Use of spreadsheet software for short-range forecasting of pharmacy management data

Area of Science:

• Pharmacy Management
• Health Informatics
• Data Analytics

Background:

• Effective forecasting is crucial for pharmacy management.
• Traditional methods may not fully leverage modern computational tools.
• Accurate prediction of pharmacy data aids in resource allocation and operational efficiency.

Purpose of the Study:

• To describe the application of a personal-computer spreadsheet program for pharmacy data forecasting.
• To present a practical method for predicting future pharmacy performance using historical data.
• To demonstrate how spreadsheet-based forecasting can support pharmacy managers in decision-making.

Main Methods:

• Utilized exponential smoothing for the forecasting model.
• Employed a personal-computer spreadsheet program (Lotus 1-2-3).
• Developed two versions of the model: Version A for stable data and Version B for trending data, incorporating mean squared error for weight determination.

Main Results:

• Demonstrated the model's ability to forecast pharmacy data using historical information.
• Illustrated Version A's application in predicting outpatient prescriptions.
• Showcased Version B's utility in forecasting semiannual expenditures on intravenous solutions and sets.
• Highlighted the tabular and graphic output capabilities of the spreadsheet program.

Conclusions:

• Spreadsheet-based forecasting models, like the one described, can effectively quantify drug-use and personnel information.
• These tools enable pharmacy managers to present data-driven insights to hospital administration.
• The described method offers a practical approach to enhance pharmacy management decision-making through data forecasting.