Alternative Methods for Forecasting Variations in Hospital Bed Admission
S. Sarifah Radiah Shariff, Mohd Azuan Suhaimi, Siti Meriam Zahari, Zuraidah Derasit
Abstract
The Malaysian healthcare system is well-being recognized for providing a wide range of access to primary healthcare. The number of hospitals is found to be growing in line with the increase in population. However, over-crowding has become the most common scene that people see in every hospital. The number of patients being admitted may somehow mislead healthcare planners, and thus causing them to underestimate the resources that are required within the hospital. Thus, this study aims to identify better forecasting models for variations in hospital bed admission considering State Space Model (SSM). Data on the admission rate of a state hospital was collected, spanning the period of historical data from 2001 until 2015. The findings indicate that State Space model can outperform common model due to its lower Mean Squared Errors. Female aged between 25 -34 years old are found to be having the highest variation, which could lead to unpredictable in terms of being admitted to hospital.
Keywords
Forecasting Variation, Bed admission, State Space Model
DOI:
http://doi.org/10.11591/ijeecs.v9.i2.pp410-416
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Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).
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