About: Long-Term Prediction of Emergency Department Revenue and Visitor Volume Using Autoregressive Integrated Moving Average Model

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About: Long-Term Prediction of Emergency Department Revenue and Visitor Volume Using Autoregressive Integrated Moving Average Model Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Long-Term Prediction of Emergency Department Revenue and Visitor Volume Using Autoregressive Integrated Moving Average Model
Creator	Chen, Chieh-Fan Chen, I-Te Chou, Huei-Yin Ho, Wen-Hsien Shi, Hon-Yi Yang, Shu-Mei
Source	Medline; PMC
abstract	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.
has issue date	2011-12-04(xsd:dateTime)
bibo:doi	10.1155/2011/395690
bibo:pmid	22203886
has license	cc-by
sha1sum (hex)	b56324b4de371913188d3eae4437eaaeda3b814b
schema:url	https://doi.org/10.1155/2011/395690
resource representing a document's title	Long-Term Prediction of Emergency Department Revenue and Visitor Volume Using Autoregressive Integrated Moving Average Model
has PubMed Central identifier	PMC3235663
has PubMed identifier	22203886
schema:publication	Comput Math Methods Med
resource representing a document's body	covid:b56324b4de371913188d3eae4437eaaeda3b814b#body_text
is schema:about of	named entity 'REVENUE' named entity 'INTEGRATED' named entity 'temperature' named entity 'correlation' named entity 'revenue' named entity 'Volume' named entity 'PREDICTION' named entity 'MOVING AVERAGE' named entity 'INTEGRATED' named entity 'FORECASTING' named entity 'PREDICTION ERRORS' named entity 'RELATIONSHIP' named entity 'ABSOLUTE PERCENTAGE' named entity 'SENSITIVITY' named entity 'NON-' named entity 'INDEX' named entity 'ACTUAL' named entity 'INDEPENDENT VARIABLE' named entity 'INDICATED' named entity 'FLUCTUATION' named entity 'VOLUME' named entity 'EMERGENCY DEPARTMENT' named entity 'RAINFALL' named entity 'MOVING AVERAGE' named entity 'QUANTIFY' named entity 'CORRELATION' named entity 'VISITOR' named entity 'MODEL' named entity 'LONG-TERM' named entity 'VISITOR' named entity 'CROSS-CORRELATION' named entity 'MODELS' named entity 'MEAN' named entity 'TIME' named entity 'TRAUMA' named entity 'EVALUATED' named entity 'MODEL' named entity 'REVENUE' named entity 'MINIMUM TEMPERATURE' named entity 'MAXIMUM TEMPERATURE' named entity 'VISITS' named entity 'STOCK MARKET' named entity 'ARIMA' named entity 'USED' named entity 'ANALYZED' named entity 'PEDIATRIC' named entity 'PERFORMED' named entity 'ERROR' named entity 'VALUES' named entity 'TO IDENTIFY' named entity 'MODEL TRAINING' named entity 'FORECASTS' named entity 'BUT' named entity 'COMPARING' named entity 'USING' named entity 'VOLUME' named entity 'SPEARMAN CORRELATION' named entity 'RELATIVE HUMIDITY' covid:arg/b56324b4de371913188d3eae4437eaaeda3b814b named entity 'quantify' named entity 'time' named entity 'correlate' named entity 'relative humidity' named entity 'pediatric' named entity 'volume' named entity 'visitor' named entity 'performed' named entity 'forecasting' named entity 'training' named entity 'comparing' named entity 'volume' named entity 'Sensitivity' named entity 'independent variable' named entity 'stock market index' named entity 'Autoregressive integrated moving average' named entity 'Spearman correlation'

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