A multivariate time series approach to modeling and forecasting demand in the emergency department.
OBJECTIVE
The goals of this investigation were to study the temporal relationships between the demands for key resources in the emergency department (ED) and the inpatient hospital, and to develop multivariate forecasting models.


METHODS
Hourly data were collected from three diverse hospitals for the year 2006. Descriptive analysis and model fitting were carried out using graphical and multivariate time series methods. Multivariate models were compared to a univariate benchmark model in terms of their ability to provide out-of-sample forecasts of ED census and the demands for diagnostic resources.


RESULTS
Descriptive analyses revealed little temporal interaction between the demand for inpatient resources and the demand for ED resources at the facilities considered. Multivariate models provided more accurate forecasts of ED census and of the demands for diagnostic resources.


CONCLUSIONS
Our results suggest that multivariate time series models can be used to reliably forecast ED patient census; however, forecasts of the demands for diagnostic resources were not sufficiently reliable to be useful in the clinical setting.
Department of Biomedical Informatics, University of Utah, Health Sciences Education Building, 26 S 2000 E, Salt Lake City, UT 84112-5750, USA. spencer.jones@hsc.utah.edu
Spencer S
SS
Jones
R Scott
RS
Evans
Todd L
TL
Allen
Alun
A
Thomas
Peter J
PJ
Haug
Shari J
SJ
Welch
Gregory L
GL
Snow
D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D005544:Forecasting / Q000379:methods; D006301:Health Services Needs and Demand / Q000706:statistics & numerical data*; D006761:Hospitals / Q000706:statistics & numerical data; D006801:Humans; D007755:Laboratories, Hospital / Q000706:statistics & numerical data; D016015:Logistic Models; D015999:Multivariate Analysis; D011872:Radiology Department, Hospital / Q000706:statistics & numerical data; D015203:Reproducibility of Results; D013997:Time Factors; D000078329:Workforce