Patrick Aboagye-Sarfo1, Qun Mai2, Frank M Sanfilippo3, David B Preen4, Louise M Stewart5, Daniel M Fatovich6. 1. Clinical Modelling, Health System Improvement Unit, System Policy and Planning, Department of Health, Western Australia, Australia. 2. Clinical Modelling, Health System Improvement Unit, System Policy and Planning, Department of Health, Western Australia, Australia. Electronic address: Qun.Mai@health.wa.gov.au. 3. Clinical Epidemiology Unit, School of Population Health, The University of Western Australia, Australia. 4. Centre for Health Services Research, School of Population Health, The University of Western Australia, Australia. 5. Centre for Population Health Research, Curtin University, Australia. 6. Emergency Medicine, Royal Perth Hospital, The University of Western Australia, Australia.
Abstract
OBJECTIVE: To develop multivariate vector-ARMA (VARMA) forecast models for predicting emergency department (ED) demand in Western Australia (WA) and compare them to the benchmark univariate autoregressive moving average (ARMA) and Winters' models. METHODS: Seven-year monthly WA state-wide public hospital ED presentation data from 2006/07 to 2012/13 were modelled. Graphical and VARMA modelling methods were used for descriptive analysis and model fitting. The VARMA models were compared to the benchmark univariate ARMA and Winters' models to determine their accuracy to predict ED demand. The best models were evaluated by using error correction methods for accuracy. RESULTS: Descriptive analysis of all the dependent variables showed an increasing pattern of ED use with seasonal trends over time. The VARMA models provided a more precise and accurate forecast with smaller confidence intervals and better measures of accuracy in predicting ED demand in WA than the ARMA and Winters' method. CONCLUSION: VARMA models are a reliable forecasting method to predict ED demand for strategic planning and resource allocation. While the ARMA models are a closely competing alternative, they under-estimated future ED demand.
OBJECTIVE: To develop multivariate vector-ARMA (VARMA) forecast models for predicting emergency department (ED) demand in Western Australia (WA) and compare them to the benchmark univariate autoregressive moving average (ARMA) and Winters' models. METHODS: Seven-year monthly WA state-wide public hospital ED presentation data from 2006/07 to 2012/13 were modelled. Graphical and VARMA modelling methods were used for descriptive analysis and model fitting. The VARMA models were compared to the benchmark univariate ARMA and Winters' models to determine their accuracy to predict ED demand. The best models were evaluated by using error correction methods for accuracy. RESULTS: Descriptive analysis of all the dependent variables showed an increasing pattern of ED use with seasonal trends over time. The VARMA models provided a more precise and accurate forecast with smaller confidence intervals and better measures of accuracy in predicting ED demand in WA than the ARMA and Winters' method. CONCLUSION: VARMA models are a reliable forecasting method to predict ED demand for strategic planning and resource allocation. While the ARMA models are a closely competing alternative, they under-estimated future ED demand.
Authors: Rui Zhang; Zhen Guo; Yujie Meng; Songwang Wang; Shaoqiong Li; Ran Niu; Yu Wang; Qing Guo; Yonghong Li Journal: Int J Environ Res Public Health Date: 2021-06-07 Impact factor: 3.390