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Related Experiment Videos

Exponential smoothing method for forecasting drug expenditures

M M D'Sa1, R S Nakagawa, D S Hill

  • 1Division of Pharmacy Administration, Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, Canada.

American Journal of Hospital Pharmacy
|October 15, 1994
PubMed
Summary

This study introduces an exponential smoothing model to forecast hospital pharmacy drug budgets, improving accuracy in four of six tested departments. The new model offers a more precise and user-friendly approach to budget planning.

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Area of Science:

  • Health Economics
  • Pharmacy Management
  • Operations Research

Background:

  • Accurate hospital pharmacy drug budget forecasting is crucial for financial stability.
  • Existing forecasting methods may lack precision and ease of use.
  • The need for a statistically sound yet accessible forecasting model is evident.

Purpose of the Study:

  • To develop and evaluate an exponential smoothing model for forecasting hospital pharmacy drug budgets.
  • To assess the model's accuracy compared to current forecasting methods.
  • To determine the impact of workload variables on forecast accuracy.

Main Methods:

  • Developed a forecasting model using exponential smoothing, weighting recent data more heavily.
  • Incorporated drug expenditure data and workload variables (e.g., medication-order volume, inpatient days).

Related Experiment Videos

  • Tested the model on fiscal 1988-1992 drug budget data from 10 British Columbia hospital pharmacy departments.

    • Main Results:

    • The exponential smoothing model achieved a mean absolute deviation of 5.93%, compared to 8.70% for current methods in six departments.
    • The model demonstrated improved forecast accuracy in four of the six departments.
    • Using pharmacy medication-order volume as a workload variable yielded better forecasts than hospital inpatient days.

    Conclusions:

    • The exponential smoothing model offers a more accurate and user-friendly method for hospital pharmacy drug budget forecasting.
    • The model's performance suggests its potential for wider adoption in pharmacy financial planning.
    • Optimizing workload variable selection can further enhance forecasting precision.