Multifactor prediction of hospital service workload.
Prediction of workload for hospital departments is a forecasting problem. Most forecasting techniques use time series methods. However, the unpredictability of hospital utilization which occurs because of environmental turbulence requires that predictions be based on strategic plans. Regression models developed from cross-sectional data can provide a methodology for linking predictions of service workload to strategic plans. The methodology is illustrated and evaluated in a pilot study, which produced models predicting measures of workload such as laboratory tests (R2 = .85), doses of medication given to inpatients (R2 = .43), outpatient prescriptions (R2 = .79), and x-rays (R2 = .86).
D005544:Forecasting / Q000379:methods; D006748:Hospital Departments / Q000706:statistics & numerical data*; D006787:Hospitals, Veterans / Q000706:statistics & numerical data*; D015233:Models, Statistical; D012044:Regression Analysis; D013647:Task Performance and Analysis; D014481:United States; D014937:Work