Inventory Control Methods in a Long-Term Care Pharmacy: Comparisons and Time-Series Analyses

Area of Science:

• Pharmacy Operations
• Supply Chain Management
• Process Improvement

Background:

• Current inventory theory relies on simulated data, leading to frequent out-of-stock (OOS) events.
• Existing inventory replenishment models are often unrealistic and disrupt supply chains.

Purpose of the Study:

• To compare out-of-stock (OOS) events across four inventory control methods in a long-term care pharmacy.
• To evaluate the effectiveness of Six Sigma protocols in reducing OOS events.
• To assess manual, computer-assisted, and automated inventory systems with and without Six Sigma.

Main Methods:

• Daily OOS rates were collected over 11 weeks for each of the four inventory control methods.
• Statistical comparisons were made between groups, and time-series analyses assessed OOS rate changes.
• Methods included: manual, manual with Six Sigma, computer-assisted with Six Sigma, and automated with Six Sigma.

Main Results:

• Six Sigma protocols lowered OOS rates in manual systems.
• Significant differences in OOS rates were observed among the three Six Sigma systems.
• Computer-assisted and automated systems with Six Sigma demonstrated significant OOS rate reductions over 11 weeks.

Conclusions:

• Six Sigma is an effective process improvement strategy for pharmacy inventory control.
• This study uniquely used empirical OOS events, unlike prior research relying on simulated data.
• Inventory management improvements can be achieved through systematic process analysis and optimization.