A supply model for nurse workforce projection in Malaysia.

Autor: Abas ZA; 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. zuraidaa@utem.edu.my., Ramli MR; 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., Desa MI; 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., Saleh N; Planning Division, Ministry of Health Malaysia, Kompleks E, Presint 1, Pusat Pentadbiran Kerajaan Persekutuan, 62590, Putrajaya, Malaysia., Hanafiah AN; Planning Division, Ministry of Health Malaysia, Kompleks E, Presint 1, Pusat Pentadbiran Kerajaan Persekutuan, 62590, Putrajaya, Malaysia., Aziz N; Planning Division, Ministry of Health Malaysia, Kompleks E, Presint 1, Pusat Pentadbiran Kerajaan Persekutuan, 62590, Putrajaya, Malaysia., Abidin ZZ; 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., Shibghatullah AS; 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., Rahman AFNA; 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., Musa H; Excellence Centre of Innovation, Technology and Entrepreneurship Development (ExCITED), Faculty of Technology Management and Technopreneurship, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya, Durian Tunggal, 76100, Melaka, Malaysia.
Jazyk: angličtina
Zdroj: Health care management science [Health Care Manag Sci] 2018 Dec; Vol. 21 (4), pp. 573-586. Date of Electronic Publication: 2017 Aug 18.
DOI: 10.1007/s10729-017-9413-7
Abstrakt: 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.
Databáze: MEDLINE
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