Forecasting hospital census at a tertiary care children's hospital.
Developing a forecasting tool for patient census allows for improved staffing, better resource utilization and mobilization, and improved timing of educational campaigns around the disease control process. Using a neural network approach we evaluated several different models and variables for predicting patient census prospectively. These initial studies enabled selection of a subset of predictor variables and show that different network models, and variables must be used based on the season.
Walton
Nephi
N
Department of Biomedical Informatics, University of Utah, Salt Lake City, UT, USA.
Poynton
Mollie R
MR
Maloney
Chris
C
Gesteland
Per H
PH
D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D005544:Forecasting; D006760:Hospitalization / Q000706:statistics & numerical data*; D006776:Hospitals, Pediatric / Q000706:statistics & numerical data; D006801:Humans; D016571:Neural Networks, Computer; D012141:Respiratory Tract Infections