Abstract
In this paper, we explore the development of a simulation model to assist in the decision-making process for monitoring the health conditions of elderly patients using data from their smart beds. The main objective of the proposed simulation model is to estimate the transitional condition of the health system by tracking patients’ physiological signals via a growth model. This approach allows the model to mimic the dynamics of various health-related issues faced by patients and the elderly. When combined with real-world data and practical expertise, the discrete-event simulation model can become a valuable tool for improving patient health and streamlining medical treatment processes. The proposed simulation model incorporates input from subject-matter experts and utilises statistical analysis to fit essential parameters based on patient data obtained from smart beds. However, authors should consider rephrasing this section to improve clarity and coherence.
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