旨在探讨使用系统动力学为卫生人力规划政策建立模拟模型以预测注册护士供应量的意义。非常需要一个模型来预测未来护士的劳动力需求，该模型支持使用马来西亚作为案例研究，全面开发基于需求的护士劳动力预测。供应模型由三个子模型组成，用于预测未来 15 年的注册护士数量：培训模型、人口模型和全职等效（FTE）模型。实际上，培训模型用于预测培训完成后新注册护士的数量。此外，人口模型用于指示全国注册护士的数量，而 FTE 模型则用于计算直接护理患者的注册护士数量。每个模型都详细描述了逻辑连接和数学控制方程，以实现准确的预测。供应模型使用误差分析方法进行验证，包括均方根百分比误差和泰尔不平等统计，这对于评估模拟结果非常重要。此外，模拟结果的输出为决策者提供了有用的见解，因为可以进行假设分析。为了解决护理短缺问题，提出了一些建议。必须指出的是，模拟模型的结果将用于基于需求的护士劳动力预测项目的下一阶段。这项研究的影响是，它提供了更大的规划和决策能力，以及更好的预测。
