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Long-Term Prediction of Emergency Department Revenue and Visitor Volume Using Autoregressive Integrated Moving Average Model
Joint Authors
Ho, Wen-Hsien
Chou, Huei-Yin
Shi, Hon-Yi
Chen, Chieh-Fan
Yang, Shu-Mei
Chen, I-Te
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2011, Issue 2011 (31 Dec. 2011), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2011-12-04
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
This study analyzed meteorological, clinical and economic factors in terms of their effects on monthly ED revenue and visitor volume.
Monthly data from January 1, 2005 to September 30, 2009 were analyzed.
Spearman correlation and cross-correlation analyses were performed to identify the correlation between each independent variable, ED revenue, and visitor volume.
Autoregressive integrated moving average (ARIMA) model was used to quantify the relationship between each independent variable, ED revenue, and visitor volume.
The accuracies were evaluated by comparing model forecasts to actual values with mean absolute percentage of error.
Sensitivity of prediction errors to model training time was also evaluated.
The ARIMA models indicated that mean maximum temperature, relative humidity, rainfall, non-trauma, and trauma visits may correlate positively with ED revenue, but mean minimum temperature may correlate negatively with ED revenue.
Moreover, mean minimum temperature and stock market index fluctuation may correlate positively with trauma visitor volume.
Mean maximum temperature, relative humidity and stock market index fluctuation may correlate positively with non-trauma visitor volume.
Mean maximum temperature and relative humidity may correlate positively with pediatric visitor volume, but mean minimum temperature may correlate negatively with pediatric visitor volume.
The model also performed well in forecasting revenue and visitor volume.
American Psychological Association (APA)
Chen, Chieh-Fan& Ho, Wen-Hsien& Chou, Huei-Yin& Yang, Shu-Mei& Chen, I-Te& Shi, Hon-Yi. 2011. Long-Term Prediction of Emergency Department Revenue and Visitor Volume Using Autoregressive Integrated Moving Average Model. Computational and Mathematical Methods in Medicine،Vol. 2011, no. 2011, pp.1-7.
https://search.emarefa.net/detail/BIM-468776
Modern Language Association (MLA)
Chen, Chieh-Fan…[et al.]. Long-Term Prediction of Emergency Department Revenue and Visitor Volume Using Autoregressive Integrated Moving Average Model. Computational and Mathematical Methods in Medicine No. 2011 (2011), pp.1-7.
https://search.emarefa.net/detail/BIM-468776
American Medical Association (AMA)
Chen, Chieh-Fan& Ho, Wen-Hsien& Chou, Huei-Yin& Yang, Shu-Mei& Chen, I-Te& Shi, Hon-Yi. Long-Term Prediction of Emergency Department Revenue and Visitor Volume Using Autoregressive Integrated Moving Average Model. Computational and Mathematical Methods in Medicine. 2011. Vol. 2011, no. 2011, pp.1-7.
https://search.emarefa.net/detail/BIM-468776
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-468776