Modeling Nurse Time For School Health Service Using System Dynamics

• Main Authors: Abal Abas, Zuraida, Zainal Abidin, Zaheera, Ramli, Mohamad Raziff
• Format: Article
• Language: English
• Published: Blue Eyes Intelligence Engineering and Sciences Publication 2019
• Online Access: http://eprints.utem.edu.my/id/eprint/24447/2/PAPER%20_%20NURSE%20TIME%20MODEL%20SCHOOL%20HEALTH%20SERVICE.PDF; http://eprints.utem.edu.my/id/eprint/24447/; https://www.ijitee.org/wp-content/uploads/papers/v8i12/L28001081219.pdf

One of the national primary health care services in Malaysia is school health care. This care is very crucial as it ensures that, countrywide, the health of students from the age of five to fifteen is in a good condition. In Malaysia, nurses hold a major responsibility for delivering the school health service. However, there is no solid research investigating the nursing time required to deliver school health services. This paper presents a system dynamics model representing the specific school health services delivered by nurses. System Dynamics is a computer-aided approach to policy analysis and design. In this paper, the system dynamics model are represented by several causal loop diagrams which covers all the school health activities and is able to determine the projected total nurse time required in delivering the service. The baseline simulation result of the nurse time required for delivering school health services is about 1080000 hours in year 2030, which is equivalent to 680 full time equivalent (FTE) nurses. Furthermore, various what-if analyses are tested with the model, as it is important for policy makers to investigate various scenarios for an effective decision-making process. In other words, the theme of the study is to understand the implication of the changes in school population size and the modification of certain activities in the school health program on the nurse time spent delivering school health service by developing a dedicated forecasting system dynamics model for school health. The time horizon for the forecasting is from 2018 until 2030.