Exponential smoothing method for forecasting drug expenditures

Abstract

A model for forecasting a hospital pharmacy drug budget is described, and its results in 10 hospital pharmacy departments are evaluated. A model for forecasting inpatient drug expenditures was developed based on the method of exponential smoothing. Exponential smoothing predicts a value based on the forecast for the prior period, with adjustment for the error of that forecast. Recent data are weighted more heavily than older data; as data become older, weights decline exponentially. The model incorporates changes in workload in addition to drug expenditure data. The variable used for workload can vary from one hospital to another, depending on the statistics that are available. The model was designed to be more accurate than current methods, easy and quick to use, and usable with a minimal knowledge of statistics and forecasting theory. The model was tested on fiscal 1988-1992 drug budget data from 10 British Columbia hospital pharmacy departments. Four departments had insufficient data; of the remaining six, the forecasting model performed better than the hospitals' current methods in four departments. The mean absolute deviation between budgeted (by current methods) and actual drug expenditures was 8.70% (range, 6.19-15.16%). The forecasting model yielded a mean absolute deviation of 5.93% (range, 3.13-7.66%). Better forecasts resulted when pharmacy medication-order volume was used as a workload variable, as compared with hospital inpatient days. An exponential smoothing model improved the accuracy of drug-budget forecasts in four of six pharmacy departments.